The Incidental Science of Organizational Growth via Digital Transformation

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Simply boosting top line metrics such as profitability isn't enough to make digital transformation as a successful. Pervasive access to data and insights is critical as consumer demands shift alongside technological advancements. We explore the mechanisms for knowledge dissemination that address the rapid evolution of today's world and identify ways to push organizations up the S Curve of Growth through digital transformation.

Buckley Barlow
Founder/Executive Chairman | RocketSource

&

Cassidy Hilton
VP Data Science & Analytics

Post Summary

1. The Foundation of Organizational Growth Happens Along the S Curve of Business
   Growth ebbs and flows, flinging organizations into strategic inflection points. It's in these moments that having a framework is critical.

2. Cost Reduction Cannot Drive Digital Transformation
   Opportunities are lost when an organization focuses on digital transformation as a means of reducing costs.

3. Pervasive Insights Are Critical
   Through pervasive insights disseminated across the organization, the people, processes, and platforms can work together in harmony to succeed at digital transformation.

4. The Concepts of Ba and Bioholonics
   Places and types of knowledge, as well as how they're shared, all come together to empower organizations to work in harmony toward a common goal.

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There are necessary steps an organization must take to derive maximum value and growth via digital transformation initiatives and stay relevant in an increasingly innovative world. However, to extract meaningful value from digital infrastructure an organization must approach incremental growth by way of optimization and innovation across the business. A lack of pervasive information causes enterprises to get stuck and the transformative power of digital to stagnate.

The concept of communicating initiatives well as a means of gaining organizational buy-in isn’t new. Companies regularly tap into many types of knowledge, including organizational know-how, specific skill sets, expertise, familiarity with the market or industry, and insights born out of data and analytics. What is new, and still less clear, is how to implement mechanisms to disseminate all of this knowledge — especially insights, data, analytical modules, target (variable) definitions, meta-data, and micro- and macro-level combinatorial systems — across the company to drive growth through digital transformation.

The organizations that democratize tangible and intangible innovative capabilities and tendencies throughout the incremental outcroppings of the business will navigate those “butt-puckering” inflection points with a high level of confidence. In turn, using this approach will allow for increased peaks of growth and sustainable relevance in their respective markets. Here’s why this matters and how it’s done effectively.

The Foundation of Organizational Growth Along the S Curve of Business

As in the stock market, cyclical growth within organizations is predictable. Every company, regardless of industry, size or business model, will incur periods of upward trajectory. Just as predictably, these same companies will also experience tapering growth. This cycle of predictable trends is often referred to as the S Curve of Business.

We’ve already gone into detail about the S Curve of Business (also commonly referred to as the S Curve of Growth) in a previous post, but if you’re new to the concept here’s a quick primer. In the business sense, the S Curve enables organizations to predict and react to complicated influences such as new trends and industry disruptors.

As an organization moves along the S Curve of Business, growth will periodically ebb and flow. In these ebbing stages, businesses are flung into a strategic inflection point where the organization must undergo transformation initiatives to regain or maintain forward momentum. It’s here that businesses fight the battle to stay relevant.Navigating these blips might seem simple enough on the surface, but  they’re difficult to master in practice — especially because organizations don’t always recognize when they’re in the midst of one. The key to successful navigation along the S Curve is the alignment of the organization’s mission and vision with the emotional and cognitive associations of the modern consumer. This approach requires empathy, which isn’t always as easy to come by as it might seem. The University of Pennsylvania and Harvard Business Review determined that 91% of business leaders believe it is very important to make compassion a habit. Of those leaders, 80% said they wished to increase their ability to show compassion and empathy but weren’t sure how. This is a common problem when navigating strategic inflection points — one we solve with our proprietary business transformation framework, StoryVesting.

We’re firm believers that the framework you choose to navigate the murky waters of business transformation must be easy to understand and remember, and yet deep and detailed enough to capture the essential nuances and complexities of daily life. StoryVesting has served as a guide for dozens of Fortune 500 organizations to lay the foundation for success along the S Curve of Business because it empowers organizations to be agile and empathetic while building a vested workforce.

Every business should begin with this foundational landscape before building innovative products and digital solutions. The key to laying this foundation lies in the 3 Ps of StoryVesting — people, processes and platforms.

People: Personnel Enablement Transformation in Action

It’s no secret that personnel are one of the biggest assets of organizations today. It’s the people within the organization who are conduits of innovation and transformation.

It’s not enough simply to hire top talent. Ivy league diplomas are certainly admirable, but our research determined that passion and dedication are ultimately the most valuable employee traits.

40% of successful business leaders believe the key to organizational success is having a vested workforce. – RocketSource

That vesting is especially important when it comes to an endeavor as complex as digital transformation. Organizations embarking on digital initiatives without having a firm understanding of the end goal and its correlated impact on the business and its consumers, and without knowing the required steps, skillsets and other tangential factors, will falter. As evidence, take a look at what McKinsey found to be the future of the workforce based on the perceived importance of various present and future skillsets.

As you can see here, basic data input, which can come from less vested employees, is currently valuable but is quickly becoming less relevant. On the rise, but still considered of low importance, are complex information processing and advanced data analysis, both of which require employees to have a vested interest in the mission to draw out necessary insights that will fuel growth. This skewed perception of importance will soon shift as more companies understand and embrace the impact of digital transformation.

Accenture found that companies which understand the potential impact of digital transformation earn 26% more profit than others. The same holds true for organizations that embrace the idea that entire jobs, not just skillsets, are being replaced (and some obliterated) by technology. For example, deepkapha.ai focuses on breakthrough artificial intelligence (AI) that would knit the worlds of neuroscience, models and frameworks around deep learning for the future. Tarry Singh and his team build AI solutions for corporate customers and train engineering teams to holistically build AI solutions with hands-on, market-relevant advanced AI projects. Focusing on training, skilling up for the new AI economy skilling up for the new AI economy and a deep-rooted dedication to forward thinking is allowing organizations to surge ahead in an increasingly competitive market landscape.

When determining the top digital trends of 2018, eMarketer found that 45% of top-performing companies invest significantly in digital skills & education. The cumulative expansion of employees’ hard and soft skills is a prerequisite of transformation and is a solid foundation upon which StoryVesting is built.

The continued development of employees over time creates an atmosphere of empowerment that is crucial to the individualized, innovative tendencies of employees to consistently push the envelope and prioritize leveling up. Research shows that employees value growth opportunities, which is why smart companies, like Amazon, pay their employees to learn. In doing so, personnel feel more valuable and more able to help fulfill the organization’s vision. This concept of personal and professional growth is the crux of the StoryVesting framework. When built on a solid understanding of the organization’s “why”— the core mission of the organization — personnel feel empowered to do what it takes to position the company to win in any imminent competitive landscape, even through recessions.

This system of empowerment is especially important considering that employees aren’t naive to the changing competitive landscape. It’s a deep understanding of the future business landscape, along with incoming threats to job security, that have sparked employees to want to contribute to future growth, which is expressed through increased employee engagement. Gallup recently found that employee engagement is rising, with a whopping 34% of U.S. workers feeling engaged in their jobs. That figure ties the highest engagement rate in Gallup’s history.

