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Gartner Blog Network

  • Speculating on Buying Behavior and Inflation Using Enterprise Technology Adoption Profiles
    by Hank Barnes on June 14, 2022 at 12:51 pm

    Rising inflation, the Russian Invasion of Ukraine, and other tensions create a lot of uncertainty in markets.   But uncertainty is nothing new.  We just went through it (and are still going through it to a degree) with COVID-19.   And there will always we changing circumstances in markets that we have to deal with.  Our forecast team is working continually to understand how this impacts what people buy and how much.   That is where behaviors are most likely to change.  But how they buy will probably not change significantly, beyond the potential for increased scrutiny of purchases. All of that being said, I do think this is a good time to remember that you can't really understand what is going on by assuming that all customers will react the same way.  In times of crisis or increased scrutiny, some organizations see an opportunity to gain, or strengthen, competitive advantage knowing that their competitors are likely to be more risk averse.   So, with everything going on, I thought it might be helpful to look at some still relevant Gartner data using our Enterprise Technology Adoption (ETA) profiles.   This is from a study we conducted  about buying efforts undertaken in 2019 and 200.  We looked at the number of buying efforts organizations pursued--and how many of them were effectively canceled --- the decision that was made was not to do anything.  I've probably shared some of this before, but it is worth a new look. Part of what we wanted to do was see how much the pandemic impacted buying efforts.  We were expecting a dramatic difference in the number of efforts pursued in 2020 vs 2019.   We did not see it.  Basically, for every ETA grouping, and overall, there was a slight increase in buying efforts considered in 2020 compared to 2020.  But the more interesting thing would have been cancellations. Surely, we would see a difference there.   Not really. The only two groups that canceled a higher percentage of buying efforts in 2020 compared to 2019 were the two strict planning organizations - Fast Followers and Disciplined Followers.  This does reflect the discipline they bring to the decision process.  For every other group, they canceled the same percentage or less in 2020.     The overall % of cancellations is just more evidence of the New Chasm.  The organizations that are more likely to be effective at buying, namely the Agile Leaders, Fast Followers, and Disciplined Followers cancel a significantly lower percentage of buying efforts than those that are on the other side of the new chasm. Just to add a bit more detail before discussing some speculation on what this might mean for the current, and future situations,  we can look at the percentage of the 2020 efforts that were cancelled due to implications of the COVID-19 pandemic. Here the picture is a bit different.  The more effective buyers were more likely to have canceled buying efforts due to COVID than the others! Implications As uncertainty mounts, the macro trends of markets, using our forecasts, are important to understand.  But for specific opportunities, you can't think macro--you need to think micro-and truly work to understand the situation of your customer.  The questions I would be asking: What is the ETA of the prospect? How important is the project for which your product or service is being considered? How much risk is associated with the project? How does the cost outlay for the customer look over time? and more But above all, don't make blanked assumptions.    You can start with the knowledge that more than 1/2 the market struggles--but many still invests.   Those that are more likely to cancel don't cancel everything--but you will need to connect and understand other issues and dynamics. Just as the more disciplined and effective buying organizations gain advantage from that discipline, now is the time to step up your efforts in building a culture of deep understanding of the customer.  Doing so will give you a competitive advantage.   We'll talk about this more at the virtual Gartner Tech Growth and Innovation Conference.  Hope you join us.    

  • 4 Types of B2B Buying Organizations: Align Your Marketing Accordingly
    by Rick LaFond on June 14, 2022 at 9:01 am

    The only constant in life B2B buying is change. Ninety-four percent of B2B purchases are made amid organizational change, according to the 2021 Gartner B2B Buying Survey. The top organizational changes that contribute to a B2B buyer's need to make a purchase include: digital transformation, a change in operations, and a response to new regulatory requirements. A B2B buyer’s ability to successfully navigate those changes can make or break their ability to buy and implement a new solution. Fortunately, both marketing and sales teams can offer information, guidance and tools to help buyers confidently understand and manage the change(s) contributing to the purchase need. A Gartner survey of 725 B2B buyers revealed four distinct enterprise customer profiles. These profiles have stark differences in how they manage change, as well as how they behave during the buying journey. We’re calling these four profiles “Gartner’s Enterprise Change Readiness Profiles”. Which Profile(s) Represent Your Customers? These four profiles span across industries, purchase categories and company sizes. Fence-Sitters are the most common profile, representing 39% of survey participants. You might be able to instantly recognize which profile best aligns to the majority of your customer base. If you're unsure, share this blog with some members of your sales team. They should be able help you find the right answer. Alternatively, your customer base might consist of a more even mix of two-to-four of these profiles. You might also see some themes across different product and/or customer segments. Tailor Demand Generation To These Profiles Each profile requires a different combination of digital content, guided selling tools and sales support to make high-quality purchases. For example, Adventurers are organizations whose openness to risk and change exceeds their practical readiness to successfully execute change. For customers that fall into this profile, you should offer information and tools that prompt buyers to engage in productive reflection. Help them reexamine their own needs and goals to ensure these customers fully understand what is required to make their change successful. Provide prescriptive advice and practical support for completing the tasks associated with managing the change contributing to their purchase need. To learn more about the characteristics of each of these profiles, as well as to collect guidance on how to best engage with each of these profiles, access this detailed report: Boost B2B Demand Generation Performance Using Gartner’s Enterprise Change Readiness Profiles (Gartner login required).

  • Scenario Planning for Seasonality — The Ultimate Duet Between Demand and Supply
    by Sarah Gilchrist on June 14, 2022 at 9:00 am

    Summer finally feels like it’s arrived in the U.K. The sun is shining, Wimbledon is on the horizon and families up and down the country are sparking up their barbeques. Whilst many British residents associate the summer sunshine with relaxation — and maybe even a well-earned summer holiday — there will be others in the country for which this is the make-or-break selling period for their company’s seasonal products (e.g., alcoholic summer spritzers, barbeques and Father’s Day gifts) Here lies the crux of the seasonal product supply chain. Months of supply chain planning and production have been orchestrated, and now the only question to be answered is “Will the sales be in line with the forecast?” Facing Into the Decoupling Between Demand and Supply For products with highly seasonal demand, supply chain leaders must acknowledge, and proactively face into, having to finalize decisions on supply commitments in the context of incomplete demand intelligence. This challenge is not unique to seasonal products, however, it is amplified by the stockbuild requirements often required to service the huge peak in sales. Key to maximizing the seasonal peak’s profitability is ensuring that commercial teams are engaged up front and in advance of the supply plan being “locked and loaded.” Insights around projected category size and market share, joint business plans with key customers and advertising and promotional plans all provide assumptions to underpin the size of the demand peak. Identifying Risk and Opportunity to the Sales Forecast Through Scenario Planning Companies can leverage commercial insights further by using scenario planning within their S&OP process. Scenario planning allows companies to take proactive, financial-based decisions to trade off the opportunities of seasonally driven sales, often at optimal margins, versus the risk of closing the season with unsold stock. At best this stock might sit on the balance sheet for a year and, at worst, depending on shelf life, may be at risk of write off. To work at its best, scenarios should focus on variables that might cause a positive or negative variance around the demand plan during the sales peak. Such insights and intelligence lie in the heads of the commercial teams in the business. Therefore, it is critical that intelligence and insights come from the demand side of the business, rather than being estimated or assessed in isolation by those further upstream in supply chain. Consider Not Only External Variables, But Also Internal Levers Splitting the factors that might impact sales into external and internal drivers helps provide a structure (see Figure 1). It is also an important distinction to make. A company will have limited ability to influence the external factors: however, the internal levers are within its control. Data and intelligence from sales and marketing teams on understanding, upfront, what internal levers exist to mitigate external headwinds allows different scenarios to be modeled from both a volume and value perspective. For example, commercial colleagues might be able to provide intelligence such as: “An x% uplift in sales or a y% increase in market share could be stimulated by an extra z$ investment in marketing” Upfront information like this is scenario-planning gold dust! These sorts of inputs allow business leaders to make informed, assumption-based and quantified decisions upfront about the financial consequences of selling through seasonal stock builds. Constructing various scenarios that assess the impact of a variety of “what if” scenarios based on both external variables and internal lever responses enables potential outcomes to be assessed before irreversible decisions are made. Five recommended steps to bring the theory to life Start your engagement with stakeholders early — If your seasonal products have an annual cycle, you only have one chance a year to set out your stall. Identify who will sponsor your approach — Ultimately, this needs to be the person in your business that cares how both revenue and costs impact the bottom line and is also invested in the inventory impact on cashflow. Partner with finance — Switching on any internal lever to stimulate sales of prebuilt stock will almost certainly trigger a cost. Collaboration with finance should both facilitate predicting the financial outcomes of different scenarios and also provide an ally in pitching your proactive, scenario-planning approach. Document the lessons — As you practice the strategy, keep a record of what worked and where there were opportunities for improvement, both in terms of data and approach. This ensures that valuable knowledge is incorporated into planning for the next peak. Ensure active decisions are made in a timely manner — By its nature, this supply chain context is time sensitive. If a proactive decision is not made, a passive one will be made, by default, in its place.   Sarah Gilchrist Director Analyst Gartner Supply Chain Sarah.Gilchrist@gartner.com   Listen and subscribe to the Gartner Supply Chain Podcast on Gartner.com, Apple Podcasts, Spotify and Google Podcasts

