Data-Driven Digital Transformation: Filling the Gaps between Strategy and Execution

A new IDG survey underscores the challenges CIOs face balancing strategy and execution with their data-driven initiatives

IT leaders believe they have made significant progress mapping out next-generation data strategies. But selling the strategy to business leaders, translating policy into projects, and effectively executing on the details of specific initiatives remain barriers to data-driven digital transformation.

According to an exclusive IDG QuickPulse survey, 76% of IT decision-makers say their organization has been extremely or very effective at mapping out a data strategy. That positive view, however, is shared by just 50% of business decision-makers; nearly one in five business respondents describe their company’s data strategy as not very effective.

This perception gap indicates that some CIOs still have not clearly articulated the business benefits of their data strategies to non-IT stakeholders. Or they have not sufficiently aligned their investment priorities with the priorities of their business counterparts.

That’s a missed opportunity, given that many organizations are already seeing quantifiable benefits as their data strategies take shape. Nearly half (48%) of respondents in the IDG QuickPulse survey say they are seeing improved visibility into customer information and behavior, 42% have successfully reduced costs and increased operational efficiencies, and 40% report improved internal decision making.

The results align with growing investment: The just-released 2018 State of the CIO survey finds that one-third of companies are channeling the largest portion of their IT spend to data management and business analytics tools.

Looking ahead, many organizations remain focused on capturing internal benefits. According to the QuickPulse survey, the top four data strategy priorities for the year ahead are:

  • Maintaining compliance with government and industry regulations (78%)
  • Improving productivity (78%)
  • Improving internal decision making (72%)
  • Reducing costs and increasing operational efficiencies (72%).

Yet while organizations are achieving some clarity on direction, challenges remain when it comes to execution. The top five obstacles are:

  • Scoping data strategy into prioritized, phased projects (36%)
  • Skill gaps (30%)
  • Budget constraints (28%)
  • Unclear organizational roles and responsibilities (28%)
  • A corporate culture hesitant to embrace new ways of doing business (28%).

These challenges underscore the fact that, in this time of accelerated change, people and processes often pose greater challenges than the technology itself to successful data-driven digital transformation.

“Technology can overcome the making-it-possible part, but cultural change is really required to overcome the barriers to making it happen and to obtain end-to-end value from whatever the initiative is,” Graeme Thompson, CIO and senior vice president at Informatica, explains in the Big Pivot podcast episode, “So You Have Big Data: Now What?”

AI and Machine Learning: Transformation Accelerant

Technology advances are accelerating the “making-it-possible” part. In particular, artificial intelligence and machine learning capabilities hold promise for extracting more value from data strategies.

More than two-thirds (68%) of respondents to the IDG survey say AI has changed or will change their data strategy. Forty-four percent of respondents see AI having the greatest potential as a means to facilitate operations in areas such as system maintenance, troubleshooting, and optimization. Other areas where AI is expected to have significant impact include security (34%), notably threat analytics, intrusion detection, and prevention; and user productivity (34%), by enabling easier and faster data visualization, for example.

Data-driven strategies in general, and AI specifically, still have much untapped potential to impact the business. Fewer than 3 in 10 organizations in the QuickPulse survey, for example, are capturing quantifiable, data-driven benefits in areas such as identifying new market opportunities (28%), optimizing the supply chain and distribution channels (26%), and enabling a multi- or omni-channel experience for customers (24%). Companies already working with AI view the technology as a key enabler of sales/marketing opportunities, such as increased cross-selling or personalization. These are the types of positive business outcomes that could bridge the strategy gap between IT and the business.  

Translating Vision to Value

How can CIOs expand the reach of their data strategies to begin capturing more of this outward-facing business value? For one thing, they should redouble their efforts to help business users gain an understanding of all the organization’s data – not just the data that individual teams own – and identify concrete examples of the positive business outcomes that data initiatives can deliver.

“A vital part of the CIO’s job is to help their CEO and the management team think about how a desired outcome may depend upon changes across the entire system—not just within a functional area,” Thompson says in another Big Pivot podcast episode, “Digital Transformation: From Vision to Value.” “Participating in management team and board meetings has given me the perspective I need to read between the lines and ensure the IT team is focused on the right outcomes. Being part of the discussion when decisions are being made helps connect the dots for everybody across the enterprise.”

Equipped with that perspective, CIOs can continue to put processes and tools in place that make analytics accessible to business users while ensuring that IT doesn’t serve as a roadblock to data-driven insights.

“The business user knows more about their data than anyone in IT,” Thompson says. “IT should be focused on making sure data is available from the right applications, making sure it’s a trusted source of truth and [is] secure, providing two or three analytics and data visualizations on top, and training and enabling users so they can have at it.”

Recruiting talent or retraining workers with the right skills is another important lever to move data strategy into project implementation. Business intelligence and data analytics skills is one of the top areas where organizations are struggling to find talent, according to the 2018 State of the CIO survey.

In addition to sourcing external talent, CIOs should identify high-performing employees with traditional data warehouse skills and retrain them for the big data needs of today. Aligning with technology suppliers that have large communities of partners and professional services organizations can also help mitigate the skills challenge.

Successful data-driven digital transformation requires equal parts strategy and execution. Both require a lot of heavy lifting, but with emerging technologies like AI and the right mix of cultural change, CIOs can lead their organizations on a successful journey.

Listen to the full podcast episodes with Graeme Thompson:

To learn more about data-driven digital transformation strategy, visit https://www.informatica.com/CIO.