It is essential that organizations leverage engagement to allow for more innovative efforts across personnel of all levels. Unfortunately, these higher levels of involvement can quickly be squandered, leaving an employee’s passion to stagnate in the face of outdated business processes; frequent, lengthy, unproductive meetings; or task overwhelm, all of which can lead to employee burnout. Organizations that focus on the increased engagement rates rather than on reining in employees who want to innovate will be more equipped and empowered to lead the digital transformation charge. The disparity between the number of engaged and disengaged employees is a reason for concern for organizations that are not able to facilitate a vested workforce. Dropbox confirmed this notion when revealing their secret for saving time in meetings.

Dropbox declared “Armeetinggeddon” in 2013 after hearing employee outcry against the inefficiency of their seemingly infinite number of scheduled meetings. Overnight, leaders erased all recurring meetings from their teams’ calendars and for two weeks teams were instructed to collaborate only when necessary. During those two weeks the company learned which meetings were critical and which were not, thus helping to eliminate time wasted in conference rooms.

Overloaded calendars aren’t the only things that lead to a lack of productivity and satisfaction. Overloaded to do lists are another area where organizations can cut back to accelerate forward. A study by Shira Baror and Moshe Bar determined that humans think better when they think less. As people, we naturally default to innovative thinking when our minds are clear, meaning when we’re free from busy work and not overloaded. The tendency to overwork, or become overwhelmed by the noise of the digitally integrated workplace leads to the tendency for employees to be present but not mentally engaged in and effective at in their work.

Mental disengagement due to stress is detrimental across the board. Health Advocate determined this kind of stress in the workplace costs companies $150 billion per year. One way we’ve promoted a reduction in noise and inspired innovative thinking during critical stages of an organization’s journey is through a modified Hoshin exercise moderated during our LevelNext MasterClass on Modern Business Transformation. In action, the engaging and thought-provoking exercise looks something like this:

The premise of Hoshin to leverage a unique process in which silence is used to flesh out mission-critical ideas, democratize those ideas and then reach an agreement without speaking to one another. In doing this, organizations can quiet those people who tend to be the loudest voices in the room, such as employees with higher internal rank or those who are naturally more outspoken. By putting all employees on an equal playing field and giving everyone an equal voice, fresher ideas have room to emerge. This approach, paired with a methodical decision-making process, brings teams together through unified decision making. Everyone leaves the exercise motivated and confident in the objective, facilitating the requisite organizational buy-in that any transformation initiative needs to succeed. It’s through this strategic moderation process that teams can ideate, collaborate and prioritize key objectives, keeping everyone engaged and tracking toward a common goal.

There is another cure for this plague of less-effective, disengaged and dissatisfied employees. You might already know that a growth mindset is one of the three most crucial ingredients for a successful business. What you might not realize is that having a growth mindset has been proven to grow leaders who actively pursue more innovative projects. Microsoft does this regularly by holding hackathons, encouraging the undertaking of high-risk projects, and redefining their talent program. Each of these efforts pushes employees beyond their limits while simultaneously accelerating collaboration among teams. In turn, they’re able to build a more modern talent pool, creating what we call a V-Shaped team.

A V-Shaped team member is someone who specializes in one area but is still knowledgeable in other areas of the business. V-Shaped team members’ roles overlap with the roles of others, enabling them to speak the same language about critical tasks driving transformation initiatives.

For V-Shaped teams to exist, democratized knowledge-sharing must occur. Google’s training program is a perfect example of facilitating robust V-Shaped teams. In their program, known as the g2g training program (Googler-to-Googler), 80% of all tracked training is conducted through an employee-to-employee network. The program serves up first-hand knowledge and know-how from experts in different fields. That knowledge is then passed from employee to employee. In essence, the program relies on employees’ ability to share learned knowledge among their colleagues. In this format, people not only learn but also teach, which enables them to review and solidify their knowledge. This structure encourages an environment of knowledge democratization that suppresses the impulse to store critical information in silos. What’s not surprising (based on our experience) is that vesting throughout the organization as a result of “peer-to-peer” interactions continually pushes innovation forward.

The role of managers in establishing a healthy team culture for group employee learning is immense. With its g2g program, Google created a “willingness to share” atmosphere. They paired it with mechanisms to disseminate that knowledge, which required teams to learn how to speak the same language. A culture of knowledge sharing, leveling up and information dissemination allows for a healthy, vested workforce who are all rowing in unison towards a common goal.

The benefits of V-Shaped team members are evident when compared to T-Shaped team members.

T-Shaped employees are hyper-specialized in their area which makes it difficult to share knowledge between departments. This lack of insight shareability creates a distinct gap in discussions.

For example, consider a team discussing a data loop and putting together a python script. It might look something like this:

The idea of performing this type of data analysis as well as understanding the impact it could have would go over the head of a T-Shaped team member. However, across a V-Shaped team, a basic level user could perform, understand and disseminate the rudimentary data analysis performed in the above example. More importantly, a V-shaped employee would be able to understand the work that would go into the following big picture objectives:

1. To develop and curate this analysis
2. To harvest insights, identifying integrity deficiencies and expansion opportunities

This level of comprehension is critical for an organization to pass along knowledge and context and, ultimately for the innovative capacity of the team to be realized across the organization. A broad, deep and diverse informational ecosystem will ultimately dictate which organizations can cultivate and extract the most value or predictive power out of their data, disseminate relevant insights and eventually navigate rapid changing business environments.

Take data acquisition as a prime example. Without a holistic approach to the gathering process, organizations risk data leaving data in silos or collecting incomplete data sets. The risk of biased analysis is even higher because there’s less variety or diversity. The more diverse your data, the fuller the picture of analysis is and the more predictive power it possesses.

To illustrate the importance of data diversity, let’s use a theoretical case study. A finance department is performing data analysis on a given set of existing customers using only finance-specific information such as current balance, credit score and payment methods. The analysis and insights available from that dataset are very limited. However, if the same analysis was augmented by information specific to the services department — such as tenure, contract type or usage — the report would gain context. Further, adding sales and marketing information, such as sales cycle, initial deal size, campaign, source, channel and more would allow for a broader perspective.

Looking at this image, you can see the instant depth added when you take a holistic approach to acquiring data. Once you have collected diverse data sets, it’s imperative to make this information accessible via a democratized digital infrastructure. That accessibility is the result of properly aligning the processes and people so that the analyzed data can be more effectively corroborated, documented and utilized. For example, when insights are gleaned from and specific preparatory work done to a given set of data of features (fields), that information should be documented and shared to guide the next individual who is performing a separate analysis. By keeping data accessible across the organization in this fashion, you increase the economic value of available data and exponentially grow its impact on the organization.

The above scenario distinguishes industry leaders from the rest of the pack. When a holistic approach to data acquisition is paired with qualitative insights within the same analysis, the results are outstanding. For example, you can deepen your insights into a new online campaign by gauging the emotional reactions of consumers.