  • Where Machine Intelligence Excels over Human Intelligence
    by Anthony J. Bradley on June 14, 2022 at 8:57 am

    As I have stated previously, and hopefully clearly, I prefer the term “machine intelligence” over “artificial intelligence.” The former term favors the benefits of machine intelligence. The AI term leads to a comparison with human intelligence with a bent towards how machine intelligence falls short. The comparison to human intelligence is not constructive because, in reality, machines have their own approach to “ intelligence.“ An approach that far exceeds many capabilities of human intelligence. This is why machine intelligence and human intelligence are disparate and compatible, not interchangeable.   Machine intelligence is intelligent in its own way.    With machine intelligence, machines substitute pattern construction for learning, pattern recognition for understanding, and probability analysis for judgment in decision making. These are the core capabilities behind the machine learning subset of AI.    Some artificial intelligence pundits seem to downplay what machines can accomplish because, compared to human intelligence, it is not “true intelligence.” In my opinion, this misses the point. Just because the means are different doesn’t mean the ends aren’t just as, if not more, valuable. Although machines take a different approach to intelligence, this doesn’t mean that it isn’t tremendously beneficial.   Machine intelligence is a tool, just like human intelligence. Just like humans, MI can make bad decisions based on bad data. Like humans, MI can be manipulated and used towards nefarious means. Just like humans, MI needs governance to reach its positive potential. I’m not positioning MI as this pollyannaish force for good. But It is a powerful tool capable of “intelligent” work in its own variant of the term.   Machine intelligence is better than human intelligence in many ways.   The machine intelligence combination of pattern construction, pattern recognition and probability-based decision-making is indeed very powerful. This combination enables data engineers, data scientists and computer programmers to build algorithms that can see. They can create, read, write, listen, respond, decide and act. Machines do these “intelligent” activities differently from humans and with some superhuman capabilities.     You can sum up what machine intelligence does very well with the three Ps of patterns, probabilities and performance.  Machines are far better than humans at identifying patterns in enormous amounts of data.   A big strength of machine learning is finding patterns in large amounts of data. The “big data” concept began gaining general acceptance about a decade ago. But we are now past “big data” into unimaginably enormous data. And the rate of data accumulation is growing exponentially with the combination of social media, the internet of things (IoT) and cloud computing. This ever expanding volume of data makes algorithms indispensable. We now have far more data than humans can absorb with even the best dashboards. There is little value in these enormous data sets without algorithms to help make sense of them.    Finding patterns in large amounts of data is the basis for machine learning. The “learning” aspect is the creation of algorithms that identify select patterns in the data. So, computers don’t learn the way humans do. Instead, they learn the way machines do, through pattern-based algorithm training. For example, using a large number of images of dogs, a computer algorithm can randomly assign and reassign variable values to pixel patterns until the algorithm establishes a formula that represents key pixel pattern characteristics of dog images. This is pattern construction through deep learning neural network technology.   If pattern algorithm creation simulates human learning, pattern recognition simulates human identification. After the “pattern constructed“ algorithm is complete, you can input a new image and the algorithm will predict, using probability mathematics, whether it is or is not a dog based on how well the pixel patterns in the new image match the “dog” pixel patterns in the algorithm.   Algorithms are highly effective at recognizing objects within images and they get better every day. The same goes for identifying patterns in video, sound, light, text, and, of course, structured data. Earlier, I specifically used the phrase “simulates human identification” vs. simulates human understanding. Because although the algorithm may recognize pixel patterns associated with the label “dog,” it doesn’t understand dogs. It doesn’t know that dogs are man’s best friend, that they like to fetch things, that you can train them with treats, etc. It simply recognizes pixel patterns with a strong match to those of dog images.    For example, the US Postal service has now deployed an edge AI system using computer vision and analytics to process over 20 terabytes of mail image data per day. Using this image data, AI accomplishes tedious work at great scale. In addition to package tracking, it identifies, deciphers and repairs damaged barcodes. It also checks to see if postage is correct. And the USPS is just beginning to tap into the power of their growing image AI capabilities.     Machine intelligence also can create content from patterns   Machine intelligence doesn’t stop at pattern construction and pattern recognition. With machine intelligence advancements like generative adversarial networks (GANs) the pattern recognition algorithms can be “run backwards” to generate rather than identify content. This is the technology behind “deep fakes.” Machine intelligence can create. This is ground breaking. Over time, as these technologies evolve further, machines will be capable of generating text, images, video and sound content that is indistinguishable from the real thing. Yes, this certainly has numerous scary implications but the positive applications are astounding. Machines can very rapidly generate alternative designs that meet stipulated criteria.    For example, IBM has spearheaded new AI technology that can generate designs for new antibiotics and antivirals. Essentially, researchers apply AI to large data sets to determine   patterns of peptide molecule binding relationships. AI identifies how molecules assemble to perform certain functions. Researchers then determine the characteristics they are looking for in an antibiotic. They input these characteristics into the algorithm and it generates alternative molecule designs that meet the criteria. Researchers then test these designs to find the most effective antibiotic.       Another more famous example is AlphaFold where AI is used to generate protein folding patterns. How a protein folds determines its function. Prior to AlphaFold, protein folding was a tedious, long, expensive trial and error effort. Referring to AlphaFold, protein folding expert and CASP co-founder John Moult is quoted as saying, “This is the first time a serious scientific problem has been solved by AI.”      Does it matter that the algorithm doesn’t “understand” the patterns it recognizes or generates? Theoretically, maybe. But practically, machine intelligence can accomplish a large variety of highly valuable work finding, identifying and using patterns.       Machine Intelligence substitutes probability mathematics for human judgment and decision making    Probability math is the foundation of machine learning.With probability based algorithms, machine intelligence can run through huge amounts of data, assess a multitude of potential options and then consistently select those with the highest probability of meeting the desired goal. This MI capability far exceeds those of even the world's smartest mathematicians. The capability delivers a powerful tool in making well understood business decisions at great scale.     With intelligent customer relationship management (iCRM) capabilities, large companies and service providers are using AI to process millions of prospecting email responses and automate decisions on prioritizing them as sales leads.   Some financial institutions are using AI to comb through enormous amounts of customer data to identify good candidates for a new product or service.     It is well known that facebook and Google apply AI against unimaginably large amounts of member activity data to make automated decisions on what content to serve them next. They also apply the same approach to decide what advertisements to feed members while trying to serve both user and advertiser needs.    This is algorithm driven probability based decision making that happens everyday across every industry and every geography.         Machine Intelligence outperforms humans in speed, scale and consistency   The performance of computing machines is well understood. Computers operate at astounding speeds and scale. They can consistently execute tasks with great precision at tremendous scale. Computers don’t get tired, frustrated, angry or rebellious. They do what they are asked with great efficiency. Scale, speed, endurance, consistency and precision have long been a core value proposition of computing machines. We have long capitalized on this performance by programming computers to execute procedural tasks. But now we have graduated from these more transactional tasks to more “cognitive” like tasks. And all the core benefits translate well to machine intelligence and its capability to detect issues, predict outcomes and facilitate decisions.    This characteristic of machine intelligence can’t be overstated. Why? Because it takes “intelligence” far beyond the human performance spectrum. When you hear about how AI will replace human jobs, it is almost always one-sided and limited to the human scale world. This may make sense for job losses but not for gains. Machine intelligence takes us far beyond the physical human world and opens up the hyper-human realm for new opportunities. This hyper-human realm operates at spatial, time and spectrum scales that are far too small or far too large for unaided human abilities. For example, the combination of microbiome ML, smart-microscopy and bio micro-robotics is turning human biome engineering (managing the bacteria in our gut) into an industry of its own.    At the other end of the scale spectrum, AI was required to combine data from eight observatories across six geographies to help develop the first ever actual picture of a black hole. I will post more in the future on hyper-human hyper-specialization and the explosion of AI generated jobs.        Business leaders can use the 3Ps to direct machine intelligence at the right business problems   Machine intelligence applies well to business challenges involving monitoring activities at great speed and scale to detect and respond to potential issues. Finding important business patterns in large amounts of customer or market data is also a clear application of machine intelligence. Any business challenge requiring pattern recognition, probability-based decisions and automated actions in a high performance environment is potentially a strong fit for machine learning.

