Businesses looking to adopt a data-driven approach tend to focus first on the most innovative technology. Technology is however only one piece of the puzzle. The success of a digital transformation depends on driving change throughout the organization and drawing up a plan. It takes a careful strategy to judge what changes are needed from a business perspective – and what technological solutions might help to drive these changes. Implementing this strategy requires a consistent roadmap that carefully aligns the various components of the plan. Most importantly: approach your change value-driven, instead of technology- or data-driven.

Technology virtually always plays a supporting role, says ORTEC’s Chief Technology & Innovation Officer Patrick Hennen. “At most, you can use very innovative technology as a driver, but even then, you shouldn’t want to use it at all costs. The technology must create value for the business; business should be able to do something with the technology that was not possible before. Ultimately, technology is an enabler, not an end in itself.” Hennen has identified three closely connected trends that could play a significant role in the future: elastic cloud computing, the rapid development of applied mathematics, such as Artificial Intelligence (AI), and a veritable data explosion. Better maths, significantly greater computing power, and increasing quantities of data can be combined to solve bigger problems. What’s more, you can do so quicker, more accurately and in a more integrated fashion, which will generally lead to better decisions. As global digitization continues to ramp up, it makes sense that more and more businesses are looking to get involved. “However, it can be dangerous to take a solely technological approach and neglect the human and organizational aspects of the business.”

According to Rianne Langenberg, Business Strategist at ORTEC, companies looking to adopt a data-driven approach in one fell swoop often fall into this trap of putting data and technology first. This can sometimes be refreshing, but it is a lot better to first determine what you want to do with this data and technology. “Digitization is not only about boosting efficiency, for instance, lowering the average handling time of your customer service department”, Langenberg explains. “It’s mainly about becoming smarter: making sure your customer service agents know exactly who to call each day to ensure the company keeps gaining and retaining customers. While part of digitization is about automating processes, the data-driven part is all about getting smarter.”

Digitization should, fundamentally, be based on your business, not the other way around. What challenges and opportunities does your organization face? What is the market like? You have to think how harnessing data will add value. It all starts with the question: why does my organization aspire to become data driven? “This is an important question to ask and answer in order to get the entire organization on board”, says Langenberg. You need to tell people exactly what they can expect, because “shifting to a data-driven approach” is a very wide-ranging goal. What is the biggest change you want to make? Are you looking to catch up with the market or lead the way? What time frame have you set for achieving that goal? What is your strategy? Will it be a strategic project fully sponsored by the Board of Directors, a change program, or will you set up a center of excellence first? These are the types of questions you need to answer first. At this stage, you need to create a small plan for change: why, who, what, where, and so on. “There’s no one-size-fits-all solution that works for every organization, but there are plenty of best practices to guide you. The key to success is the awareness that digital transformation is as much about organizational change as it is about technology.”

The ultimate goal is for analytics to be an integral part of the organization. Organizations used to adopt a functional approach in structuring their organizations. “We see that they are now moving to do so based on the product or service they offer. This means the various functional expertise fields will work much more closely together – which is exactly what a data-driven approach is all about. You can get a lot more mileage out of your customer journey by looking at the journey as a whole, and digitalization has made that a lot easier.”
Though to group on a product-oriented level, roles need to be fully mature. If a company is only just starting to get traction in data analysis, it should not hire five analysts and assign them to five different sections of the organization. “Those analysts first need to learn to work together and to apply the same set of standards. We therefore advise customers to start with one core team, for example in the form of a center of excellence, and to do so in a central location rather than in the IT department. The idea is to have all data analysts temporarily work in the same location because their focus should be on sharing knowledge, building expertise, and establishing standards. Next, you can reassign those data analysts within the organization, leaving just an expertise center with a limited number of roles.”

To sum up: a good plan is based on the customers’ needs and considers which organizational changes are necessary for the successful implementation of the plan.

One of those changes is learning new data skills. Data skills are becoming more and more important in organizations - not just for the data science department, but also for employees involved in the core business. This requires a shift. You can teach employees new skills with an educational program, but to give large numbers of employees a relevant, useful experience, such a program will have to be tailored to the organization in question. Robert Monné, manager of The Analytics Academy, recommends a mix of online and offline learning interventions. “The content has to be adapted to your employees and their daily jobs.” The employees of an organization can often be categorized into different groups. After all, IT experts need a different set of skills than customer service employees. “Offering a tailored online or offline learning program to each specific group of employees maximizes adoption. You can offer theory and exercises in a learning environment, before encouraging employees to apply their newfound knowledge in their daily jobs. The results can then be discussed with peers or internal experts.” On top of that, employees will have to be coached and the organization will have to internally communicate positively about new technologies and applications. That is how you offer your employees the right toolset, skillset ánd mindset.

These new skill sets should enable employees to generate added value for customers. According to Erica D’Acunto, Innovation Lead at ORTEC, every company should start with market research first. “This will highlight the things that are going right and those areas that need improvement. It also provides valuable information about your customers’ needs. Often, existing market research will already offer valuable insights.” In addition to market research, talking to your customers is a great way to learn more about what they want to achieve, and what triggers them. On top of that, businesses will often have their own ideas about which problems they consider worth solving to make a difference for their customers. Only when you know what you want to solve, you can start thinking about a solution. Sometimes, companies focus too little on answering the questions that really matter, says D’Acunto. "They lose sight of what's important. Some businesses’ main reason for innovating is a desire to show the world that they, too, are working with machine learning and AI, without actually having identified their real challenges and questions. The fact that another company has a chatbot is not a valid reason for wanting one yourself.”

Every year, Vlerick Business School studies 52 major Dutch companies and their digital transformation. Their research has shown that these businesses value a culture in which experiments, and possibly failures, are accepted and encouraged. They even consider it a key success factor for digital transformations. This attitude, however, does not appear to be pervasive. Apart from these leading companies, very few businesses have shown themselves willing to reveal their digital failures. Frontrunners in particular tend to organize internal incubators and pitch competitions in an attempt to create an open, safe corporate culture. Besides, these businesses do share data and experiences with failed products and services within the company, such as a lack of integration with current business processes, great features for which customers simply did not want to pay, the lack of a solid earnings model, and initiatives that have failed from the start. According to Rianne Langenberg, it’s not as though you need only that one idea which should be an overnight, slam-dunk success: what you need to do is abide by the ‘fail fast’ principle. “Instead of just soldiering on for two years to try turning a low-potential use case into a success, you’re better off dropping it and starting a new initiative after one month. This sometimes requires a fundamental cultural change if the belief that ‘failure is not an option’ has always been part of the company’s DNA. It’s actually better to think in terms of ‘learn fast’ rather than ‘fail fast,’ because what matters is that a business can quickly identify what does and doesn’t add value. Also, be sure to celebrate small wins: people will have a very hard time committing to a change program for three years if you only get to celebrate at the very end.”

“Businesses must pay attention to their customers’ needs, the education and training of employees and cultural change, all coming together in a holistic digital strategy that is crucial for a well-functioning data-driven organization.”