• Did the person watching enjoy the ad?
• What specific elements caught their attention?
• Did the ad impact their opinions or deepen the cognitive associations of your brand?
• Did any people within the ad, especially team members, jive with the audience?

The answers to these questions and this type of data provide an excellent baseline. Moreover, it’s not hard to collect through simple phone calls or strategically positioned surveys. When done correctly and managed into an automated set of collecting and mining mechanisms over time, your organization will gain more levers that can be pulled to turn that data into actionable insights. These extra levers can further be used to prescribe action in a machine learning or deep learning setting. For example, you might know X customer is 73% more likely to cancel during a specific quarter. By deepening your insights through qualitative data, you would be able to determine that reaching out to the customer and making an offer for a different contract type would significantly decrease the chances they’ll cancel.

These types of insights can have a dramatic impact on growth, emphasizing the point that organizations cannot achieve noteworthy levels of diverse information when working in silos. In this case, Gary David Goldberg hit the nail on the head when he said:

Maximum diversity in datasets is critical for achieving noteworthy predictability in the data and a broader perspective, context, and interdepartmental and inter-individual connectivity. So is the process taken to utilize and disseminate this information.

Process: Guided Growth

The second of the 3 Ps in StoryVesting is process. When it comes to improving organizational growth, you cannot target a single level or facet of an organization. Rather, you must continually evaluate and iterate multiple levels and subsystems within the organization, influencing behaviors and attitudes rather than focusing exclusively on group norms and interactions. Though McKinsey found that attracting and retaining the right talent is the first step to growth and digital transformation, the onboarding processes used with new team members is equally important.

How your business transforms and the rate of transformation is predicated on the methodologies you use. Highly capable workers cannot make as big of an impact in roles with low complexity as they can in roles with high complexity. The McKinsey study on the important relationship between highly complex jobs and rate of transformation illustrates this point.

Here you can see the productivity gap between low complexity jobs and very high complexity jobs. When a task is deemed low complexity, there’s only a 50% increase in productivity between mediocre performing employees and exceptional employees. In contrast, when doing a high complexity task, exceptional employees do 800% better. This approach to process complexity has far-reaching implications for how workforces are being used in industries. Based on this data and on the results of the studies mentioned above, organizations that bog down their top performers with low complexity busy work not only discourage employee engagement and innovative thinking but actively bleed away potential productivity and heightened efficiency. Processes need to be structured and used with the organization’s employees in mind, whether that means reducing meetings like Dropbox did or using employee talents to their fullest potential in high complexity roles.

One reason organizations may not manage high complexity tasks in their processes as well as they could is that they’re difficult to manage and lead. High complexity tasks require refined processes to accomplish effectively. As processes become complex and convoluted, transformation efforts fall flat. To properly manage the level of high complexity tasks required of any company in today’s business climate, you need to be able to create organized processes that offer high level overviews without sacrificing informing details. By mapping out the flow of a project and all of the departments working on it, you can achieve that level of organization while making your operations more efficient and chiseling away at silo walls. Here’s an example of what this looks like:

Visualizing complex processes in this digestible format empowers your team to operate on agile effectively and properly while moving in harmony toward a common transformation goal. That structured agility is a key competitive differentiator. When it comes to creating the organization of the future, 94% of executives say that agility is critical to an organization’s success but only 6% believe their organization is agile, according to a Deloitte study. There’s clearly room for process improvement through this period of digital disruption and in the face of navigating the new, tighter S Curve of Growth.

One way to improve processes is by viewing them through the lens of the customer’s emotional and cognitive triggers. When alignment exists between an organization and a customer, as is guided by the StoryVesting framework, there’s a natural, progressive undercurrent woven so tightly throughout the fabric of the organization that it drives the organization’s heartbeat. It’s this alignment that enables organizations to realize faster time-to-market with transformation initiatives, run more experiments and fix errors faster, pushing the organization upward on the S Curve of Business.

Platforms: Democratizing Product Innovation

Regardless of the talent pool you have on board and the processes you have in place, without the right platform to facilitate communication you could unintentionally stunt your transformation efforts. The way you deliver critical ideas, insights and information across the organization has a direct impact on your ability to keep each department oriented toward your North Star Metric. The formation and dissemination of insights require dynamic cooperation among groups.

Many companies are looking to leverage solutions around the Internet of Things as a means to improve dynamic cooperation, increase corporate agility and drive higher productivity. By 2021, IDC estimates that $530 billion will be spent on cloud technologies, with 90% figure going toward multi-cloud solutions. Despite this investment in modern, robust technology, organizations are challenged by unintentional neglect on the part of the team members using it. Because it’s difficult to separate data for each desired application, employees are forced to filter and manipulate data sets, an endeavor that many teams aren’t properly equipped to take on. Furthermore, teams tend to harvest the insights that are easier to grab instead of reaching in deeper to datasets for the kind of insights that will drive transformation. It’s for these and many other reasons that, instead of being shared across the organization, data and insights are kept close to the vest and only handed out on a perceived need-to-know basis. In a recent Forbes Technology Council article, Devo CEO Walter Scott had this to say about why data silos are bad for business:

In the article, Scott points to an example of a clothing company that stopped sending its $58 t-shirts in a protective bag in an effort to save money. Although it might’ve made sense from a cost reduction standpoint, Scott, as the consumer, felt that the bag was important to protect his clothes in the shipping process. Because the bag was such a valued aspect of his purchase experience, it’s elimination sparked him to start searching for a new shirt company. This breakdown in customer experience wouldn’t have happened if the organization as a whole had the qualitative data and deep insights to know what he valued as a customer. Consumer insights like this need to be pervasive across the entire organization, in every department making both large- and small-scale decisions. Unfortunately, insights like these continue to get stuck in silos that allow for flawed decision making, breakdowns in the customer experience, and inevitably increase churn.

Despite the fact that group chat platforms have become prolific in organizations today, a whopping 83% of leaders have encountered information silos in their organizations, according to a study by the American Management Association. Despite this greater-than-ever ability to share things widely and the distinct opportunity to solve for information sharing in the business world, chat platforms still fail to organize important data and convey it in a way that’s accessible to the organization at large without becoming overwhelming.

In addition, chats and other digital platforms in the workplace can create an atmosphere in which only a handful of people contribute data and insights. Look no further for evidence of this than the results of a Harvard Business Review study on the feeling of collaborative overload. Researchers found that in most cases, as many as 35% of value-added collaborations came from as few as 3% to 5% of employees. As that small percentage of effective collaborators come to be relied on more and more by their peers, they begin to feel disengaged and experience lower levels of employee satisfaction.

The more a person is perceived to have insights and information, the more team members want access to that person. This pervasive nature of unequal involvement discourages collaboration and knowledge democratization. The potential result is a benefit to those around the collaborator and influencer, but a failure to advance their own personal development, as well as a likely lack of recognition or reward. This constant demand for access, particularly on platforms can lead to an underlying problem of collaboration overload known as observer-mode.

When only a small percentage of people are contributing regularly, the majority of team members unintentionally sit back and neglect responses on internal communication tools or project management boards and fall into a pattern of observing. Because they’re rarely called upon for their insights, they don’t feel obligated to respond; this causes internal communications to stagnate and eventually leads to siloed efforts and misguided approaches.

