Mental Models to Clarify the Goals of Digital Transformation, Part 2
In an earlier post, I proposed that rather than trying to make sense of the term digital transformation, we think of it as the application of eight new mental models to the way we do business. In that post I discussed the first four mental models; here I’ll cover the remaining ones.
Model 5: Being Data-Driven
This mental model, unfortunately, is also based on a term that’s quickly being emptied of its meaning by overuse. But there’s a big change afoot. In the old days, our data was locked in databases that were structured transactionally, so only limited operational reporting and analysis was possible. Today, we’ve freed that data for broader analysis and added to it nontraditional types of data like audio and video. We also have tools like machine learning available to analyze it in new and powerful ways.
Organizations can use their data to improve customer service, to find new opportunities for generating revenue, to reduce costs, and who knows what else—it just depends on their creativity and the particular business challenges and opportunities they face. As a result, the value of corporate data has increased geometrically.
More data also means more opportunities to misinterpret data. A truly data-driven company takes a professional approach to drawing inferences from its data—that’s why data science skills have become so important. Human insight is still critical in the digital world—maybe even more than in the analog world—but it is insight informed by data and insight that may be tested by gathering further data.
The increasing focus on data has led to technical questions about how we manage our data. Are relational databases always the best way to store data? How can we build privacy controls into the data and the tools we use to analyze it? How can we attach a financial value to the assets that our databases represent? How can we process tremendous amounts of data quickly enough to take appropriate actions based on it?
Digital transformation, in this mental model, is about more than collecting, storing, and analyzing data. It is about learning to use it effectively.
Model 6: Increasing Resilience
The digital world is one in which we’re connected at all times. It requires that our information systems be available more or less 100% of the time, both in normal operations and in the face of disasters. That, in many ways, is the foundation for all the other things we call digital transformation. Enterprise technology must be resilient to everyday interruptions—employees tripping over wires, hacker attacks, sudden spikes in website traffic—but also resilient to crises like pandemics and flooding.
The expectation for continuous availability comes partly from the increasing importance of IT systems to company operations—without IT, the company can’t operate—and partly from the public’s growing expectations for always-on services. Information services are no longer consumed just during business hours, which anyway are 24 hours a day in today’s global multi-time-zone business world, but at any moment when a consumer chooses to look at their smart watch. The days of “Sorry, our system is down for maintenance—please check back in a few hours” are gone. As are the days of “Whoops—that’s a bug. Please enter it into our bug tracking system and we’ll get to it in a future release.”
Since our systems are always on and always connected, they’re always available as targets for hackers. It’s in the nature of digital services to be under attack. Security, like resilience, must be built in from the ground up: not something added, but a design consideration and an attribute of quality.
Digital transformation involves making information services available like any utility is. I take that back—even more available, since they shouldn’t be vulnerable to power outages either.
Model 7: Becoming Future Ready
Digital transformation is also about being able to cope with future demands. The most important thing to note about the future is that it’s unknown. No matter how much you think you know, you’re certain to be surprised. There are “unknown unknowns,” as they say. Digital transformation is about preparing your organization to respond to unknowns. When something unexpected happens—a competitor’s price change or new product introduction, a change in consumer behavior, a Brexit, a trade war or a real war, rushed legislation—will you be prepared to deal with it? Is your company in a position to survive disruption and adapt to new competitive environments?
The key to becoming future ready in the digital world is to become agile, nimble, flexible—choose whichever word is less “loaded” with distracting connotations. Agility, to me, is the ability to react appropriately, quickly, inexpensively, and at low risk to change. Since most enterprises have not set themselves up to be agile, they need to un-become some of what they are. When it comes to IT, for example, they may have to replace outdated legacy systems, move to the cloud, reduce technical debt, build new skills. They may also have to change their governance and investment oversight processes, their organizational structure, and their culture.
This mental model makes digital transformation the process of readying the organization to cope with an ever-surprising future. It’s uncomfortable, because it’s about investing in capabilities that will be used in ways we don’t yet know. It therefore requires a different investment strategy, essentially one of investing in real options, or in an intangible ability to approach tomorrow with speed and flexibility.
Model 8: Building the Enterprise of the Future
Digital transformation is not just a bolt-on to what businesses look like today, but a different way of understanding what a business is. That may sound frighteningly complex, but it doesn’t necessarily mean a big change in what we do each day, just in how we construct our business strategies.
Let’s put all of the other seven mental models for digital transformation together. Let’s say that we can move pretty much as fast as we want, and that our competitors can too. Let’s say that we can get a rapid flow of innovation going—and our competitors can too. We can use data effectively, even in tremendous quantities, as can our competitors. We’re always on and always available. And we have a host of new technologies that are so game-changing that no one yet knows all the changes they will bring. And, yes, it’s the same for our competitors.
Does this mean that we are living in a commoditized, hyper-efficient market, where it’s impossible for any company to have a true advantage over its competitors? Quite the opposite, I think. Just because every company can innovate easily doesn’t mean their innovations will be equal. And their focuses will be in different areas: some may emphasize customer service, some price—well, you know, all of the usual competitive positioning options. And the only way to make these kinds of decisions in a fast-paced environment is to already have agreed on principles, values, and tenets beforehand.
It’s sort of like the arts—literature, say. Writers are constantly influenced by other writers, borrowing ideas, learning, emulating their teachers and intellectual ancestors. Yale critic and scholar Harold Bloom even wrote a book on the subject, The Anxiety of Influence. But despite these influences, each great writer is unique. The same is true in painting, where each artist is part of a history of art, influenced both by artists who have come before and by their social climate.
The digital world doesn’t just lower barriers to entry for new startups—it also lowers barriers for existing businesses to be creative. Think of it as frictionless, or at least tending in that direction. The tools matter less; there’s a direct channel from employees’ minds to customers. Companies are influenced by history, competitors, and the social environment—just like artists. And just like artists, each company produces a different strategy and a different product, a different value proposition for customers.
Where do their differences come from? The “personalities” of the companies, in a sense. Who they’ve hired, their values and principles, their competencies in the physical world, the markets they’ve chosen to focus on. Perhaps most importantly, their ability to form diverse teams whose creativity exceeds the sum of its members’ creativities.
You see this emerging today. Companies increasingly realize that they need to attract not “the best” talent (as if there is an objective scale ranking all potential employees) but the right talent, with the right fit, with the right passion, with the right diversity.
Digital transformation is hard to pin down, because we mean many different things by it. In these two posts, I’ve proposed eight mental models to distinguish the different ways that people have been talking and writing about it.
- Gaining Speed
- Using Digital Technology
- Interacting Digitally
- Becoming Customer-Centric
- Being Data-Driven
- Increasing Resilience
- Becoming Future Ready
- Building the Enterprise of the Future
Each of these is a way of thinking about digital transformation. They’re all based on a common set of practices and organizational cultures, but focus on different goals. Digital enterprises are fast; they use digital technologies and interact digitally with their customers. They take advantage of digital interactions to become intimate with their customers; and they take advantage of the hard data that is available to test their ideas. Because they’re nimble, they’ll be able to deal with the unexpected. They know that customer interaction can’t wait until an outage ends, because customers don’t want to wait. Add it all together, and assume that your competitors see it the same way—and I think we’re talking about a new kind of business enterprise emerging from our “transformations” of today.
Digitally Transforming What Exactly?, Phil Le-Brun
Tuning Up the High-Frequency Enterprise, Phil Potloff
The Future of Faster Enterprises, Miriam McLemore