  • Expect buyers to ask for more ‘skin’ in the game from providers in the coming recession.
    by Mark P. McDonald on June 14, 2022 at 7:53 am

    When the current economic and political turbulence turns into a formal recession is anyone’s guess. Enterprise IT spending will remain relatively strong. There are early indications that the nature of tech spending could change, namely that CIOs, Procurement, and IT buyers will ask their providers to put more of their revenue at risk – aka ‘skin’ in the game. The logic behind asking for more provider ‘skin’ in the game. Uncertainty increases as turbulence turn toward recession. Normally enterprises would pull back on spending. However, enterprises can be expected to continue IT investments in digital technologies. Companies in progress with digital transformation will need to complete it – quickly – as being half digital is the worst position a firm could be in. Buyers naturally want more downside protection.  That downside protection calls for providers putting more of their revenue at risk. There are several reasons for this move, in no particular order: Immediate demand for digital transformation is off the charts. Normally, providers in a high demand environment would be charging a premium rather than putting revenue at risk. The pending recession creates an incentive to secure future revenue, particularly among less powerful providers.  This sets the stage of trading future revenue with some downside risk. Buyers want to keep providers focused on them in a high demand environment, particularly buyers at companies farther behind the digital curve. They want providers putting their best efforts toward them. Buyers should be willing to trade paying higher margins on digital transformation work in exchange for that focus. Having provider skin in the game, even at higher margins, helps balance that type of deal. Providers in the past, have used a willingness to put skin in the game as a way of nudging clients off the fence. Not sure you want to do this, then let us share in some of the risk because it’s the right thing to do for your business and hey it shows our commitment. This ‘marketing’ strategy is more likely among the middle to lower end of the provider market as they seek to lock in deals. Buyers, particularly procurement and IT, will see having skin in the game to ‘de-risk’ digital transformation. In a way it does, but only if the provider fails to execute, but seeking providers to be at risk will help justify digital transformation cost and disruption. Skin in the game is not the same as committing to a business outcome. Having skin in the game, is a common recessionary play.  Putting revenue or margin at contractual risk is not the same a business outcome-based strategy. Outcome based arrangements like outcome pricing or outcome contracts base provider payment on provider performance. If the provider performs according to the contract, then they get paid.  That is radically different from customers and providers jointly sharing risk and reward based on realizing the benefits of business outcomes. See Why B2B Tech Companies need to value results over provider effort, for some additional points. What do we mean by an outcome?  More on that latter Related posts: The Rumor and the News, making sense of Turbulent Times Why B2B Tech Companies need to value results over provider effort. Turbulent Times Turning Toward Global Recession ? Digital Retooling > Turbulence and Recession Technology’s Evolving Covenant with Business

  • 3 Takeaways for Adapting Your Leadership Style to Uncertainty and Disruption
    by Derek Frost on June 14, 2022 at 7:14 am

    We're at the mid-point of another tumultuous year, with deepening anxiety about a range of issues: the war in Ukraine, the prospect of famine in vulnerable countries, an escalation of the sickening plague of gun violence in the United States, ongoing Covid mutations making their way around the world... just to name a few of the more acute worries on what has become a lengthy list. Meanwhile, the economy is giving off mixed signals at best, as inflation seems to have become entrenched in our late-pandemic world, supply chains groan under the weight of recent lockdowns in China and other, more systemic, factors, and stock markets sink into bear-market territory.   How are banking leaders meeting the current (fraught) moment? Against this backdrop, I had the chance some weeks ago to speak with a number of senior banking executives about their personal approach to leadership. How are they coping with ongoing uncertainty and disruption, both personally and professionally? And how does that translate into the way they support their teams? Some of these leaders had gathered virtually late last year for a discussion led by my colleague Mary Mesaglio on finding purpose and becoming a better leader. I wanted to catch up with them (happily, in person this time) to get a sense of what has changed in their lives as leaders since then... and what deeper lessons they have drawn from their recent experiences. Our conversation yielded three key takeaways for executives trying to adapt to these turbulent times:   1. Strong, confident leaders are candid, transparent, and unafraid of showing vulnerability. The candor---and vulnerability---of the people with whom I spoke were notable. Leaders, by nature, tend to be hyper-aware of the image they project; as a result, they won't often acknowledge being especially worried or uncertain. The executives I talked with, though, admitted to not having all the answers. Also: --They confessed to bouts of angst, pressure, and exhaustion, in addition to a lack of clarity. --Many are very concerned about the well-being of their teams: one executive mentioned that her bank routinely holds active shooter drills in some locations. --Perhaps one of the more telling comments was from a leader who said he felt a blend of despondence and confidence---a "mixed signals" emotional environment, if there ever was one. The vulnerability that this group felt comfortable sharing appeared to reflect their belief in themselves as leaders and their desire to do the right thing. After all, if you really trust in yourself, you don't obsess about how you might be coming across. You're comfortable being exactly who you are. These executives seemingly understand that the times in which we live pose unique, thorny challenges, rendering many traditional notions of leadership obsolete.   2. Use your openness, emotion, and empathy to foster a resilient, cohesive culture for your team. The second takeaway also had to do with vulnerability, but from a different angle: its role in creating a cohesive and trusting culture. (And culture certainly needs special nurturing in today’s "new-normal" remote or hybrid environments.) One leader, underscoring just how crucial culture is, made the point that only in a crisis do you know for sure if it's there or not. If it does show up, you'll realize you’ve succeeded in creating the right culture. Another executive then helped shed light on why vulnerability matters when it comes to culture. His key leadership lesson over the past two years, he said, was how important it is to be transparent and unafraid of appearing vulnerable. In other words, admit it if you don't have all the answers, and keep communications open about the challenges you face, the decisions you're wrestling with, and what you expect of your team. This can bring multiple dividends: --If you're clear about problems and what's being done to address them, that will help prevent the kinds of rumors and unfounded speculation that can stir up collective anxiety. --If you show emotion and behave transparently, your staff will be more comfortable doing the same. --And that transparency, together with a willingness to reveal vulnerability (part of what makes us human, after all), can, in turn, help an empathetic, open, and cohesive culture grow within your organization.    3. How to sail the unknown? Surround yourself with a diversity of perspectives. Reward honesty. And don't be afraid to change course.  The third takeaway was about flying blind: navigating a world of incomplete, misleading information, a world in which it seems harder than ever to gauge where the winds will blow from next. As my colleague Ben Seesel remarked to these executives, "No business school taught you how to make decisions in this environment!"  So, as a leader, what should you do? --Surround yourself with sharp and informed people. Get a diversity of perspectives in order to weigh risks and chart the course ahead more effectively. --That first point speaks to the need for a culture of "brutal honesty": reward staff for speaking truth to power, for giving you news you may not like. And be sure to create a safe environment for them to do so. Then move quickly to solve whatever problems have been surfaced.  --And speaking of a culture of honesty: don't be afraid to admit your own mistakes. Be willing to change course. Backtracking or turning is not a sign of weakness. (Next time you're at the beach, watch how sailboats tack through strong winds that might otherwise impede their progress, and remember that Odysseus, after a ten-year voyage of many a twist and turn, made it home at last!)   Learn, adapt, and remember our shared humanity. The past few years have been exceptionally hard: an era of deep uncertainty, loss, and change. The executives with whom I spoke have not only been weathering these times, but trying to learn from what they’ve been through and adapt their approach accordingly. The best leaders will endeavor to map the way forward with empathy, openness, and an appreciation of just how important a caring, communicative culture is.   

  • The End of the D&A Center of Excellence?
    by Andrew White on June 12, 2022 at 6:05 am

    News last week: Meta shunts their AI hubs into their business product Units. That’s the message reported in the papers Tuesday.  See Wall Street Journal and Meta shakes up AI unit Amid drive for faster growth. The Trouble with Organizations The problem or trigger is not unknown: a centralized team tends to specialize in skills or capability but it’s often remote from the business roles who need that capability. The functions are centralized and operate as a shared service to business functions or units.  This creates one of the oldest customer-service arguments; does the centralized service meet the needs of the distributed 'customer'?  It’s an organizational gulf that is hard to cross. In the past a customer mentality, not unlike "real" customers outside your organization, has been used to help drive success.  This worked in only a few places.  The application of lean, agile and DevOps has been used recently, with mixed results. Not least because such practices evolved for other challenges. The Rise and Fall and Afterward Over the years we have seen the rise and fall of centralized teams. Rather than rise and fall, it’s more like a seven year itch. Organizational structures tend to vacillate every few years. It would seem that we are in a new cycle where the focus is remote, distributed capabilities rather than fatter, centralized structures. The case reported in the WSJ article suggests that time to value is hard to reduce in centralized teams.  The inability to organize the central resource with the remote "customer" needs is the great challenge. Shifting skills to the edge and away from the center should put the capabilities in more direct control of business or "customer" needs.  The result will be that some capabilities will need to be duplicated across business functions or units.  This will likely increase costs and duplicate investments. As such the key here is not really where and when to centralize or distribute. The real challenge here is coordination. And that is the real battle field. Meta May experience shorter time to value in their next cycle. But their costs will increase. Rather than assume your organizational decisions are resolved by shunting the team skills to the edge, real success over time will be in how and who coordinates all the work. This is where your Chief Data and Analytics Officer (CDAO) role is key. The right personality, the right skills, will orchestrate and progress value delivery better than any one dedicated organizational approach. So don’t fret the Meta change: focus on the hinge or fulcrum that connects all the piece parts. For some related research: Where to Best Organize Data and Analytics.