The platforms your organization uses to facilitate communication across all departments must not only encourage equal engagement from all members, but should also be democratized by way of StoryVesting.

Employees must have an emotional vestment in seeing the organization succeed, and therefore must understand the importance of a cross-organization communication strategy to facilitate that success. This vestment requires strategic mechanisms of knowledge dissemination so that data does not get orphaned or trapped in silos. Having a strategic communication approach requires an ability to tap into insights derived from a variety of sources including both qualitative and quantitative data. Having these insights can accelerate your economic value while flattening marginal costs, ultimately leveling the playing field and paving new ways for disruptors to build upon approaches to traditional business.

Digital Transformation is Accelerating the Playing Field

It wasn’t long ago that the economic playing field was dominated by big business. For new market entrants, disrupting established global markets felt like a seemingly impossible feat, causing small and medium enterprises to surrender like David to the Goliath corporations.

Then the phenomena of the digitally driven world stormed the scene, changing the very ways in which fabric of how organizations reach and engage consumers. The entrance of these new technologies gave greater opportunity to small and medium-sized enterprises (SMEs) who are ready, willing and eager to play seriously in global markets.

This concept of large organizations dominating smaller ones is often outlined in college economics classes. If you took a basic economics class, you likely learned the theory that an organization needs to reach a minimum efficient scale of production before production costs would be covered and a sustainable can be achieved. Traditionally, that minimum efficient scale of production cost was more than new entrants could afford. In today’s digital world, however, production costs have dramatically decreased, accelerating the timeline for organizations to reach new customers and making it easier and faster for businesses to get off the ground. Creators now have direct access to a global consumer base via websites such as Etsy and Shopify. Software providers can use the cloud to efficiently create, deliver, iterate and update applications. Entire industries are being disrupted by innovative solutions that simplify delivery approaches. The finance industry is a prime example.

In 2011, Personal Capital set out to reshape how people invested money. The company launched a money management platform for consumers that blended technology with objective financial advice. This approach is different than either algorithmic or traditional advisors acting alone. By pairing a modern technological approach with human touch (blending human and algorithmic advisors) the company disrupted the financial industry and grew to over 1.5 million users.

The company continues on an upward trajectory, attracting clientele who are investing increasing amounts via their app. From 2017 to 2018, Personal Capital grew by over 20% with the amount of money per user managed by the app increasing from an average of $340,000 to over $400,000. 38% of their assets are in accounts with over $1 million, and those accounts aren’t leaving. Personal Capital has an annual retention rate of 95%, which is almost unheard of in any industry.

The digital phenomenon has altered consumer behavior, which has created new economic opportunities across the industry spectrum and has inspired the need for digital transformation. It’s the economics of digital transformation which Bill Schmarzo, CTO, IoT and Analytics of Hitachi Vantara, argues is the prime reason for making it the number one strategic business initiative.

The Schmarzo Economic Digital Asset Valuation Theorem

The traditional economic mentality has deemed data the new oil. Oil is notoriously expensive to find, extract and transport. It’s also hazardous to the environment and depletes slowly over time. In reality, none of these characteristics accurately apply to digital assets. Digital transformation trends lean more in the direction of a “data is the new sun” mentality. It’s readily available in an infinite number of uses, doesn’t deplete over time, and is cleaner to find, extract and transport.

Your success in digital transformation is predicated on you approaching it with a “data as the new sun” mentality.

This mentality is the basis of the “Schmarzo Economic Digital Asset Valuation Theorem.” In essence, this theorem deems that an organization’s digital assets possess a unique ability to synchronously decrease costs while increasing economic value via the intraoperative usage of digital assets. Here’s what it looks like:

Schmarzo’s Economic Digital Asset Valuation Theorem takes into account a digital asset’s unique ability to simultaneously drive down marginal costs (via digital economies of scale) while accelerating its economic value (via digital asset reusability). As economic values grow, so do profits.

With this theorem Schmarzo has, perhaps unintentionally, identified a common key driver of digital transformation — cost savings. While we believe that cost savings offers a strong case for these new initiatives, this benefit alone doesn’t paint the full picture regarding the importance of digital transformation and how to gauge its success. The concepts behind Schmarzo’s theorem are tactical and relevant in nature. There’s a lot more to be said about the nuances and complexities involved in actually bringing data together in a meaningful way. Let’s take a closer look at how to put these ideas into motion.

Why Cost Reductions Are a Popular Driver of Digital Transformation

70% of organizations are undergoing some form of digital transformation initiative, according to a Tech Pro study. A recent report from the Cloud Industry Forum (CIF) and Ensono determined that cost savings is a primary driver of these digital transformation initiatives. Often, digital transformation efforts are driven by the desire to fall in line with the economies of scale presented in Schmarzo’s Economic Digital Asset Valuation Theorem. There’s nothing inherently wrong with that reasoning. Reducing costs (be it digital or otherwise) is a clear advantage to undergoing any kind of business transformation. Yet when you examine the data more closely, you’ll notice that there’s something off about this approach. Many of the key performance indicators (KPIs) used to track digital transformation success do not align with the key objective of cost savings.

Of the 200 IT and business decision makers surveyed in the CIF and Ensono study, only 22% of respondents on the business side said they believed their organization had finalized their digital transformation initiatives. 10% of IT decision makers said the same. This clear disparity proves that these separate departments are tracking vastly different KPIs to determine whether the end goal of cost savings has been reached.

Further proof that departments aren’t working in unison toward the business outcome of cost savings can be seen by looking at how each department views the primary drivers of digital transformation. 72% of IT respondents quoted cost savings as the primary driver, while only 68% of business decision makers said the same. Despite the majority of respondents claiming cost savings as a key driver of digital transformation, only 53% of business decision makers use cost savings as a key metric of digital transformation success. Customer satisfaction (52%), profitability (49%) and customer retention (45%) were often tracked and cited as indicators of success.

The disparity in the metrics being tracked is evidence that digital transformation yields more benefits than cost reduction alone — organizations have identified those benefits as revenue growth, increased customer satisfaction and higher retention rates.

Too many companies get stuck in the mindset that cost remediation across the board is the end goal of digital transformation. In reality, we need to be thinking about creating a strategic plan to reevaluate the benefits beyond cost savings.

An Admonition to Cost Reduction as a Driver of Digital Transformation

While marginal costs of digital assets (especially data) can, and in theory will, flatten if used in a socialized, recursive fashion, we assert that costs shouldn’t be the sole driver of digital transformation. The potential shortfall of keeping cost savings as the ultimate end goal is that it causes organizations to get stuck in the initial stages of digital transformation strategy, even if they’re in the heart of any type of business transformation maturity along that journey.

Despite experts knowing better, cost savings continues to be the end goal of digital transformation.

The focus of digital transformation should be much greater and more holistic in nature, the ultimate goal being self-organization of the tangible collectives throughout the organization. Digital transformation efforts synced across the StoryVesting framework drive initiatives to a value-oriented goal. It’s through this direction that innovative tendencies are catalyzed, cost savings are achieved, and a broader success is realized.

