In an earlier blog post this year, I shared my view that digital transformation is all about achieving business goals by creating new (or improving existing) business capabilities.
Here’s an example to recap the point: let’s say your goal as a facilities organisation is to keep city centre bins empty. There are a number of ways you could deliver this outcome, but here’s two for comparison purposes:
Sending a garbage truck on a route to empty every bin in a city centre
Deploy ‘full’ sensors on each individual bin and a smart GPS route-planner to automatically create a route each day that only includes the bins that need emptying.
Both approaches yield the same result - but building the new capability to take the second approach means you can deliver that goal in maybe half the time at half the expense. The data collected offers associated benefit and opportunities for further efficiency gains: understanding where more bins are needed, or where existing bins are unused.
Capabilities are unique to each individual business; however, they are often built on common technical foundations. The advent of smartphones, the cloud, 4G, IoT etc. have all created a wave of transformational forces that most businesses need to respond to. So, what do those common foundational blocks look like?
1. Integrated data.
There has been a lot of talk about the power of data in the last few years. While that may be true, data held in isolation is generally difficult to meaningfully leverage. What does that mean in practice?
Many businesses find themselves with disparate HR, finance, sales and reporting systems, with network and product data and analytics that run in their own void. This usually leads to myriad bridging spreadsheets, manual processes and reporting, which adds up to a complete inability to create reliable, actionable insight.
Integrating everything with everything isn’t a viable option either, but that’s where strong data strategies come into play. Data lakes and warehouses, data modelling and data management strategies (if done well!) should act as a foundational block upon which to build new capabilities.
2. Single customer view.
One of the most common blocks to build on top of a data strategy is the extracting and modelling of a single view of the customer. In practical terms this just means connecting all the useful data to one single known identity: the customer object. Billing, marketing, sales, usage data etc all help to build a comprehensive view of a customer base that can then be used as to found or catalyse other capabilities.
Managing debtors, reducing churn, understanding buying cycles and predicting sales patterns are just the tip of the iceberg in terms of what can be greatly improved with a strong single customer view.
3. Service-driven technologies.
Technical complexity creates the need for abstraction. This in turn creates more and more discrete, narrow or niche solution areas, like user authentication, payment gateways and media streaming. It’s almost impossible for any modern software system not to be built on top of (and to comprise) many layers of technology systems.
Understanding and leaning into this is extremely important – there is an off-the-shelf solution and service for almost every common problem. Modern software approaches tend to be service-oriented, stringing together many pre-made modules and services into a coherent system. This is a core strength of cloud platform ecosystems like Microsoft Azure – they offer a wide range of component solutions as a service to plug in. Only a few years ago you might have a whole team working on horizontal challenges like ‘search’ or ‘natural language processing’, while now in most cases you can just tap straight into a service providing these in a matter of hours.
Understanding and leveraging service-driven technologies allows businesses to focus on building meaningful capabilities, not designing, creating and maintaining all sorts of disparate peripheral solutions that are not core to their goals.
4. Strong internal reporting.
The last two points on this list are not technical, but are equally critical foundations. ‘Strong’ in this case means understood, trusted and actionable. Without this in place, it’s very hard to measure impact beyond the macro-levels of revenue and EBITDA.
Investing in new technologies can be an expensive proposition, so they must deliver a lot of value in turn. Without the capability to measure and surface the impact and value of these investments it can be hard in a long-term strategy to justify the level of investment and change often required for meaningful digital transformation.
5. Board level buy-in.
In a similar vein to the point above, transformation doesn’t happen overnight - and it doesn’t happen in isolation. It often requires a long-term investment strategy, culture and process changes, staffing changes and even fundamental shifts in business strategies and processes.
Boards typically understand modernisation (the requirement to upgrade and refresh existing processes and capabilities to create efficiency or reduce technical debt) – but they are less well-versed in the need for and potential impact of digital transformation, and often confuse one for the other.
To create an environment where real digital transformation becomes viable, the board must both understand and buy in to the concept of transformation and its evolving scope, risk, cost and value. Aligning cost and value is ultimately their challenge to own on an ongoing basis. Digital transformation is not a discreet project with a well-defined end point as the speed of technical change creates an endlessly moving target. Rather it’s the acknowledgement of the effort and cost required to create and sustain advantage in a digital economy, and the constant re-shaping of a business to move forward with each new wave.