  • 4 Reasons Why Financial Services Talent Leaves
    by Gladys Yeo on June 8, 2022 at 9:42 am

    “Frontline talent attrition levels are at an all-time high since the pandemic, it’s taking us much longer than usual to find the right fit” “We’ll have to likely use higher compensation packages to retain and attract talent in this market”   The above are some of the concerns that financial services leaders have shared with me during our conversation over the past few months. Hiring and retaining talent in this competitive job market is an ongoing challenge for leaders today. Some of the concerning statistics we’ve seen so far show that twenty-five percent of FS frontline talent reported a high intent to leave and nearly two-thirds would leave their current firm for a growth opportunity. Furthermore, about two-thirds of  senior FS executives surveyed in Gartner’s Financial Services Business Priority Tracker in March 2022 are expecting workforce shortages across lines of business and functions (e.g. business operations, contact centres, frontline staff) over the next 12 months But before you walk or dial into your next executive meeting to discuss your hiring and retention strategy, it’s important to understand “why” your people leave in order to determine where your bets are best placed.  One way to illustrate this is to think of your employee as an individual who is selling their house, and their reasons for selling can fall into 1 out of 4 scenarios.   1st Scenario: “There are cracks in the ceiling, the house needs repairing.” This implies poor managers, lack of employee recognition, or lack of professional growth opportunities. In short, your firm’s work experience is broken and in need of repairs. Frontline employees in FS are highly ambitious individuals who rank career growth and personal development as the two most important motivators. In this scenario, you will need to evaluate the way managers lead in the organisation as well as improve the visibility and opportunities for career development.    2nd Scenario: “There’s nothing wrong with this house, but I need an extra room so this house no longer meets my needs.”  In the last few years, new employee needs have emerged such as a greater demand for work flexibility or a greater interest in Environmental, Social, and Governance related issues.  Employees now overwhelmingly favour a hybrid work model - with 56% of operations employees stating that the ability to work flexibly would impact their decision to stay at their organisation. If employees sense a misalignment between these new personal needs and the overall employee value proposition of the organisation, your leadership will need to take a greater role in the things that matter to them.   3rd Scenario:  “The current house is fine, but the other houses are looking better.” In this scenario, other financial services or non-financial services companies are offering a better employer brand or more competitive compensation for critical talent. Firms with deeper pockets are willing to spend more to acquire the talent needed to drive growth. Some of the most sought-after roles within the FS industry include software developers, customer service representatives, sales agents, and financial analysts.  You will feel the most pain in this scenario. It is incredibly easy for employees to peruse the offerings of other firms with little effort, while leaders are typically faced with only one main strategy: that is to match the perceived better offerings of other companies.  However, with limited resources and budgets, leaders will need to determine the critical talent segments and decide where to selectively outcompete.     4th Scenario:  “I don’t want to live in a house anymore, I want to live on a boat” In this scenario, employees may have completely new lifestyle aspirations. The pandemic has caused many to question the purpose of work. Some may want to take the time off to reconsider their career path. Some are keen to pursue academic interests. And others are leaving the workforce entirely. This scenario is mostly outside of your control and ability to influence as an employer. In this situation, your efforts are better spent on recruiting and backfilling these positions instead of trying to convince your employees to stay. FS leaders should invest in creating a pipeline of talent to backfill these roles quickly.  Conclusion There’s no silver bullet to solving the attrition challenge and this will likely endure for the medium to long term in the industry. In order to adopt a more effective approach to address this issue, leaders will need to ask “why” employees leave. This will dictate the next steps critical to retaining talent.  To learn how other best-in-class organisations retain critical talent, here are a few recommended resources.  A Framework for Assessing Attrition Risk: who wants to Pack up, and Why?  4 Bold Strategies to Disrupt Compensation Competition in the New Talent Landscape  How Financial Services Leaders are Winning on ESG Goals  Blogposts: 5 Critical competencies for the Future of Financial Services How to Build an Engaging Virtual Onboarding Program for Today's Talent Market  Creating a Diverse Workforce in FS starts with Entry Level Hiring  Why the "Struggle for Talent" is a Red Herring  How to Make Hybrid Work Successful in Financial Services. 

  • Digital Retooling > Turbulence and Recession
    by Mark P. McDonald on June 8, 2022 at 6:00 am

    When the current economic and political turbulence turns into a formal recession is anyone’s guess. Enterprise IT spending will remain relatively strong. Enterprises will continue to invest in digital technologies despite a recession Turbulent times are turning toward global recession which increases uncertainty. Normally enterprises would pull back on spending. However, enterprises can be expected to continue IT investments in digital technologies. Gartner and others expect enterprise spending on IT to remain strong.  The logic of continued  spending relates to the following: Enterprises need to retool and put themselves on a digital footing. Enterprises started that retooling during the pandemic and need to complete it. Being half digital is the worst option. It creates a mutation not a hybrid – that is costly, rigid, and ineffective. Spending on digital technologies give leaders better tools to manage in a downturn. Cloud-based solutions increase IT cost elasticity and scalability. This is a plus in the face of variable demand. Digital enabled channels support deeper customer relationships and engagement. The deeper the engagement, the more likely customers are to remain loyal. These channels offer deeper interaction to extend the value of the relationship. Insight, generated by analytics and AI, give the organization a clearer picture of actual demand, operations, costs, quality etc. The more you know the better you can navigate turbulent times, particularly the unique turbulence we current face. The Dilemma Facing Buyers Spending now in the face of a near term recession presents a dilemma for IT buyers, primarily the CIO and Procurement. They need the benefits of digital retooling, but they want the flexibility to manage that spend in case of a severe downturn.  Remember being half-digital is worse than not being digital at all. Business leaders are compressing digital transformation schedules, knowing that the only thing certain is now and the longer they wait the more exposed they are to uncertainty.  This is a factor driving accelerated IT spending, particularly for IT Services. Acceleration comes at a premium in terms of costs and operational disruption. We can expect more traditional IT buyers to want to accelerate as well, but without the cost or disruption. More on that in the next post. Related Posts Turbulent Times Turning Toward Global Recession ? Technology’s Evolving Covenant with Business  

  • Connected Keynotes - Announcing Tricia Wang as the GartnerTGI Guest Keynote
    by Hank Barnes on June 7, 2022 at 10:00 am

    I was super excited last week to announce during a LinkedIn Live session that Tricia Wang will be our guest keynote on day two of the Gartner Tech Growth and Innovation Conference this July. I have long admired her work--check out this TEDtalk for a taste of her POV and her web site where the headline on the speaking page just makes me smile, "Not everything valuable is measurable." [caption id="attachment_3097" align="aligncenter" width="635"] Source: triciawang.com[/caption]   We spent a lot of time choosing a speaker, primarily because we didn't want to just have a great speaker (they are relatively easy to find).  We wanted a great speaker whose message would connect with the conference theme, "Tech Growth Requires a Relentless Customer-Centric Approach."   And Tricia fits that bill perfectly.  Her message to look beyond quantitative data for insights in "thick data" (aka qualitative data) is critical for everyone to understand, particularly as AI continues to take hold.   Data provides clues, but also may lead us down the wrong path. Insights that combine a variety of data is much more powerful. One example that comes to mind for me, of my own making, is the answer to the question "Who is your most valuable customer?"  Most go right to the customer that generates the most revenue.  It is the easy answer--but is it the right answer?   What if that customer  requires an inordinate amount of resources to support?  What if they expect customizations that really don't provide any value to others in the market?  What if the complain vocally about you, even as they stick with you? Contrast that with a customer that generates less revenue, but is a visible and vocal advocate--helping your sales and marketing drive interest and win business.   What if that customer is an active member of the customer advisory board, but doesn't do it for themselves, but to help make the product better for the market? I know which one is more valuable to me.   And that is what enhancing your approach to the search for insights can do. But back to Tricia.  It gets even more interesting.   Whenever you hire a guest keynote, there are always discussions about tailoring the content for the specific conference audience.  No surprise there.  Every great speaker has a mix of examples and stories that they can fluidly assemble together in a compelling narrative. But have you ever seen a guest keynote create a keynote that connects to an internal keynote?   I've never seen it, but I'll admit I'm not a big conference goer.   Well, that is what is happening with TGI.   As we were tell Tricia about our conference and the story we will be telling in the opening keynote about regret and paradoxes, her eyes were lighting up.   There is a natural connection between  our stories that we will be delivering.    If you think about my work with psychographics, the connection is clear.  We determine the profiles with quantitative data, but the spirit of the questions (and many of the other questions in our study) are qualitative.   Going further with ethnography, effective listening, and broadening your mindset about data and information will unlock even more value potential. The more you can get comfortable with squishy ideas, the more prepared you will be to deal with the vagaries of customer behavior.  The more open you are to learning from customer interactions--and empowering those closest to the customer to collect and share those insights--the more truly customer centric you will become. Open your morning and open your mind on day 2 of the conference.  You'll be glad you did. There are lots of great reasons to attend #GartnerTGI.  You just got another one.  