This combinatory system of collectives drives automation and transformation through data looping and mapping. By turning feedback into insights in all areas of the business — people, processes, platforms, products, services and channels — organizations can directly tie those elements to the emotional and logical decisioning of the consumer. That’s what Data as a Service providers aim to accomplish, and what we deliver for our clients here at RocketSource.

In analyzing how modern consumer demands continue to shift, it’s clear why cost savings cannot be the sole driver of digital transformation. Buyers today want more for less and almost-immediate gratification — with technology at their disposal, they’re empowered to get what they desire, forcing businesses to continue to evolve alongside technology. This continual and consistent evolution has substantially increased competition.

To achieve an end goal of rapid evolution alongside technological advances and cost reduction, many organizations are moving toward self-service, digital tools and digital utilities, removing the human element as much as possible. When focusing on cost reduction, organizations often favor digitization, automation and other elements that impact the bottom line, which has the unintended result of disregarding the customer journey.

Although automation and artificial intelligence might seem like the way to go, there’s a limit to how disconnected consumers want organizations to become. That desire stems from how we, as consumers, now live in an “empathy economy” — a human-centric way of doing business that truly grasps and accommodates the needs of the consumer with the full intention of continually enhancing their lives. With the world becoming increasingly digital, consumers crave balance with humanity. Thus, the human elements of business transformation are more imperative now than ever.

Still, the rush to leverage AI, machine learning and deep learning as silver bullets for market competitiveness has actually resulted in a great divide between organizations and consumers because of ill-advised approaches, strategies, toolsets and expectations. Said plainly:

Few organizations are deploying AI or ML successfully, let alone as a means for increasing trustworthiness and interpersonal experiences with consumers.

By leveraging technological advancements in a way that improves and humanizes the customer experience, organizations can avoid creating an even larger rift between buyers and businesses. One example of this is offering personalized experiences with the appropriate mix of properly deployed artificial intelligence, machine learning and deep learning by way of sentiment mining and emotion detection. This personalization includes humanized elements like interactions via one-on-one conversations, live chats, conversational guidance and more.

Delivering excellent, empathetic and targeted customer interactions are a few of the most omniscient means for future-proofing the organization. The value of a customer-centric approach is much greater than one might think. Adobe’s 2018 digital trends research shows that organizations with a cohesive plan, long-term view and executive support for the future of their customers are more than twice as likely as their peers to significantly outperform their competitors (27% versus 13%).

We, as a people, crave human interaction — especially throughout the buying process.

At RocketSource, we’ve created products around this concept, such as our conversational guidance platform, Pulsemotiv. As an organization, we’re betting our own ability to put dinner on the table on the fact that, despite all the technology, data and artificial intelligence, there are still situations in which people want to interact with people. We also get the argument for plain and simple cost reduction. There isn’t an easier sell than an ROI pitch with a focus on savings. This ROI focus is true within organizations and across the board in vendors of automation technology and service providers. That’s because the savings feels like an end-all-be-all solution or a silver bullet for a quick win on the budget sheet.

Although it’s an overall easy way to gain organizational buy-in, the end result tends to cause more of a headache than aligning everything across the customer journey. Instead of value arriving in the form of cost savings, it arrives in the form of positive brand sentiment. When adding innovative value to a consumer, that perceived measure of trust, appreciation, importance, usefulness and other human values stays consistent over time, even as changes happen.

Automation, data looping and AI are more valuable benefits of digital transformation than cost savings because they allow businesses to remain focused on key elemental human behaviors. This, Harvard Business Review argues, is where digital growth depends more on business models than on technology. Take two iconic startups as evidence of this notion — Lyft and Airbnb. Each of these industry disruptors planted their roots less than a decade ago and are gearing up to file an IPO in 2019.

Lyft recently hit a major milestone with one billion completed trips. Airbnb saw similar growth, reaching 108 million rooms booked per night in less than a decade. The common denominator here wasn’t cost reduction. It was a business model that disrupted an entire industry by providing exceptional value to the end user.

Lyft tapped into consumer’s usage of smartphones to make it easier and faster to hail a ride. Airbnb leveraged the Internet’s connective power to span distances and connect those who wanted to open their homes to travelers with those who wanted a place to stay. Both organizations used the technique that is the crux of StoryVesting — aligning their why with the consumer’s needs — to deliver value in a way that was relevant, repeatable and scalable.

Mature companies are often intimidated by these so-called unicorns entering the market. Disruptors pose a direct competitive threat, and disruption isn’t limited to startups alone. Disruptors have the ability to deliver unparalleled value to the modern consumer by aligning their business model, 3 Ps, products and services, and the channels through which they reach their audience to create a sublime overarching experience. To do this requires a deep understanding of the emotional and cognitive triggers associated with the journey customers go through. Digital transformation takes work and the results are not achieved overnight, but you don’t have to uproot your organization to drive this type of shift in momentum.

Any Kind of Business and Digital Transformation Takes Time

43% of CIOs said that resistance to change was a top impediment of a successful digital strategy, according to a 2017 Harvey Nash/KPMG CIO survey. At RocketSource, we often hear the same from organizations who say they are too busy to undergo digital transformation or don’t have enough data for advanced technologies. Both reasons are clear signals that they’re resisting imminent and necessary change, which are giant red flags to us as high-level consultants.

The real challenge isn’t usually a lack of time or data, but rather the lack of a digital mindset. A Computer Weekly study on digital transformation found that 78% of organizations lack this mindset and are hindered by change management, limited organizational capabilities and a lack of executive commitment as a result. On the other hand, organizations that pursue transformation initiatives time and time again (and often fail time and time again) display a deep understanding of the importance of transformation initiatives across the entire company. These organizations have embraced a digital mindset and work strategically shoulder-to-shoulder with every department leader to ensure adoption across the board.

The results of a recent digital transformation readiness survey developed by Appian and conducted by DevOps.com demonstrate how many organizations are not quite ready for the work digital transformation requires.

• 82% of organizations feel understaffed and unable to hire the software engineers they need
• 72% don’t believe they can scale to keep up with business demands
• 20% have over 50 major development requests in their backlog

Organizations that are too busy and understaffed for digital transformation are faced with a much greater problem — one that stems from within the culture and DNA of the business model itself. The organizations that say they’re too busy are most often the ones that need transformation the most, but that also struggle the most because transformation isn’t built into their culture or foundation. The absence of this core focus makes these organizations likely to suffer the most from failure to transform.

To customers, a lack of a transformational culture often results in a perceived lack of interest in creating a value proposition in the buying journey. When a brand falls out of favor with the market after failing to transform, it’s not a good sign for anyone involved. This struggle often leads to total failure. Sears is a prime example.

Kenmore, Sears’ line of appliances, has seen a slow and steady decline with the emergence of the digital world. At one time they enjoyed a healthy 40% of the market, but had declined to only 16% market share by 2016. It wasn’t until July of 2017 that Sears decided to embrace the digital phenomenon by partnering with a purely online retailer — Amazon. Sears made their reputable and recognizable Kenmore appliances available via the online retail giant, which sent their shares soaring up 22% almost instantly in pre-market trading.

