Digital transformation: the what, the why and the how

digital_transformationMy company – 451 Research – defines Digital Transformation as the result of IT innovation that is aligned with and driven by a well-planned business strategy, with the goal of transforming:

  • how organizations serve customers, employees and partners
  • support continuous improvement in business operations
  • disrupt existing businesses and markets
  • invent new businesses and business models

But what’s driving this, and why is it happening now? And what exactly is being transformed? This post attempts to answer those and other questions, based on what we are observing in the market.

Digital transformation is real, and it’s happening, although there is still a very long way to go. We believe it is an inescapable truth that every business is becoming a digital business, controlled by software, which is the manifestation of these digital transformations. Businesses must react, driven by the imperatives of improving intelligence, agility and their customer-centricity. The overall – but seldom-voiced – goal is survival; just ask some of those that succumbed to the transformation of their physical business into a digital one.

Business imperatives

There has to be a specific business reason for any organization to undergo (or at least attempt to) a digital transformation – beyond just survival. We believe there are three main business imperatives: intelligence, agility and customer-centricity.

Intelligence, in this context, means getting insight from data and moving to data-driven decision-making – we believe the organizations that own the data will win over those that don’t, in any field. There’s a reason Alibaba, Amazon, Baidu, Facebook, Google, Netflix and others go to such lengths to understand precisely what you are doing on your laptops, tablets and smartphones. It’s also one of the main reasons Microsoft stretched to $26bn to buy LinkedIn earlier this year. That reason is intelligence – about what your customers or prospects want to buy, where they want to travel, where they want to invest their money, what they like and what they dislike. Swap the word ‘customer’ for ’employee’ or ‘citizen,’ and you see the same imperative to gather such intelligence.

The second imperative is agility. Business agility is essential because digital disruption is coming to your industry (if it hasn’t done so already). When physical assets become digital information, markets experience massive growth and disruption. Such a shift means things become knowable and measurable in ways that were not possible before – and the cost of adding new customers drops dramatically. Look at industries where this has already happened, such as music, photography, mass media, and (most recently) transport and hospitality with the rise of Uber and Airbnb.

The third imperative is customer-centricity. We’ve been around long enough to recall the previous wave of focus on this around the time of the dot-com boom and into the 2000s, where we the customers were supposedly king and organizations had to bend to our will. But in reality, we weren’t, and they didn’t. That’s because customer-facing organizations still held the balance of power in terms of technology. They had the CRM systems, the billing systems and so on, and all the customer had was a web browser mostly on a computer tethered to a desk and an internet connection measured in megabits, rather than megabytes per second.

Things are a lot different this time, mainly because of the smartphone. Now the customer has a lot more power, but so do those selling to us. The age of personalized marketing is upon us, so rather than individuals being grouped into vague demographics, it is now possible to know precisely when you are walking down the aisle of a specific supermarket, or have entered the lobby of a specific hotel. That enables true customer-centricity, and comes with greatly heightened concerns over privacy and data protection, especially in continental Europe. Consider Amazon, which started back in 1995 selling books. As it added increasingly more product categories and eventually third-party sellers, it made sure it kept its customer enveloped in its environment. And now with Amazon Echo, it is listening to customers and gaining deep insight into their lifestyles.

What do you want transformed today?

What exactly is it that is being transformed digitally? It is different at each organization, depending on its maturity, the industry in which it operates, its employees and many other factors. But we see three aspects of an organization being transformed most often: the way it uses information, its business processes and the technology platforms it uses.

Information transformation

Going digital results in an explosion in the amount of data you have. New channels of engagement between customers and organizations have resulted in new sources of information coming into the organization at speeds not seen before. In the past, customer interaction was mostly one-way – from the organization to the customer. Now it is about customer-directed, on-demand two-way engagement anywhere on any device. Customers want to communicate on their terms in their preferred channels. That causes organizations to have to transform the way they handle such information, since having a large call center may not be enough – or even that relevant in the future, given that so much communication will come via social media, in messages or increasingly via video. Add to that the explosion in information from Internet of Things (IoT) devices, and it’s pretty clear that the days of management by gut-feel and hunch are over, and data-driven decision-making is the only way to go.

