`8 Designing Your Company for Digital`

In chapter 1, we observed that SMACIT (social, mobile, analytics, cloud, Internet of Things) and other digital technologies are changing the competitive landscape. These technologies have introduced three capabilities that require companies to rethink their customer value propositions: ubiquitous data, unlimited connectivity, and massive automation.

The message of this book is that, to succeed in the digital economy, you need to be inspired by these capabilities. You need to imagine what’s now possible for your customers that wasn’t possible before. Then you need to design your company—your people, processes, and technologies—to deliver on that inspiration.

There will surely be winners and losers in the digital economy. We anticipate that the winners will succeed at both digital inspiration and digital design. What might not be obvious is that design can—and should—influence inspiration just as much as inspiration influences design: autonomous teams steeped in customer awareness will come up with ideas for offerings you haven’t even dreamed of. In this chapter, we’ll review how to get digital inspiration and design right.

How Not to Be Inspired by Digital Technologies

A risk with digital technologies is that leaders can get caught up in the hype about a technology. In the short term, the value propositions that a given digital technology makes possible typically exceed what any company can pull off. That’s because the value realized from the use of digital technologies is limited by what people in complex environments can (and will) actually do.

Without digital (re)design, any new technology will, at best, improve how companies do what they’ve always done. It won’t deliver a new exciting value proposition to customers. For example, big data can provide insights about customer needs. To use those insights, however, someone must be able to adapt an offering to reflect the new knowledge. If a company does not have the appropriate accountability framework around that offering, no one will own—and thus be capable of changing—it. Benefits of big data unrealized!

Similarly, blockchain will deliver data transparency, which can be a powerful business enabler. But companies that have not accumulated insights about what their customers want and what changes they themselves are willing to make may well pursue all kinds of frivolous applications.

This is why the concept of the building blocks is so important. Executives cannot simply insert game-changing technologies into their technology portfolios and wait for valuable new offerings to come rolling out. Companies need to arrange all the pieces of the puzzle so their people will be able to learn how to effectively apply the capabilities of digital technologies to new value propositions.

If a company purposely pursues learning how to (a) build new infrastructure, data and business components, (b) test and learn what its customers value, and (c) enable individuals to deliver on those capabilities while aligning their individual efforts, leaders can take the business to the next level. Artificial intelligence is a perfect example of a technology with lots of potential to change a business—or not.

Artificial Intelligence: Inspiration and Challenge

Perhaps no digital technology generates more excitement about its ability to change business right now than artificial intelligence (AI). Often in conjunction with other digital technologies (especially analytics, IoT, and cloud computing), AI brings to bear the possibilities that ubiquitous data, unlimited connectivity, and massive automation have to offer. Converting the possibility into reality, however, is not easy.

Autonomous vehicles highlight both the promise and the hiccups that accompany an AI implementation. As with most proposed applications of AI, autonomous driving improves on an old idea—getting a vehicle from one location to another. The opportunities for improvement relate to greater safety (by eliminating human error), lower cost (in cases where the driver is compensated), or elimination of an undesirable manual task (driving, for example, in Bangkok traffic). In other words, AI changes the experience but not the goal.

Conceivably, autonomous vehicles will change the value proposition of automobile manufacturers. They could inspire people to reimagine personal transportation and even lifestyles. But autonomous vehicles must adapt to existing road and transportation systems. If creators of autonomous vehicles could also create the context for autonomous driving, they would build different roads and traffic control systems, and they would propose different rules of the road. But that is not an option.

Autonomous vehicles, for now anyway, must succeed on roads and in systems designed for human drivers. These roads and systems are sometimes unsafe (due to bad design), sometimes inadequate (due to growing usage), and sometimes inefficient (due to changes in travel patterns). These realities mean that autonomous driving features currently constitute product improvements rather than new value propositions.¹ AI algorithms are having an impact on cars—indeed a growing impact—but we haven’t realized the dream.

Companies inserting AI into their technology portfolios face a similar challenge. They have existing business models, as well as established processes, systems, and roles. Although the capabilities of AI create opportunities for new business value, a company will only realize that value if it redesigns those systems, processes, and roles and reimagines its value proposition.

Adopting AI for Digitization at OneBankAssure

Leaders at a financial services company, which we will refer to as OneBankAssure (1BA),² were inspired by the capabilities of data science and artificial intelligence to transform the company into a more data-driven, customer-centric company. To pursue that vision, in 2014, the CEO created a Decision Science and Machine Learning (DSML) unit and populated it with 30 data scientists and machine learning experts. Three years later, the company had 75 data scientists developing hundreds of new applications a year (90% of which applied machine learning models).

Relative to most of the companies we’ve studied, 1BA’s adoption of AI was extremely successful. AI applications had significant bottom-line impacts and leaders were pleased with the results. They noted, however, that the company had been slow to realize its vision of becoming data-driven and customer-centric. At the time we were studying 1BA, AI had not yet had a meaningful impact on 1BA’s customer value proposition. Although a few applications introduced digital customer services (like alerts that a storm is approaching) most of the applications had generated improvements to internal processes and decision-making.