At the same time, to reduce costs Sears began shuttering brick-and-mortar locations and leaning into digital transformation. Although this approach seemed like a positive signal of a larger shift away from traditional retail sales, the move was too little too late. As seen in the chart above, the blip in stock price, and the accompanying optimism, didn’t last long. In January, Sears reached a deal with Chairman Eddie Lampert to save the company from liquidation.

Sears, like other market leaders, was thrust into the world of digital transformation, forcing the organization to enter a newborn market. Also like other companies, Sears had put off digital transformation, likely because of fear, doubt and uncertainty of how much it was needed. They eventually attempted to enter the game with a reactive approach by partnering with a digital giant, Amazon, but their efforts weren’t strong enough to catch them up after years of falling behind. Had the company prioritized its business objectives by aligning its goals with the customer’s journey via the StoryVesting framework, they may have implemented strategic measures sooner. It was the lack of insights and being disconnected from the customer’s journey that steered the organization to a poor outcome.

Returning to Schmarzo’s Economic Value Asset Theorem, we can see that cost reduction is a distinct value add. However, as can be seen from Sears’ struggles, cost reduction by way of digital transformation is not a strong strategic move. It’s the pervasive insights via data and analytics that equip organizations to predict future trends and build robust value-based strategies to survive and thrive.

Pervasive Insights are the New Economies of Scale

Business insights most often stem from the organization’s mission and honor the business model. However, to be effective these insights must eventually be disseminated across the 3 Ps in a strategic and purposeful manner. This dissemination requires a lot of moving parts, which is where having a guardrail in the form of a business transformation framework, such as StoryVesting, is so critical. It’s the pervasiveness of these insights, by way of economies of scale, that will really change the entire data and analytics industry.

To reach that level of pervasive insight, many organizations take the stance of being “data-driven.” As popular as this concept has become, organizations have become befuddled by this buzzword, which is intended to define the approach of leveraging data and analytics. In today’s world, to run an intelligent operation you shouldn’t focus on being data-driven but rather on being insights-centric.

Data-driven, data-centric and insights-centric are three terms that are often used interchangeably but there’s actually a big difference between them.

• Data-driven involves letting data drive the decision making. What the data says goes, no questions asked. There’s less human thought and reasoning involved, which can lead to a host of problems. When data is considered absolute it can inform the wrong thing, lead to flawed conclusions and turn a business sideways, effectively increasing risk rather than mitigating it.
• Data-centric organizations assess and temper their user data, leveraging it only to inform and validate rather than to drive decision making. Data becomes a pillar to build on, which isn’t a bad approach, but it’s still one step short of the ideal usage of data within a business.
• Insights-centric organizations process, study, test, humanize and analyze data with logical reasoning to extract insights. By leveraging statistical models and analyses to understand what’s happening in the market, companies are better equipped to predict upcoming trends and stay ahead of the curve. If you’re insights-centric, data is your map and compass — it gives you the information you need, but you’re interpreting it and making the critical decisions. It’s much harder than letting the data steer for you but also much more effective, allowing you to validate decisions, and find out-of-the-box solutions that have the potential to disrupt entire industries.

Bringing it back to the StoryVesting business transformation framework, taking an insights-centric approach is critical as you aim to tell a story with data that’s understandable and actionable across the entire organization. You’re able to prioritize decision making based on real-time feedback loops, enabling your company to stay relevant and connected to the market while giving consumers more equity in your transformation efforts. This is how you align your organization’s why with your customer’s why and build brand euphoria.

In order to achieve pervasive insights, organizations must have a democratized, combinatory system of digital collectives across the organization for knowledge dissemination in place.

Ultimately, the holistic innovative power of an organization grows exponentially with full-scale innovative capabilities. In order to achieve pervasive insights, you must have a democratized digital infrastructure and mechanisms for knowledge dissemination in place.

Mechanisms for Knowledge Dissemination

A lot has been said and done in the data and analytics space regarding democratization of information and dissemination of insights. Although we’ve made tremendous strides in making data accessible, there’s still room for growth. To deepen these tactics and dig into all that’s available, we approach these mechanisms for knowledge dissemination a little bit differently than most. Our goal is to help companies hit the accelerator by making insights easily understood and conveyed.

Economic Value Accelerates When Digital Transformation Can Be Easily Understood and Conveyed

Schmarzo’s model was a refreshing new approach to the idea of reusing data and analytical models to facilitate growth by way of flattened costs. We argue that we can continue to leverage data and analytical models that already exist and reuse them in subsequent use cases but, first and foremost, we must have a mechanism for knowledge dissemination. The knowledge we’re disseminating can range from quantitative data in a much different, better, more robust world or insights derived from qualitative data.

But here’s the deal. Getting all departments across an entire organization to support an entire scope of data science is one of the most complex functions any business leader faces today. It requires the convergence of tech, data, visualization beyond spreadsheets, creative, content, customer experience, user experience, human resources and more. Still, Harvard Business Review determined that every organizational function needs to work on digital transformation. Over 66% of CEOs now expect their companies to change their business models, and 62% say they already have management transformation programs underway to gear their organizations toward becoming more digital. Further, a whopping 87% of organizations say that digitalization is do-or-die.

Despite the fact that digital is such a critical next step, many organizations approach it with too much gusto, sending them into a downward spiral instead of progressing upward on the S Curve of Growth. General Electric (GE) is a prime example. GE took an all-in approach to embracing the digital wave. After pouring billions of dollars on advertising to stake their claim as “a digital-industrial company” and hiring thousands of software engineers in 2015, the organization faltered in their own efforts.

In June 2017 the organization replaced CEO Jeff Immelt with John Flannery. By November 2017, GE began cutting 25% of their digital expenses, according to a New York Times article on GE’s digital ambitions. Soon after, they eliminated thousands of jobs, and a year later GE was dropped by the board of the Dow Jones. After failing at digital transformation the first time, the organization cut back and has opted for a more calculated step-by-step approach that leverages industry knowledge and customer feedback.

GE threw millions of dollars at digital transformation only to dampen the momentum of their initiatives by slashing their budget and eliminating jobs. The core problem wasn’t the initiative itself, it was the approach. Like GE, many organizations have experienced shiny object syndrome when it comes to digital. Although the initiative’s concept is good, a lack of understanding about the complexities of navigating the ecosystem keeps it from being successful. Instead of laying the foundational groundwork and taking an analytical stance, they got off course in their decision making after misjudging the electric power market and reaching too far outside of their area of expertise.

These examples are evidence that transformation attempts in the current economic backdrop aren’t always a surefire guarantee of success. The Principal Research Scientist at MIT, George Westerman, believes that digital transformation succeeds when it starts on a strong platform for knowledge dissemination. Success is predicated upon everyone in the organization communicating across a shared space, buying into the transformation initiative, and making decisions while armed with the appropriate knowledge. This is where the concept of ba comes into the mix.

