Think of a company that you believe is truly digital. If you are like most others, you thought of a great digital experience you enjoyed as a consumer, and, naturally, the company that brought that to you. And it’s also likely, you were right in your choice.
Although you chose based on just one part of the picture. Because, being digital, for enterprises, is not just about ‘looking digital’ to the consumer (although that’s an important manifestation), but having insights into the opportunities and threats born from the changing needs and expectations of consumers, then modernising and improving their core (along with the process landscape around it) to be able to respond faster to those signals and deliver the new experiences that their customers need.
In fact, that’s a point strongly established in a recent survey report titled How Enterprises are Steering through Digital Disruption — where leaders attest to the fact that they use digital technologies as commonly for IT management (79 percent) and business process management (60 percent) as they do for customer relationship management (62 percent).
To bring that agenda to fruition, digital organisations leverage their biggest asset — data. The data-driven digital organisation is, therefore, one that has modernised its core to support a seamless data landscape powered by the cloud to scale and by pervasive analytics to democratise consumption.
It has also strengthened its customer and systems connections by using data to inform the improvement and automation of its processes. And is continuously leveraging data to uncover new opportunities to improve its workings as well as deliver unprecedented solutions and experiences.
Frankly, that end-state is more than a leap away for most organisations. And it’s not for want of data, the tools to manipulate it, or respect for its capabilities. And yet, it’s possible to get there in three stages.
Modernise the core
Incumbents, in most industries, haven’t managed to offload their legacy baggage. This is not only preventing them from developing the agility, adaptability and flexibility required in a digital enterprise but more importantly, impeding information and insights from flowing seamlessly across and between enterprise systems.
Therefore, the first step should be to modernise the core by transforming siloed, monolithic systems into an interdependent, intercommunicating landscape that can easily connect with new platform-based components and open source software solutions. This is often achieved by fire landing Application Programming Interfaces (APIs) in the legacy systems to create microservices that enable enterprises to share data. Not just within, but also across an ecosystem.
Take the example of Bud, a plug-and-play financial services platform that integrates around 60 financial or financial technology services using APIs, and is being used by many of the biggest banks around the world. Besides facilitating information sharing and innovation, APIs also allow enterprises to access their partners’ customers and capabilities.
Improve and automate
Data can play a key role in discovering the processes that need to be improved as well as in informing the ways to do so. It also paves the way to automate routine, repetitive, rule-based operations. Artificial intelligence (machine learning) solutions play a big role in working with enterprise data to initiate these cycles of autonomous learning to deliver improvements and pervasive automation of its process landscape.
A potato chip manufacturer exemplifies this in the area of quality control. After replacing human tasters with sensors that could detect various parameters associated with spiciness, it applied algorithms to the data to correlate it with the recipe. Finally, it compared the sensor data with that from physical tasting to build a prediction model for spiciness and taste and succeeded in slashing consumer complaints by 90 percent.
Monetise the biggest asset
A truly digital enterprise creates monetary value for itself from its most valuable asset — data. This means leveraging data to acquire insights into unexplored business opportunities and revenue streams, improve operational efficiencies, and delight customers with new experiences.
Insurance companies have made headway in this area by analysing customer behaviour (driving pattern, for example) and lifestyle data (exercise regimen) gathered from sources such as wearable fitness trackers and vehicle telematics systems to price insurance premiums ‘just right’ for each customer.
And perhaps, best of all, there’s one crucial difference between the data-driven digital organisation and one that is not — where the latter chases data to be able to make informed decisions, the former gets data to automatically and ubiquitously dictate decisions and actions that are best for the enterprise. And that makes all the difference.
The author of the article is executive vice president for the Data & Analytics division at Infosys.