  • Doing Better in the Healthcare Supply Chain Top 25 by Adding an ESG Metric
    by Eric O'Daffer on June 7, 2022 at 9:00 am

    Maya Angelou famously said, “Do the best you can until you know better. Then when you know better, do better.” Her quote applies to a lot of things, but for purposes of this blog it applies to the healthcare supply chain and a change we are making in Gartner’s Healthcare Supply Chain Top 25 to “do better.” We are adding an environmental, social and governance (ESG) quantitative metric to the ranking for the first time. The goal of this blog is to share the details of the change, and what you can do to align and give feedback to help shape our next steps. As a refresher, last year we made the biggest change in the history of the Healthcare Supply Chain Top 25 by moving to an all-U.S. healthcare provider ranking. Previously, we had also included manufacturers, distributors and retail pharmacies. This move reflected the growing supply chain maturity and scale of health systems, along with improved performance of life sciences manufacturers in Gartner’s global ranking across all industries. In making this change, we signaled that we would seek to add an ESG metric to the quantitative portion of our ranking. How do ESG Metrics Improve Our Ranking? Our healthcare ranking is a compilation of quantitative metrics and qualitative peer and analyst opinions. The new ESG metric will be weighted at 5% of the valuation for each health system, and will be based upon membership participation and active engagement in the not-for-profit organization Healthcare Anchor Network (HAN). Founded in 2017, HAN is a national leader in promoting healthcare supply chain strategies that uplift local, diverse and employee-owned businesses and that encourage prime suppliers to create better quality jobs in high-need communities, creating a natural alignment with a need to account for ESG practices in our ranking methodology. HAN has partnered with a leading national nonprofit focused on environmental sustainability, Practice Greenhealth, to produce an Impact Purchasing Commitment, a leadership pledge in which HAN members commit to aligning their purchasing power to buy from, and build capacity of, vendors that are minority- and women-owned, sustainable, employee-owned and local. We recognize the critical importance of ESG practices in supply chain and are proud to partner with HAN to improve our ranking system with this ESG metric. Historically, ESG has taken a backseat to cost savings. Measuring and incorporating ESG practices into supply chain poses challenges. There are tradeoffs and costs to incorporating ESG best practices just like there are tradeoffs and costs to resiliency. We know many health systems are working hard on DEI spend and sustainability. Leaders like Kaiser Permanente were recognized in Gartner’s Power of the Profession Supply Chain Awards in 2022 for their commitment in these spaces. While your CEO is (or should be) focused on these strategies, certain systems may need time to adapt to these changes. Therefore, the ESG metric will initially be weighted at 5%, with an intention to increase this weight to 15% or more over the next few years. Many health systems represent the largest employers in a geography and could be better aligned to ESG. We hope these methodology changes to our ranking will encourage further resources and investment in these areas. The new makeup of the Healthcare Supply Chain Top 25 ranking components is detailed below. We are taking 2.5% from the peer and analyst opinion section and creating room for 5% allocation to the increasing commitment to HAN. Every health system can participate equally in this portion of the ranking — it is participation-based, and every health system has the chance to earn this 5%. Below are the details on HAN levels and scoring to earn 5%. We want to keep this simple with the three tiers of participation as highlighted in Figure 2 and outlined below: Are you a member of HAN (like 72 other health systems are)? Did you submit third-party Tier 1 supplier diversity data for procurement and construction to HAN as part of its annual data collection? Is your health system a signatory of the Impact Purchasing Commitment, meaning you will double your DEI spend in the next five years, achieve at least four sustainability goals and commit to five-year goals for community wealth building? Every health system in the United States can access points associated with this new metric, even in this first year. In September, HAN will be notifying us of which members have met the agreed-upon criteria this year for our ranking, which will be unveiled on Nov. 9, 2022. Please join us in “doing better” by uplifting the critical importance of ESG in our healthcare supply chains. We are excited about this first step on the journey and look forward to collaborating with all of you on the next steps for the 2022 Healthcare Supply Chain Top 25 ranking. If you have questions on our Healthcare Supply Chain Top 25 methodology and/or would like to be a peer voter this year, please contact me directly at eric.odaffer@gartner.com. Eric O’Daffer VP Analyst Gartner Supply Chain eric.odaffer@gartner.com   Listen and subscribe to the Gartner Supply Chain Podcast on Gartner.com, Apple Podcasts, Spotify and Google Podcasts

  • Human's At Risk - Webinar June 8th
    by Barika Pace on June 7, 2022 at 3:25 am

    Why Discuss Humans at Risk? As the connection between the cyber and physical worlds grows more intertwined, the risk to humans and our environment falls into the laps of tech companies. Technology service providers are confronted with questions about sustainability, safety and even navigating geopolitical disruption. Tomorrow, I will be pleased to host a lively panel discussion with three Gartner experts. Discussion Panel This panel discussion with experts will tackle how technology is placing society at risk and address what product leaders must do to safeguard people and the environment. Join Aapo Markkanen, Forest Conner and Wam Voster as we address your questions, such as the following: How do we build a message around technology for the good? Who in our organization is responsible for product safety and security? How do we address environmental, social and governance (ESG) concerns in our product strategy? What societal and geopolitical factors are at play? Join Us Come ready with your questions. I hope to see you tomorrow! Register Today  

  • DBMS Market Transformation 2021: OSDBMS Advances
    by Merv Adrian on June 6, 2022 at 12:33 pm

    A very frequent topic of inquiries to the Gartner DBMS teams can be stated simply as: "should I consider an open source DBMS (OSDBMS)?" Users have asked about open source in 3.6% of the team's inquiries over the past two years. Our usual answer is "yes, if it's commercially supported and meets your requirements after a POC that tests its ability to perform as required." Users are not the only source of this inquiry, though. Investors want to know if OSDBMS are viable commercially, and vendors considering new opportunities often want to think about using open source as the basis for a new offering. For different reasons, they have the same question: "is OSDBMS a commercially significant market I should be interested in?" Is OSDBMS a market juggernaut? Seemingly not. But there is a huge amount of "hidden" money here. Among vendors generating more than $35M in revenue in 2021, 13 primarily offer a commercial product based on an OSDBMS along with a community edition of it: Aerospike, Cloudera, CockroachDB, Couchbase, Databricks, Datastax, EDB, HPE, MariaDB, MongoDB, Neo4j, Pivotal Greenplum, and Redis. Collectively, those who offer this one DBMS represented at least $3.1B in 2021 - 3.9% of the $79.5B market. Over half of that revenue comes from two of the vendors: Cloudera and MongoDB. Neither can realistically be considered aggressive advocates for the open source, community version of their flagship DBMS offerings, but both do offer an open source version. MongoDB Community is the source-available and free to use edition of MongoDB. CDH is Cloudera’s 100% open source platform including Apache HBase (not all Cloudera revenue is attributable to the DBMSs, but Gartner lists it there.) HPE also supports HBase, but recommends its customers use the HPE Ezmeral Data Fabric Database with the Apache HBase APIs. Few other vendors offer products based on these two, though API support is more widespread. Another modest slice of market revenue comes from numerous other small vendors with their own versions of the Big4 favorite open source DBMSs: Cassandra, MySQL, Postgres and Redis, and others with another, less broadly known OSDBMS. We can consider them the pureplays. But there is much more revenue that is hard to quantify. The cloud service providers (CSPs) are DBMS market behemoths and offer their own versions of OSDBMSs. AWS markets RDS for MySQL and Postgres and Elasticache for Redis and Amazon Keyspaces (for Apache Cassandra). Google has Google Cloud SQL MySQL and Postgres, and Memorystore for Redis and Datastax's Astra (based on Cassandra). Microsoft offers Azure Database for MySQL and Postgres, AzureCache for Redis and Azure Managed Instance for Apache Cassandra. Oracle offers a Community Edition of MySQL, but does not disclose the revenue from its commercial version. Oracle has upped the ante with its high-performance Heatwave offering, now in its third release with built-in machine learning; it uses the MySQL API but is not open source. In the IBM portfolio, there is IBM Cloud Database for Datastax, MySQL, Postgres and Redis. IBM Cloud Pak for Data offers OSDBMS options as well. Like the Enterprise versions from commercial vendors, the CSP products often add some special sauce that extends the community version - in their case, it's cloud native features that leverage their storage engines, their control of the stack, and increasingly their ability to share governance and even semantics with their other offerings. And, as I discussed in my earlier post about nonrelational DBMS, for OSDBMS CSP revenue may well exceed all the independent players' revenues combined. CSP revenue for OSDBMS may well exceed all the independent players' revenues combined. Overall, the OSDBMS revenue story, muddy though it is, continues to be one of steady growth, appearing in more of the DBMS landscape every year. Open source is succeeding by itself and as a component of enhanced offerings. It influence and impact will continue to grow in the years ahead as more of the data management stack is disaggregated and slices continue to be replaced by open source offerings.