The Concept of Ba in and around Digital Transformation

Japanese philosophers Kitaro Nishida and Hiroshi Shimizu developed ba, a concept centered around the importance of knowledge dissemination. Literally translated, ba means “place” or “scene.” In a business sense, the term represents the place where relationships are formed and knowledge is created. It is defined in the following way:

Ba extends beyond traditional human interaction. The focus of ba is on the principles of building self-serving systems. These systems focus on value-creation and empower individuals to realize themselves as part of the environment in which they work. For individuals, ba is the team dynamic. For teams, ba is the organization. For organizations, ba is the market.

The idea of ba is a scientific approach to managing complex systems — very complex systems — by compartmentalizing various types of knowledge in shared spaces, thus encouraging collaboration. Each environment, from the individual entering a team to the organization entering the market, is filled with nuances and complexities.

It’s on the ba platform that individual and group knowledge is broken out of silos, dispersed and integrated across the organization. This knowledge gathering and sharing happens in either a physical, virtual or mental space and in one of these four manners — socialization, externalization, combination or internalization.

These four types of ba serve various functions across the organization. For example, in the socialization stage of ba, people share a physical and mental space during conversation. During the externalization and combination phases, physical assets might be passed along. These assets could also be delivered and/or discussed virtually by email or on a webinar. The internalizing stage is used to exercise the knowledge that’s been gathered, usually in a shared mental space as teams learn and grow together as a team. The type of knowledge shared in each type of ba is either tacit or explicit, or a combination of the two.

Explicit vs. Tacit Knowledge

There are two types of knowledge gathered in the ba space — tacit and explicit.

Explicit knowledge is the information that’s readily accessible, articulated and verbalized. Physically, this type of knowledge usually takes the form of documents or various forms of media. It’s typically shared as data, documents or digital files. People often reference explicit knowledge when articulating irrefutable facts or trivia.

Conversely, tacit knowledge is soft knowledge, such as subjective insights, intuitions, or hunches. Tacit knowledge can be thought of in two different ways. First, internally, which includes your and your team’s expertise, know-how and cognitive skills. With internal tacit knowledge, you’re able to adjust your company culture and create a more tacit environment with a predictive stance to problem recognition and creative problem solving. Second, tacit knowledge is drawn from qualitative information in the form of insights from areas, such as feedback, observations, values, attitudes and more. Regardless of its form, tacit knowledge is highly personal and difficult to formalize.

It’s imperative that tacit knowledge informs your explicit knowledge to humanize the data and disseminate deeper insights across the organization. But in order to increase our level of explicit knowledge, we must cultivate an environment that’s tacit in nature. The entire system or approach to building out a more humanized company culture — or environment — is known as the semantic feedback network.

Semantic Feedback Network

The semantic feedback network is how organizations can become connected through the dissemination of both tacit and explicit knowledge. This dissemination is a convergence of the 3 Ps, in which people share their knowledge in shared spaces — including virtual platforms — via an evolutionary process. That process looks like this:

Think about a semantic feedback network as various loops — which including both data and innovation loops — that fall under one of four quadrants:

• Socialization: All tacit knowledge, such as face-to-face communications
• Externalization: Tacit knowledge paired with explicit knowledge, such as a dialogue in which information is shared verbally
• Combination: Explicit knowledge paired with other explicit knowledge, such as financial statements
• Internalization: Explicit knowledge that deepens into tacit knowledge, such as learning a skill and then putting that skill into action

These loops continually circle around each other, bouncing between tacit knowledge and explicit knowledge and then back again. As they do, the culture becomes more connected, which is key to productivity and growth. This connected culture is critical to an organization’s success. McKinsey Global Institute found in their research on the social economy that productivity improves by up to 25% among connected employees. This was confirmed by a Gallup study on culture compliance that determined teams with high employee engagement rates are 21% more productive.

Semantic feedback networks can’t be effective without spaces, as seen in ba, and systems to enable dynamic cooperation among the microsystems throughout the organization. As the culture becomes more intertwined and tightly knit, individuals are able to break out of their individual thinking patterns to gather and share knowledge more collectively. This approach is recognized by knowing the details of another person’s knowledge through a semantic feedback loop, which keeps associates on the same wavelength when it comes to leveraging insights to drive transformation. As more employees get on the same wavelength, teams start to work more in harmony — a concept known as bioholonics.

Bioholonics: A Scientific Approach to Complex Systems

The creator of the concept of ba, Hiroshi Shimizu, had a lot to say on team cooperation and information sharing, and he didn’t stop at the concepts and theories of ba. Shimizu also developed the theory of bioholonics. Bioholonics represents life phenomena and the way in which complex systems self-organize to perform specific functions in cooperation with other components. In the theory of bioholonics, Shimizu asserts that living things create macroscopic information which consolidates the functions of each autonomous element.

In a business sense, bioholonics can be used to describe a similar scientific approach to complex systems where autonomous entities work cooperatively toward a common goal for the organization as a whole. A good metaphor of his theory can be found by looking at the human heart.

Each individual cell of a heart vibrates independently, but when working together as a whole, heart cells synchronize to vibrate at a uniform pace so that the heart beats 60 times per minute. Japanese groupism culture is a prime example of what working in harmony, much like a heartbeat, looks like in action.

The Japanese culture possesses an intellectual tradition of oneness — unifying self and others together into an indivisible social unit. When we talk about the StoryVesting framework, the synergies we regularly refer to across the 3 Ps — people, processes and platforms — are similar to this groupism culture. Tying the cognitive associations of key people — employees and consumers — together allows organizations to create a more sublime experience that drives transformation efforts. In doing so, organizations are able to incrementally increase the power of knowledge and insights through tactical dissemination. As teams combine the microservices and loops in the semantic feedback network, they’re empowered to develop a larger macrosystem of feedforward and feedback processes.

The shared environment, or ba, plays a role in the type of knowledge gathered and how it fits into the system as a whole. The combination of information enables dynamic cooperation among the microsystems. Meanwhile, the concentric circles of the StoryVesting framework facilitate a natural alignment of information specific to the primary objective (model) and the story of the business, and correlation to the behaviors of the consumer (market).

By feeding order back into the group through theories such as ba and bioholonics during periods of fluctuations, organizations can stabilize and extract insights that can be directly materialized as products and services. In doing so, organizations are able to enrich the quality of their deliverables by closing the loop and moving toward digital maturity.

The Digitari Are Unlocking the Potential of Digital Transformation

Operations and technologies only scratch the surface of what digital transformation entails. It requires the convergence of two dimensions — digital intensity, which is the investment in altering how the company operates in a technology-enabled world, and transformation management intensity, which speaks to the leadership capabilities necessary to see digital transformation through. When blended together these two axes form four types of digital maturity.

The amount of gumption organizations put into both their management and digital intensity determines into which quadrant they fall. Most organizations start in the Beginner quadrant and work their way outward. The companies with shiny object syndrome, known as the Fashionistas, often latch onto advanced digital capabilities but lack the know-how to implement them. Similar to organizations who have a perceived lack of time and resources, conservatives often have the drive to develop digital initiatives but lack the tools and expertise.

