Big data and analytics go hand-in-hand with digital transformation initiatives, but consulting and services firm HCL Technologies recently found that many companies are not as far along with digital transformation efforts as they hoped.

Anand Birje, corporate vice president and head of HCL’s digital and analytics practice, believes that other factors are also contributing to the digital transformation challenge.

“Over the past four or five years, enterprises were pushed hard to do anything in the field of analytics, big data and digital transformation,” said Birje. “They were being pushed because there was this fear about what their competitors might be doing, so there was this feeling that they had to do something digital.”

The result was an avalanche of small proof of concept (POC) projects throughout organizations that were driven by the C-suite. “Organizations literally became ‘proof of concept labs,'” said Birje. “There were pockets of POCs all over the enterprise that included digital technologies, analytics, structured and unstructured data–and that changed everything from business processes to customer engagement. There were data science centers, innovation centers and experimental POCs where no one was certain whether they would prove out.”

What was lacking, according to Birje, was board-level knowledge about the different digital projects–and expectations for the business value these projects would deliver.

Organizations weren’t necessarily wrong in pursuing big data, analytics and digital transformation as a series of proof of concept projects, and there are still many recommendations that they should. However, many companies got so deeply engaged in new technologies and projects that they forgot the ultimate business values they were seeking.

“This is to be expected when organizations are experimenting with new technologies where they have little experience,” said Birje. “But what is different now is that a lot of this early experimentation is behind most companies. Now they are entering a natural maturity phase with big data, analytics and digital transformation where they must look at what they do much more strategically.”

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What should companies do now?

Recognize that analytics and digital transformation is a cultural change.

“You are not just plugging in analytics, big data, and digital technologies,” said Birje. “You are changing the way you work and the culture of your business.” This means that your organizational structure might have to change with digitalization. For employees, it could mean new reporting relationships, concerns over new job roles, and anxiety about whether they can do them. HR should be an integral part of the transition process, providing training and support for those involved in digital transformation efforts.

Think more long-term about digital transformation projects.

“A major bank was using an agile and scrum approach for digital transformation POCs that were being done in eight to 12 week timeframes,” said Birje. “There were numerous product release cycles, users didn’t want to wait for products to be final before they started working with them, and it got confusing.” Instead, organizations need to take more time with these projects. What are the projects supposed to accomplish? How do they fit into a linear succession of deliverables that comprise the company’s overall digital strategy? “To do this, companies need to think more about projects becoming part of long range programs, and less about individual proof of concepts being ends in themselves,” said Birje.

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Think about the experiences your company is delivering to end users.

Is the new digital application providing service value to your end users? Does the app have stickiness that makes users want to keep using it?

“Several years ago, a large telecom was trying to deploy a mobile digital application for teenage users, but the app wasn’t integrated with the company’s billing system,” said Birje. It was a frontend app without backend integration, and it didn’t satisfy the customer.”

Look at your business value chain.

Companies building their longer term analytics, big data and digital transformation strategies should develop a business value chain that defines what they want to accomplish. This process involves defining a value chain of functionality for the business that achieves key goals, and an asset value chain that assures that the hardware, software and person power you are investing is being fully utilized.

“The final message for companies is that the hype phase of big data, analytics, and digital transformation is over,” said Birje. “It’s now time to align project initiatives with a long term strategic plan for the business so there is absolute strategic clarity.”

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