  • Turbulent Times Turning Toward Global Recession ?
    by Mark P. McDonald on June 6, 2022 at 8:45 am

    Executives are leading in a time of turbulence in its truest sense of the word.  Turbulence in terms of the uneasy or unsteady movement of economic and socio-political forces. Turbulence Factors Navigating turbulence requires acknowledging the multiple and often contradictory factors at play.  These include, in no particular order: Inflation at 40-year highs, initiated by supply chain disruptions, exacerbated by the invasion, and accelerated by recover from the pandemic Rising interest rates, coming off historic lows to curb inflation via traditional monetary policy, as well as the end of quantitative easing. Supply chain disruptions, driven by world events: the pandemic, Russia’s invasion of Ukraine, the realignment of global trade arrangements Food production and supply, as the Ukraine and Russia are major food exporters, this not only drives inflation, but it also increases political and economic instability, people who cannot feed themselves or their families take action. Tight labor markets, as companies look to hire in response to greater demand created by recover from the pandemic, particularly in the services and traditional ‘blue’ collar jobs. Strong U.S. Dollar, supported by a combination of the dollar as a haven in turbulent times as well as rising U.S. interest rates Lower stock market valuations, as rising interest rates and turbulence have shifted investment patterns and predict future economic conditions. Other factors, the shift to more renewable energy, social justice and equity issues, gun violence and rising crime – particularly in the U.S. all contribute to turbulence I am sure I am missing something, apologies.  There is no consistent theme, no clear direction, no easy fix – that is the definition of turbulence. The inability of simple solutions, like raising interest rates and other actions, will most likely turn turbulence into a recession. The stock market has been the best predictor of future recession.  On that basis it looks like we are headed for one, not only in the U.S. but more globally. When, how long, how deep is anyone’s guess. Navigating Turbulence If the past is any predictor of the future, we can expect to see the mood evolve from dire predictions of protracted downturns, toward the lionization of business and political leaders who ‘show the way’, and a turn toward highlighting positive news that are signs of a recovery. What will be the subject of that cycle? How should that cycle influence the actions leaders need to take today and next year? Who knows? Here are few thoughts, conjectures really, that are likely to be wrong in fact but less wrong in their sentiment.  I really welcome your comments and thoughts. The ongoing transition toward an information-based economy. Information and insight are the tools to navigate in turbulence and the basis for taking more powerful actions in a recovery. The information transformation is centered on customers and internal operations via digital technology. That focus will expand to include information created outside of the company changing the balance of power and policy in the future. Access Rules discusses these issues from one perspective. Customers will continue to rule. Businesses will not be able to put customers back in their place as consumers. Consumers buy what businesses sell as demand exceeds supply. Current supply chain issues and shortages are real and significant, but over the longer-term companies with the best customer value can be expected to win. Global trade will change from market-based to partner-based or friend-shoring relationships. It is easy to call form the end of globalization and repatriation of supply chains. Global trade as we knew it will evolve away from open markets toward more exclusive partner/supplier relationships to secure supply chains and stabilize prices and product availability. Resource realities, economic efficiencies, political and other factors support continued trade between nations. Sustainability will remain on the agenda. Sustainability issues transcend individual companies, countries, and societies. The impacts of environmental, social, and other issues are self-evident with significant human, social and political consequences. I might be pollyannish here, but these issues cannot be set aside in the face of near-term turbulence. There are no easy answers here which leads me to my last thought. Political instability will increase, at least over the next 2 – 5 years. This goes beyond political discord and culture wars. Hunger is instability as food insecurity increases due to climate change and Russia’s invasion of the Ukraine. National competition for resources will hopefully not lead to aggression, but it will create instability. Addressing sustainability will require changes in views of national sovereignty and collective action. Global, bi-polar, multi-polar, mono-polar, who knows, but it will be different. Honest dialog is needed There are no simple answers to the turbulence we face. Complex challenges do not resolve themselves in a single, simple answer. Dialogue, understanding, and action are major parts of any answer so: What do you think? How are you considering navigating the current turbulence and high probability of a global recession? What are your considerations for the future?

  • 3 Principles To Design A Tech Stack Sellers Actually Want To Use
    by Daniel Gottlieb on June 3, 2022 at 9:52 am

    Many of my clients want to know which sales technologies to buy. As sales leaders, they're curious about innovative ways to generate pipeline, run deals, and remove friction for sellers. Regardless of digital transformation, they're focused on finding tech to make sellers more efficient virtually, not automate them away.  For a sales leader, ROI from a new investment is a pipedream without adoption from the frontline. Sellers are not quick to adopt technology for the good of the borg. In Gartner's 2021 Seller Motivation Survey, a majority of sellers noted the introduction of new tech hinders their overall efficiency (see below). For these reasons, we advise clients to improve the probability of sales tech adoption at the concept phase, before deciding which vendors to go speak with. [caption id="attachment_10" align="aligncenter" width="724"] Source: Gartner[/caption] Sales leaders need a simple way to figure out which technologies sellers will actually use. My clients are busy and straightforward. The inquiries I get about tech for seller execution distill down to: Which technologies are available to improve seller execution virtually? Which technologies would you recommend as a fit for our sales teams? Answers to these questions must account for the seller's user experience, sales process, industry complexity, and technical integrations. Anecdotally many sales leaders I work with find getting nuanced answers from vendors can be time-consuming and frustrating. Vendors from over 55 categories flood sales leaders' inboxes daily. My clients tell me they're numb to "turn B players into A players” and "close more deal" messages. Sales Tech Mayhem adds to the confusion. A client recently in the middle of an active evaluation told me she'd consider spilling coffee on her keyboard to avoid sitting through another demo if she had to. She was kidding, I think. [caption id="attachment_24" align="alignnone" width="380"] Source: Getty Images[/caption] 3 Design Principles To Invest In Tech for Sellers  Below are three principles designed to help address the daily reality of sellers through tech. Sales leaders can use them to develop a point of view about what kind of tech their sellers might use to improve execution.  I recommend clients apply these principles to the three-to-five highest-impact anchor use cases in their sales process. The outcome of the exercise is often concept statements that they then use to evaluate vendors with hyper-specific outcomes in mind. 1) Improve buyer engagement.   Help sellers improve customer engagement. It's almost cliche. The point here is to explore innovative methods for facilitating live meetings, and asynchronous interactions with customers in between meetings. Question all assumptions about how the traditional sales meeting is run, and the role of content in between. One of my clients used this principle to develop an initiative focused on turning sales presentations into collaborative buying activities using Visual Collaboration Applications, resulting in a lift for discovery to proof-of-concept pipeline conversion rates across the pilot cohort.   2) Adapt tactics based on data. Equip sellers with what we call "situationally aware" insights. The key is for tech to help activate these insights in messaging, workflows, and tactics. Sellers tend to have the lowest data proficiency in the enterprise, so the tech can help them take the next action. A client used this principle to improve QBR acceptance from clients. The exercise led them to identify messaging triggers based on product usage, service delivery, and contract data. They ended up utilizing Scheduling Automation technology to trigger sending customized QBR calendar invites for eligible clients. This effort improved the volume of QBRs and pipeline contributions from upsells.  3) Simplify seller workflows. Improve day-to-day seller work by embedding technologies into sellers’ highly detailed daily flows. Sellers need to love using the product. A lack of seller digital dexterity undermines the successful adoption of tech. I recommend looking at an internal process like steps required to secure resources for a deal, then facilitate collaboration across a deal team. One client used this design principle to look for a better interface for a deal team to share notes and enter both activity and opportunity data into their CRM. They adopted Seller Workflow Automation to share notes in a Slack channel and then log those notes dynamically to CRM directly, saving over 3 hours per week per seller. Don't sleep on the value of removing internal friction for frontline sellers. Gartner clients can read the complete research here - subscription required. Gartner's Virtual Selling Tech Stack We visualized the tech stack for selling virtually based on the design principles outlined above. With concept statements, sales leaders are now equipped to go shopping. These technologies focus on seller execution, hence why more enablement and operationally focused categories aren't featured. The graphic incorporates data collected from 168 sales leaders on adoption levels and business outcomes across 27 categories of technology. Gartner clients can see the data, analyst recommendations, and versions of the stack (e.g. volume and velocity vs. enterprise deals) here - subscription required). Stay tuned for more updates on the landscape of Revenue Technology, and let me know what you think below in the comments.