Companies that become fully digital are known as the “digitari” of the corporate world. It’s the digitari who are best able to gather, analyze and execute on Big Data through a tightly-woven culture and infrastructure. In doing so, they’re able to advance and outperform their competition in three core areas:

• Driving Innovation — Increasing organizational capacities via bioholonics of people, process and platforms to promote perpetual optimization and innovation across the business
• Remediating (Flattening) Costs – Recursive usage of an informational ecosystem via the capturing of knowledge (data, insights, insight meta-data, target (variable) definitions, tribal knowledge) and dissemination via a semantic feedback network
• Fueling Growth — Reaching customers anywhere, anytime in existing, emerging or new markets, including through ever growing mobile and social channels

The financial performance of the digitari is consistently higher than that of their counterparts in three areas — revenue generation, profitability and market value.

These benefits of a digitari’s overarchingly better financial performance are realized and achieved by extracting insights. This extraction is done through the humanization of quantitative and qualitative data across the entire organization and by building insightful journey analytics.

Still, many companies are stuck using spreadsheets to disseminate data. This grossly overwhelming overview of the insights available is enough to paralyze any team, creating a more reactive culture that causes organizations to fall behind, rather than take a proactive role similar to market leaders.

No matter how analytical and intelligent your team is, when presented with insights in this format it can be hard to extract what’s needed to drive transformation initiatives. Without strategic data visualization methods to disseminate knowledge, organizations will stay stunted and avoid taking the necessary steps to move toward transformation.

This strategic and purposeful data visualization must tell a strong story. Let’s take a look at an example of what this type of visualization can look like, and why it’s so powerful.

A Customer Insights Map is the North Star Source for Innovation

We’ve covered the importance of leveraging insights, data and analytics across the organization, and the importance of disseminating this information in a democratized fashion. One of the most practical solutions to taking this approach pervasively and effectively is through our proprietary Customer Insights Map (CIM), which we reveal and teach in our LevelNext MasterClass on Modern Business Transformation. It’s here that we apply data, analytics and insights to the traditional customer journey map. It’s what we call the next evolution of modern customer journey visualization.

Organizations must have a fully baked and built-out CIM to provide context and information holistically across an organization as a requisite step to achieve the full-scale capabilities that lay the groundwork for digital transformation. In setting up data visualization this way, you can zero in on issues and insights more easily. We do this by looking in two directions — horizontally and vertically.

When looking horizontally across the customer’s journey, you’ll get an end-to-end view of what’s happening throughout the buyer’s experience. This end-to-end view lets you identify root causes of experiential problems rather than attempting one-off initiatives in hopes that small tweaks will have vast results. When looking vertically at each stage of the journey, you’ll gain the necessary insights to know which departments and platforms are touching the customer and employee at every stage of the buying cycle, as well as what needs to change to improve those experience scores.

On this CIM, we’ve noted which platforms are being used and which departments are responsible to help teams better see where there’s overlap and where ba, or a shared space, must be solidified and utilized between the teams. In addition, we’ve infused the CIM with empathy mapping and experience scoring for both the employee and customers. This gives us a very quick overview of what’s happening along the buyer’s journey using data (explicit knowledge) to validate any hunch (tacit knowledge) about what’s happening at each touchpoint.

When insights are applied with excellence across the customer journey in this manner, customer-centric cultures are better able to anticipate emerging changes, not only in consumer behavior but also in new entrants to the market. By the fostering of ba, organizations are better equipped to access and act upon the insights they receive. Through these insights, organizations can then customize relevant interactions by integrating unstructured data with structured data for an enhanced and more intuitive consumer journey.

The end-to-end journey score (whatever that North Star Metric is for your organization) is more important now than ever before. The modern consumer is more empowered, sophisticated and complex, which has caused one-off-campaigns and singular touchpoint analytic frameworks to quickly start becoming irrelevant. To that end, the frameworks, the infrastructure, the data loops, your people, your processes and more all need to match that level of elegant sophistication but with layered simplicity so that the entire organization can quickly digest, understand and communicate the value.

Buyer’s journeys today are complex. The same cohort can take several different paths to find and purchase from an organization. To know which path is driving the biggest growth, and thus where you should invest your money, you have to have insights about what’s happening along that journey.

Your North Star Metric alone can’t be the sole factor in deciding where you spend your money. In comparing two paths-to-purchase on the CIM, you’re able to quickly visualize the value of each journey. Attaching differing metrics at each stage gives you deeper insight about which things are going well and where you can improve. Examples include understanding which path converts the fastest and with the most revenue or which journey is the fastest and has the highest cost of acquisition (CAC) ratio. You might also quantify qualitative metrics and dig into tacit knowledge by analyzing which path offers the highest customer satisfaction score and compare that to other factors, such as their time in their journey.

These paths-to-purchase don’t stop once a buyer converts. They extend long into the lifetime of the customer. Continue comparing key metrics on the backside of the bowtie funnel to find areas for improvement. In taking this approach, you’re equipped to pull out information about where it makes the most sense to enter into digital transformation efforts and which initiatives will drive the biggest outcomes. By visualizing this to the entire organization you can create buy-in, disseminate tacit and explicit knowledge alike and simplify an otherwise enormously complex system.

It’s through this modern approach to knowledge dissemination that organizations can strategically engage in digital transformation initiatives. By using insights to distribute and democratize knowledge across a variety of shared spaces, teams come together to work in harmony with one another toward a common goal.

Summary

If you simply focus on marginalizing costs as a “nice to have” or as a byproduct of recursive usage of digital assets, then you are at risk of experiencing misaligned KPIs used to track digital transformation success and a disparity of effort across the organization. Although it’s nice to talk about economies of scale in theory, we also know that having a holistic, combinatory system in place for full-scale democratization is exactly what’s needed for this to occur. Few to none can say they have achieved a fully democratized digital infrastructure.

Synergizing efforts across the organization is the real power to driving digital transformation. Through this synergy and armed with insights, data and analytics, you’re equipped to incrementally increase the power of information via a pervasive approach to disseminating the knowledge you have at your disposal.

We know how easy these concepts are to discuss and how difficult they are to pull off. If you’re vested in your organization’s digital transformation and want to play a key role in seeing it through to success, we encourage you to start laying the foundation by democratizing data and analytics across the organization. This approach is precisely what we teach in our LevelNext MasterClass on Modern Business Transformation. In the workshops, we’ll walk you through exercises, such as our modified Hoshin, to enhance team synergy. You’ll also gain a deeper understanding based on data and insights about what’s happening along your customers’ and employees’ journeys by understanding our proprietary Customer Insights Map. We teach you how to operate within your organization much like a heart’s cells beat in harmony to keep blood pumping through the body. Within your team, you’ll learn the core areas of digital transformation and how to move in sync toward a common goal. Will you join us?

Downloads and Resources

V Shaped Teams

Future Workplace Skills

Employee Engagement Trends

Top Performers of Digital Transformation

Data-Driven vs. Insights-Centric

Explicit vs. Implicit Knowledge

Semantic Feedback Network

Four Types of Digital Maturity

Customer Insights Map

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