By Bryan Kirschner, Vice President, Strategy at DataStax
Airplanes have a “stall speed,” below which their wings can’t produce enough lift to keep them in the air. While that obviously makes it important for pilots to keep an eye on the airspeed indicator, the underlying reason for a stall is fundamentally about disrupting airflow around the wing.
Even if a pilot puts the pedal to the metal, stalling can be equally inevitable if the aircraft is flying at too sharp an angle.
And for any given aircraft, there’s an optimal “angle of attack” to generate the most lift without introducing turbulence (historically called the “burble point”).
This glimpse into the physics of flight offers us a lesson in the dynamics of digital transformation.
Navigating from a smooth takeoff to successfully landing a truly transformative impact on an organization likewise requires being mindful of multiple signals and minimizing turbulence.
Here, we’ll explore three key ways that we’ve observed to keep digital transformations on course.
Think big, ship small
By nature, data-driven digital experiences are ripe for flywheel effects.
Ideally, delivering great digital experiences wins you more interactions with more customers, generating data that can be used to drive the next round of new and improved experiences. This creates a virtuous cycle.
It holds true for a scenario as bounded as “one team, evolving one app.”
The secret to getting a flywheel spinning is to be willing to ask big, bold questions, “How could we exceed our competition’s NPS by 20% through data products?”—while starting the journey with immediately actionable steps.
Don’t try to define an ideal future experience on paper, waterfall-style, and debate whether all the details are right. Instead, ask, “What’s the most failure-prone part of a process, now, and how can we fix it?” Or, “What data about their current interactions with us might our customers value, and how can we provide it to them?”
Shipping code and data features quickly enables you to (at worst) fail with learning, and (at best) open up new ways to create value for customers that weren’t previously possible to deliver—or even discover.
This is the way to avoid stalling right at takeoff. Don’t try to rationalize the data dictionary across the whole company or clean all the data, everywhere, before taking action. Determine where to focus those efforts by focusing on the data for which you see ways to make an impact—now.
Relentlessly productize (data)
Empowering and equipping teams that are closest to the customer relationship or a business process to innovate and move fast is a proven pattern for successful transformation.
In a large organization, this can mean dozens or even hundreds of teams, each hopefully spinning up their own flywheel effect.
In this context, “speed” has to take a back seat to never cutting corners on one thing: always, always, always treating the data being produced as a product. That means assuming that data will be used, on a self-service basis, by some other team, and treating it accordingly.
This creates conditions for a secondary flywheel effect. As teams that own a process or customer segment make progress on their data-driven, digital journey, “mash ups” of data into new services becomes valuable.
Imagine you’re a retailer and your ability to predict customer responses to targeted offers increases alongside your ability to predict product availability from your supply chain. You’ve now unlocked the opportunity to combine data in order to tailor offers to maximize purchases while minimizing the probability of exhausting your stock. (Or, if you’re a wholesaler, to offer customers smart advice on when to order extra, giving them an advantage over competitors who’ll wind up with bare shelves).
Creating a culture committed to ensuring it is always unambiguously easier to discover, understand, and tap directly into data that already exists is a way to prevent another threat of stalled progress.
This is, in effect, finding that “burble point:” how fast you can climb without introducing turbulence. For example, if one team has created a well-understood, data-driven definition of a “high value account” and, rather than become a customer of this data product, another team builds its own definition and dataset, you’ve made a single view of the truth harder (and lost the chance for the teams to collaborate on evolving it together). Or, worse, imagine teams copying datasets for the sake of speed or convenience, creating data sprawl and inconsistency.
Bet on compounding returns
If you’re successfully orchestrating these two flywheel effects, the scope and scale of your data estate is going to keep on climbing—and that’s a good thing.
Don’t create stall conditions by underinvesting in the capabilities of your data infrastructure.
Build for an expectation of compounding returns from data-driven digital transformation progress, which might multiply rather than incrementally increase the amount of valuable data in your data estate. Because, fundamentally, if you’re not seeing flywheel effects, that’s the problem to fix.
By way of example, in research conducted with hundreds of companies by ClearPath Strategies, those who are running multiple modern, data-driven workloads such as real-time inventory management and personalization are also more likely to be running a 360-degree view of the customer.
Among those running a 360-degree view of the customer, 80% expect to have at least five times as much data under management in the next five years, with nearly a third (32%), expecting 10 times or more. Almost all of them (96%), say their data architecture can either already handle that volume or they are actively executing on plans to make it so.
Many of us have many years of experience in a world where the mantra of enterprise IT was “do more with less.” Today’s reality is that turning data into a driver of revenue and growth means a new core competency: every organization should be mastering how to do “more with more” consistently and for the long haul.
Prepare for a smooth flight
Much in the way that a great pilot uses an understanding of the physics of flight to give their passengers a smooth ride, knowing the dynamics of digital transformation can help executives lead their organization to a successful outcome, with little turbulence along the way.
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