Why had 1BA’s AI initiatives fallen short of the vision? Because 1BA had not redesigned its business to drive customer value from AI.

1BA had an excellent operational backbone (which, by the way, had provided invaluable data for AI applications). For the most part, the DSML unit was relying on the same systems and processes 1BA used to build and improve its operational backbone as it implemented AI applications.

Here is the process 1BA used for implementing AI. A steering committee established priorities for data science initiatives and oversaw intermediate outcomes. Although AI project teams were more cross-functional than typical IT development teams (AI teams included a business owner, a user, a data scientist, a business analyst, and, on occasion, a customer), AI teams used essentially the same methodologies for designing and delivering AI applications that produced the company’s operational backbone. New code developed by DSML was turned over to IT operations for quality assurance and production, while the DSML experts moved on to their next project. A business owner took responsibility for ensuring that necessary business process changes were adopted. Although the business owner and IT operations shared responsibility for monitoring the behavior of the AI model over time, DSML suggested that models be updated no more frequently than quarterly.

In other words, 1BA was relying on its tried-and-true organizational design and it was generating the kind of business value at which 1BA was proficient. It had not redesigned for digital at the time we were studying it. It had not developed processes for capturing insights about what customers wanted. It had not designed a digital platform to systematize reuse of business, data, and infrastructure components. It had not redesigned accountabilities around living assets. And it had not considered the need for an external developer platform. AI was helping the company generate traditional efficiency benefits, but 1BA had not changed the game! (At least not yet. Its operational backbone will give it a head start when it is ready.) In short, recognizing that a new technology like AI could be game changing is not the same as creating the context for a new game.

Customer Value Propositions Inspired by AI

In contrast, at Schneider Electric and Royal Philips—two companies that are substantially designed for digital—AI already forms an integral part of digital offerings.

For example, by inserting AI into its IntelliSpace oncology solutions, Philips helps oncologists monitor changes in a patient’s condition (e.g., a growing tumor, a change in weight, an anomaly in a lab test). AI can process data faster than a human, so these AI solutions can offer recommendations on possible therapies that oncologists might have overlooked.³

Similarly, Schneider Electric is using AI to improve predictive maintenance.⁴ Increasingly, Schneider’s customers can rely on AI-powered alerts to tell them when they need to fix or change equipment proactively instead of reactively. These improvements can eliminate breakdowns, unscheduled downtime, and unnecessary onsite service visits.

Philips and Schneider have been able to use AI to enhance—and inspire—customer value propositions because the responsibility for inserting AI components into offerings is owned by the teams that are empowered to continuously improve those offerings. Both companies have mechanisms for accumulating customer insights that identify when a solution would be more valued if it was more intelligent or when a customer problem results from inadequate insights. They have a platform of configurable living assets that can be constantly enhanced without demanding changes in other components. They have an underlying operational backbone (even if it is not as disciplined as they’d like) that enables them to reliably complete transactions and back office processes. They have partners who are expanding their value to customers by developing complementary components and offerings.

DBS applies AI to both internal processes (e.g., deciding which bank branches to audit) and new offerings (e.g., exploiting an AI-enabled chat bot as an enabling feature of its mobile-only bank in India). Its AI expertise is located in AI-focused teams that support or consult to both internal and externally focused teams, as well as in teams that own internal processes and external offerings. DBS is studying how to componentize applications and offerings so that AI models can be isolated from other components. If they can do that, the AI model components can be more dynamic and can learn without requiring changes to other components. This is how AI benefits a company designed for digital.

The capabilities of AI—or any other digital technology or set of technologies—should inspire companies to embark on a transformation journey that will allow them to deliver new value propositions. They may inspire specific ideas of how greater insights could benefit customers. But it’s also possible that the inspiration may not offer—at least initially—a very clear vision of where that journey might take them. Part of the transformation journey is learning what your company might achieve for customers, and thus clarifying your vision. Thus, for starters, we don’t think companies need to be more inspired than to recognize that digital technologies allow them to fundamentally enrich their customer solutions and engagement. Every company can get started on that journey.

Time to Get Started: A To-Do List for Embarking on Digital Transformation

A surprising number of companies cite the visit of their senior executives to Silicon Valley as the moment they got religion around digital. We are not sure such a trip is the only or best way to get religion. But it is clear that inspired senior leaders are a prerequisite to a successful transformation journey. If a trip to Silicon Valley helps inspire them, take the trip.

But don’t expect the trip to Silicon Valley to provide much more than a sense of urgency. It’s easy to start flailing when the only thing that’s clear is that becoming digital is a competitive necessity. Most leadership teams underestimate the task at hand. So take a pilgrimage, read a book (preferably this one!), hold a leadership team conference, bring in an inspirational speaker—do something to ensure that your leadership team is ready to commit to becoming digital. Then start ticking off the following six items in the to-do list for becoming digital:

Choose metrics that inspire people.
Assess your building blocks.
Roadmap your journey.
Establish ownership for each building block.
Communicate your vision and your journey.
Commit for the long haul.