  • CSO Superchargers: Internalize the Three Fundamentals
    by Christopher Gamble on June 3, 2022 at 8:34 am

    Prior to advising sales leaders with Gartner, I have had the privilege of working over 25 years in sales leadership roles across many organizations and industries.  And whether I was a new Sales Leader or in veteran CSO/CRO/CCO roles, I found that when Sellers internalize - that is, establish habits - these three fundamentals, they are more likely to experience success and achieve their goals. Knowledge - The "What/Why" are those things we learn about our company history, the reasons it exists and the mission to go to market with purpose. Skills - The "How" are the abilities we bring to a role and master through our experience. Desire - The "Want" comes from the emotional tug between pleasure-seeking and pain-avoidance (really the same, as avoiding pain makes us feel good). When Sellers internalize these fundamentals, it creates an intersection of the right Knowledge, right Skills, and the right Desire to form Habits. Why is the internalization of these fundamentals important? Allow me to use an example of "a guy I know" who accepted his first international Sales Leadership role.  In France, he was provided a corporate apartment in Paris, a company car (Note: manual transmission which he had never driven) and a reserved parking space at the Versailles office. He aspired to acclimate quickly to the culture and look confident to his new co-workers, so he laid out a plan to master his new daily commute by applying each fundamental: Knowledge: Learn French driving rules and the best routes to drive back/forth. Skills: Operate a stick shift and safely navigate both city and suburban roads. Desire: Attain a good work/life balance (pleasure-seeking) by minimizing his commute time (pain-avoidance). Now, between the apartment and office lay "L'Étoile" (the Star), the infamous roundabout at the Arc de Triomphe with its inverse right-of-way. Meaning, you enter the roundabout at full speed, then you must immediately yield to cars entering from TWELVE feeder lanes, all while masterfully braking, shifting, accelerating, and lane-changing during morning and evening rush hours.  What could possibly go wrong by neglecting to internalize even a single fundamental? Knowledge + Skill, but no Desire? He mastered the rules and his shifting, but he never quite articulated his dream of conquering L'Étoile and coasting into his parking spot, blaring "Thunderstruck".  Instead, he opted for a 90-minute train/bus/walking commute each way. Hello 14-hour day and his empty reserved parking space for all to see! Skill + Desire, but no Knowledge? He mastered the shifting skills required to speed through L'Étoile, and he relished blaring playing "Thunderstruck" as he slid into his parking spot. But all those failures to yield in L'Étoile? Hello 1500 euro fine along with the shame of the violation being mailed to the office! Desire + Knowledge, but no Skill? "Thunderstruck" was teed up for his big entrance, and he memorized L'Étoile's rules. Unfortunately, he stalled the company car 11 times in L'Étoile, finally rear-ending a vehicle in front of him. Yes, that is his Executive Assistant calling asking "why aren't you here yet?” So… much like my good friend learned the hard way, we all (sellers and leaders included) really need to master all three fundamentals to achieve our goals. If we miss internalizing any of these, the right habits will not form, and our goals will become unrealistic or unreachable. In a future Blog, we will talk about how internalization of these fundamentals connects directly to our responsibilities as Sales Leaders.

  • More on ‘Where You Invest Your Firms’ Capital Matters’
    by Andrew White on June 3, 2022 at 8:09 am

    I have been fixated on the study for how organizations allocate capital.  One of blogs in 2016 teed up some ideas I was working on at the time: Where You Spend Your Firms’ Capital Matters.  This was followed up in 2017 with More on How Firms Make Capital Decisions.  Most recently there was this: Yet More on Where You Spend Your Firms’ Capital Matters.  This might suggest to you that I have a passion. It is also a beautiful thing. I am exploring decision making (data and analytics) and economics both at the same time.  It can't get more delectable than that. My studies have continued and I just bumped into some new material I just had to share.  Here is an important quote from an old book: “…[I]nvestment decisions, as to their magnitude, and even more as to the concrete form they are likely to take, depend at each moment on the prevailing composition of the existing capital stock.”  The quote is from Capital and It’s Structure, by Ludwig M. Lachmann, published in 1956. How I alighted on this treasure is due to another book I am reading: Restarting the Future- How to fix the intangible economy, by Jonathan Haskel and Stian Westlake. As with so many books I read, I have to pause and read another that is referenced in the former. Its Your Choice and What You Do Next Capital and It’s Structure is a real gem despite its age.  Rebuilding after WWII was still happening. The Cold War was building. Central Banks were not that dominant. Winston Churchill was superseded by Anthony Eden as PM in the UK. Dwight D Eisenhower was President of the US.  And it seems that around this time new ideas were emerging that explore the theory, structure and composition of capital. The quote highlights something that has vexed me for several years. Surely what you decide to invest in as a CEO, CFO, or CIO, is impacted by what you previously invested in?  If you invest in, say, analytics and BI this year, isn't the success of that investment impacted by what you invested last year?  If last year you invested in a little data management, and some governance capabilities, perhaps your analytics investment that follows would be more impactful? What if you hadn’t so invested and instead invested in ERP?  Would that lessen the impact of the analytics investment that followed? What Does the Data Say? We have tried to unearth data to help explore this idea. Several years ago we ran a survey and we published some high level findings. See Sequence Your Data and Analytics Investments to Maximize Business Value.  I was a little disappointed in the effort.  The concept seemed innovative, but we were not able to find enough folks who could talk knowledgably about the range of investments we were looking at.  However the findings were at least directional. Yes, there is some data that infers a dependency for some investments.  There were examples that suggested investing in foundational practices did lead to higher  return on subsequent investments. A colleague of mine, Jitendra Subranyan, recently revisited the data set and worked out yet another cool question to ask of the data. We just published those findings. See Data and Analytics Benchmark Findings: How CDAOs Can Achieve Cost Recovery on D&A Investments.  We effectively took out the sequence angle in the data and instead analyzed each periods' investment as a discrete investments.  This new analysis exposed some intriguing implications for investment returns.  But many questions remain as to the impact of each investment over time. What is Capital and What You Do With It Matters It seems that some investment behaviors may impact the likelihood of a successful investment, defined as cost recovery. Such behaviors may depend on the degree to which an ROI of some kind is evaluated ahead of the investment. Others may include a firms risk appetite, which might lead to self-enforced success. Additionally smaller and more well defined investments may be more reliable in terms of likelihood of success.  But there are different kinds of capital.  So the mix, or the structure, makes a big different to success. All in all it seems that economic theory in this area is strong. The mix of capital should be taken into account when you plan the next D&A investment going forward. The particular mix could well influence the rate or even likelihood of a return or successful investment. Knowledge capital is critical, not just money or software or infrastructure. As Mr. Lachmann notes in his book, you don’t see railways being operated by staff using knowledge “from 125 years ago”. Why would we invest in new technology every year but not always upgrade our staff and their knowledge capital at every step of the way?  Or innovate with new business process or decision re-engineering capital?  In modern parlance, why would invest in new analytics, data science or AI technologies but also, always, upgrade our data literacy, management, organization and people skills? Studies continue.