In fact, research by Erik Brynjolfsson, Lorin Hitt and Heekyung Hellen Kim from MIT and University of Pennsylvania found that companies with data-driven decision environments have 5% higher productivity, 6% higher profit and up to 50% higher market value than other businesses.

But how to achieve it? Help is at hand, in the form of advanced analytics and machine learning. The coming of Total Data, coupled with hardware advances from the chip to the server level, has enabled software applications across the board to take advantage of machine learning to help organization get their arms around all this new data. And it’s a virtuous circle – the more data the algorithm processes, the better they get.

Process transformation

Process transformation is one of the hardest parts of any digital transformation because it requires not only a technical shift, but quite often a cultural one as well. But a broken process with new technology applied to it is still a broken process, so processes must be transformed too. Sometimes this can happen organically and take organizations by surprise. Consider modern collaboration techniques. Whereas just 10 years ago people grappled with early efforts at asynchronous (i.e., team) collaboration and synchronous (i.e., real-time communication) tools, now we have employees using enterprise file-sync and -share tools such as Box, Dropbox and Google Apps for Work, among others, or embracing Slack among their team and asking for IT’s blessing later. These tools, which are driving a particular type of process transformation from the bottom up, share a common set of characteristics. They are focused on collaboration – not just internal, but also with customers, partners and suppliers. A lot of thought has gone into the user experience; they integrate with applications via lightweight APIs and they are mobile-native.

In software development, massive process transformation has been happening for a few years now, and is having a significant effect on the wider organization beyond the development team in the form of DevOps. Many software development teams have moved from so-called waterfall processes to agile methods. Our research shows about 65% of IT decision-makers using agile methods and about 40% adopting DevOps today (VotE Software-Defined Infrastructure Q4 2015).

But agile alone is not enough – even then developers could be developing the wrong application, albeit in an agile way. DevOps is a good example of effective process transformation, whereby teams are involved not just in the planning, coding and build phases, but beyond into testing, release, deployment and operations, thereby having a shared understanding of how software is being used in the organization. DevOps enables organizations to react faster to customers’ demands, so it directly effects – and benefits – the overall customer experience.

Platform transformation

IT priorities are changing as IT moves from being a cost center to being a potential differentiator as software permeates all forms of business. The days of focusing solely on on-premises applications are over, and hybrid cloud environments are becoming the norm. Rather than focusing on managing PCs, the focus is on endpoints – including those owned by the employees. And the explosion in the volume of data has caused IT departments to radically rethink how they store and process information.

Why this is all happening should be fairly apparent by now; it’s because the old-style systems of record IT – such as monolithic ERP and CRM systems that are expensive and time-consuming to modify – are unsuitable to today’s pace of business. Organizations need systems of engagement – tools and applications specifically designed for omnichannel customer interaction – that integrate with the old systems of record, so that customer intelligence isn’t lost, but can be leveraged in ways that enable, rather than inhibit, good customer experience. These systems of engagement need to be able to take advantage of all this additional customer interaction and the data that is generated from it, and keep pace with the smartphone-toting, social media-posting empowered customer.

Because of this need to shift to systems of engagement, platforms need to be transformed. Two crucial developments on this front have been the rise of APIs and microservices. APIs really started taking off with the shift to the cloud, and open APIs have made it much simpler for one application to talk to another one without heavyweight hardwiring. And now smarter APIs are codifying increasingly sophisticated aspects of data integration.

A similarly agile approach to integration is with microservices, a development from service-oriented architectures whereby applications might comprise 20 separate microservices, and a developer can make changes to one microservice without having to worry about breaking the whole application. Clearly defined microservices and API-based integration also allow more advanced technologies – such as machine learning – to be dropped into applications to optimize specific functions more easily. Thus, businesses can be more agile and react more quickly to changes in the market.

This is an edited version of a report that first appeared on 451 Research’s website here. For trial access to 451 Research, click here.

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