Choose metrics that inspire people Are you feeling comfortable that quarterly performance metrics and business line financial results will generate passion for your digital transformation? We hope not. You’re not serious about digital until you realize that your existing metrics are only relevant to your existing business. Metrics useful for a digital business assess your value to your customer, not your performance. PI Chile seeks to improve customer readiness for retirement. Philips aims to improve healthcare outcomes at lower cost. Schneider Electric is going to make sure customers have all the energy they need for the lowest cost possible. USAA will not be happy until USAA members are financially secure. These goals set companies up to transform. To help your people get excited, they will need some measurable objective. DBS attacked customer-wait time. Philips is going to change three billion lives a year by 2025. Metrics like these change behaviors. In the short term, they also create tension because companies cannot abandon traditional metrics, but companies that establish these metrics and make them count are set up to make progress on their transformation.

Assess your building blocks How strong are your customer insights, operational backbone, accountability framework, digital platform and external developer platform? Recognize your existing capabilities (appendix 2 provides a tool for assessment) so you can build on them. Understand your limitations because they should guide your journey. This assessment will help you prioritize. It will also help people in the company link their own goals to the building blocks. One thing that hasn’t changed about strategizing—you still must decide what you’re not going to do, not just what you are going to do. Assessing your building blocks will help you identify your highest priorities.

Roadmap your journey Make a plan, even though it will change as you learn what works and doesn’t work with customers. Decide what investments matter most now and what needs attention down the road. There will be surprises, but a plan helps you recognize them and adjust. Reevaluate your roadmap regularly by reassessing your building blocks and monitoring your key metrics. In chapter 7, we outlined a way to visualize how you are planning to divide your company’s attention and resources across the five building blocks. Go grab some colored sticky notes and start mapping out your company’s journey.

Establish ownership for each building block Sometimes everyone in a company shares ownership for a given building block (like customer insight, at DBS). At other times, the owner of a building block (for example, the general manager of your external developer platform, the chief architect of your digital platform, or your CIO) should take it and run with it. Things get done in digital companies when a problem solver takes ownership of a problem and leadership empowers the problem solver to solve it. Building blocks are big commitments. Put a senior leader in charge of each, have that leader define goals and make a roadmap. Then reconcile the roadmaps for the various building blocks, and move forward.

Communicate your vision and your journey Explain your new metrics, expose your building block assessment and roadmap, and make it very clear who owns what. Communicating your intentions will not only help people get on board, it will make it more obvious when the train starts to go off track. Widespread awareness will generate more ideas on how to fix what’s broken—and more commitment to doing so.

Commit for the long haul Understand that your board, your investors, and most market analysts are largely clueless about what it means to become digital. Unlike start-ups that accumulate vast sums of investor dollars on what sometimes seems like just the whiff of a good idea, your investors will get nervous when they don’t see quarterly results from your digital initiatives. This is no time to hide. State your intentions. Sell your ideas. Communicate your intermediate metrics that will signal progress. Manage expectations. You’ll need to sustain your existing business, but you must generate excitement about your vision outside of your organization as well as inside it. As you learn and your roadmap changes, share that too. You’re probably not in a position to act like Jeff Bezos, telling people that this is about long-term growth not earnings, but you can take a page from his book. (In his 1997 letter to shareholders, Bezos made the statement that “It’s all about the long term.” Each year since then, he has attached that letter to his new letters.⁵) Educate your investors, board, employees, and market analysts about what it means to be digital, how you will succeed, and why they should trust you. But also start small. Don’t invest massive amounts of resources in ideas that may or may not gain traction. Act like a start-up!

What Are You Waiting for? Design Your Digital Business!

In chapter 1, we acknowledged the temptation to approach strategic change by restructuring the company. We have argued that structure is an inadequate tool. Frans van Houten, CEO at Philips has similarly observed the limitations of structure:

Historically we have always done a transformation by focusing solely on the organizational structure. For example, we thought that by changing the reporting lines, we would be successful. Of course, this is nonsense and although Philips has reinvented itself many times in the past, I do believe that this narrow approach has held us back. So for our radical transformation to a health technology company, we took a holistic and very comprehensive approach. We integrally addressed all the factors that drive success, including shared vision, culture & behaviors, capabilities, processes & systems, and incentives.

The “factors that drive success” he was referring to are the elements of what we defined in chapter 1 as digital business design: the holistic organizational configuration of people (roles, accountabilities, structures, skills), processes (workflows, routines, procedures), and technology (infrastructure, applications) to define value propositions and deliver offerings made possible by the capabilities of digital technologies. The five building blocks described in this book package these elements to deliver that kind of holistic design.

We hope this book has given you the inspiration and confidence to redesign your company for rapid delivery of digital offerings that customers are willing to pay for. It’s time to put this book aside and design for digital!

Notes