  • There is No New Normal
    by Wade McDaniel on June 3, 2022 at 8:00 am

    Remember those days 12-18 months ago when we were saying that we’re headed into a new normal? In the thick of the pandemic, waiting for things to reach some sort of equilibrium? Well then what? War in Europe, two months of COVID lockdown in Shanghai, inflation run amok, food scarcity and fuel shortages. What does the next 12-18 months look like? It’s anybody’s guess. Many experts are saying that we live in unprecedented times. They say there is no way to predict the future as this series of events has not intersected in modern history. Recession seems to be on the horizon and central bankers are doing their best to avoid hard landings. Energy availability and pricing could swing wildly based on outcomes from the war in Ukraine. Agriculture is under threat due to snarls in fertilizer and grain exports. Climate events continue to disrupt at an unprecedented rate. The number of ransomware attacks have decreased recently, but it might just be that hackers are stretched thin due to the intense cyber war between Ukraine and Russia. Even with trillions of dollars of pandemic-related personal savings in place, it might not be enough to keep consumer spending on the move, which could result in an inventory hangover. Supply chain efforts in the past year have been focused on supply continuity and inflation. These issues are hugely significant, but we may have a case of "target fixation." We learned at the start of the pandemic that the companies that fared better had built their resiliency and agility strategies some years prior, and they simply accelerated the progress as the pandemic unfolded. Analyzing the complete landscape is more important than ever. This is not the time to hold back on strategies and tactics for building sustainable resilience in our supply networks. We can’t delay our efforts, which include making our supply chains more adaptable. Going Deeper On the Move Friend-shoring is how a podcast on the Wall Street Journal describes it. Is this reshoring, nearshoring, offshoring? Well yes, a bit of all, with security at the heart of it. When we asked our chief supply chain officer community about the state of their global locations, 75% said they are making moves. While these are typically smaller in terms of the overall network, it indicates networks are in continuous motion. The network is no longer a set piece to be reviewed every 18 months. When changes are planned, additional selection criteria are coming to the forefront. Leading the list are energy security, availability and pricing, political stability and climatic impacts. Elephant in the Room Is there an inventory bubble on the way? Many think so and it’s been a growing topic of conversation with our clients. Blank sailings at Shanghai have left plenty of goods on the beach waiting to move. Things will free up in the coming weeks and the bubble will start to clear out. Retailers have said the holiday season has already begun; this is months earlier than typical, implying an inventory increase. Should we continue to hold traditional inventory performance and targets at the heart of supply chain metrics, or should we be more pragmatic about how we look at them? Think about playing golf — you wouldn’t expect the same score in Scotland during stormy weather as you’d achieve in sunny Florida. Yet that doesn’t mean you can’t win. Leaders and investors might need to accept increased inventory as a normal byproduct of resiliency and adaptability. Environmental Controls The focus of many supply chain executives has been on greenhouse gas (GHG) reduction in recent years. They are right to do so, but we’ve come to a point where we need to recognize that our supply chains need to adapt to the climatic events that are occurring now. Consider the impact on the workforce where the ambient temperature is 32 degrees Celsius and the humidity between 80 and 90%. “Wet-bulb” conditions are a threat to human life, and they were reached on May 1, 2022, in Chennai, India. This is not the first time or location a wet-bulb event had occurred, and they are growing more frequent. Supply chains will need to adapt to these events through greater use of air-conditioning and energy, commuting practices, remote working and employee well-being programs. In some cases, we may need to rethink our sourcing and manufacturing location strategy. The time has come, the facts are facts. We’re faced with unprecedented changes in our supply networks and a new normal doesn’t seem to be emerging. Resilience was just a buzzword in 2019, but we all know what it means to us now. Over the decades we have been taught to search for the most refined and optimized solutions. But in the face of uncertainty, we need to build sustainable resilience that addresses the most likely scenarios, even though we don’t fully understand them. This may lead to suboptimized outcomes, but it might be the best we can do in the absence of normality. Wade L. McDaniel VP Distinguished Advisor Gartner Supply Chain Wade.Mcdaniel@gartner.com   Listen and subscribe to the Gartner Supply Chain Podcast on Gartner.com, Apple Podcasts, Spotify and Google Podcasts

  • Supplement Microsoft 365 with Best of Breed New Work Hub Services
    by jmariano on June 2, 2022 at 8:09 am

    In January I introduced the concept of the New Work Hub. It was defined as an assembly of differentiating team productivity applications created for employees with diverse needs. You can augment it with development, automation, artificial intelligence (AI), and analytics services. Most Gartner clients we speak with consider Microsoft 365 as the foundational new work hub service. The truth is there are a lot more services beyond Microsoft 365 out there.  Data from Gartner and others prove that IT leaders are willing to spend when needed. We also recently published 5 Digital Workplace Myths That Impede Workforce Digital Dexterity to help dispel this myth and provide guidance on how to move forward. As we were prepping this research for publications, two things happened. Gartner’s Governing, Managing, and Succeeding with Microsoft Office 365 Survey was being conducted Okta released its annual Business at Work report which provides data on what services its customers are using That data from the Gartner survey showed that 60% of participants are using some other collaborative services beyond Microsoft 365. This included services from across the new work hub, including Atlassian, Zoom, Miro, Slack, Mural, SmartSheet, and Google Workspace to name a few. Okta's report pulled from more than 14,000 of their global customers, and raised two key points with a huge impact on the evolution of the new work hub: For the first time since Okta started running the report, five collaboration services made this list as the fastest-growing apps. (Notion, Figma, Miro, Airtable, and monday.com) Among Okta customers deploying Microsoft 365, 45% are supplementing with best-of-breed services, including new work hub services such as Box, Google Workspace, Slack, Smartsheets, and Zoom. We primarily use Microsoft 365, but others certainly trickle in, depending on audiences, relationships, etc. Particpant Feedback From: Governing, Managing, and Succeeding with Microsoft Office 365 Survey To be clear in most cases these are NOT enterprise-wide implementations of these services, context is king. Being strategic with picking the right services for the right use case will be important. This could include frontline workers, healthcare professionals, marketing, and sales. To get to the context you must first determine which departments will get the most value from supplemental services (usually those tied to driving the business goals) and identify the gaps that Microsoft 365 has that may impede reaching those goals. Recommended Reading: Market Guide for Collaborative Work Management Market Guide for Visual Collaboration Applications Market Guide for Workstream Collaboration Magic Quadrant for Meeting Solutions Magic Quadrant for Content Services Platforms  

  • When it Comes to Ads, "Relevance" Means What Exactly?
    by Kate Muhl on June 1, 2022 at 2:43 am

    It is a marketing truth universally acknowledged, that relevance is the key that unlocks consumers’ gates. Make sure a message is relevant and consumers will allow it through their filters – the literal ones (ad blockers) and the figurative ones (they’ll actually pay attention to it). How do we know this? Because we ask consumers questions like, do you prefer ads that are relevant to you? Or, when an ad is not relevant to you do you find it annoying? And – surprise! – consumers tend to say they prefer the relevant ones. Another truth, perhaps less universally acknowledged: Sometimes a fact is just too good to check. Like, for instance, what exactly marketers and consumers mean by relevance. Consumers and Marketers Do Not Gave a Shared Definition of Relevance All too often, we marketers assume that consumers have the same definition of “relevance” that we have. A relevant ad, according to lots of marketers, is an ad that’s personalized for the viewer. And that personalization is based largely on the demographic or location-specific data points we tend have on them. Verifying that definition is only going to slow us down. So we don’t always bother defining our terms in the surveys where we ask consumers what kinds of ads they prefer. But here’s the rub: Assuming consumers share marketers’ definition of “relevant” can leads to bad decisions and missed opportunities. Because, it turns out, consumers don’t share our definition of relevant. In fact, in recently published Gartner research, “Maximize Ad Relevance by Responding to 4 Drivers of Consumer Attention,”[subscription required] we uncovered not only that consumers don’t define relevant in the way we do. They also have a range of different ways they define it. There are Four Key Consumer Definitions of Relevance In general, consumer definitions of relevance when it comes to ads are much more personal, idiosyncratic and emotional. They see an ad as relevant when it provides new-to-them information on products and services. Or, ads are relevant when they have emotional appeal, evoking feelings and featuring music or imagery that they like. A relevant ad, according to our consumer research, can also be one that helps the consumer understand an issue or people who are different from them. Find more detail on each of these definitions or drivers in the research linked to above. The connective tissue throughout these definitions of relevance? Relevant ads connect to something personally and emotionally specific to the individual viewer. Data points marketers gather through tracking aren't great at surfacing this kind of relevance.  There is still a role for targeted advertising. A portion of consumers do consider an ad relevant when it seems to be based on their internet searches or past purchases. The thing is, Apple and Google are reducing access to third-party cookies and device IDs. So data required to build this kind of relevance is increasingly difficult and expensive to acquire. To Make Ads More Relevant, Go Old School Faced with this definitional disconnect, what’s a modern digital marketer to do? Borrow a little from the old school marketing playbook! Leverage more population-level insights by digging in to the core values, experiences and interests of your target consumers as a group, rather than the specific user/ad viewer. It may seem counterintuitive, but leaning into more universal truths just may be the most efficient and modern way to get to specific relevance in ads.