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Is data really the new oil fueling digital transformation? Absolutely. A company’s ability to make fast-paced, meaningful decisions in a volatile business environment is key to competitive differentiation. Indeed, industry leading enterprises are using data and analytics to adapt to dynamic market conditions, drive continuous innovation, and accelerate the speed of doing business.

However, many organizations are struggling in their efforts to harness the value of data to aid their transformation efforts. The single most important reason for these failures is their technology-first thought process. They invest in the latest big data and analytics tools, AI and ML algorithms, and visualization technologies, and subsequently determine how to drive adoption.

This approach is flawed. Why?

Technology in and of itself does not provide answers to how businesses must adapt for success in a data-driven future. It’s not enough to have the best tools; organizations need to start with a broader vision built on a foundation of business requirements. Companies that succeed at meeting their analytics objectives let business goals drive the technology, and not the other way around.

The business objectives

To develop an effective and value-generating analytics roadmap, enterprises need to start with their strategic business objectives. These tend to fall into three broad categories:

• Top-line growth – Value derived from better understanding potential target segments to enable greater revenue generation. For example, improved customer satisfaction, creating long-term customer loyalty, etc.
• Cost reduction – Value created by leveraging analytics to identify the cost leaks, such as redundancies and inefficient processes, and trim expenses. For example, minimizing procurement spend, plugging revenue leakage by reducing inventory cost, etc.
• Risk and compliance management – Value gained from monitoring, preparing, and managing risk and compliance on a real-time basis, and anticipating any potential risk-related issues, e.g., fraud detection and monitoring.

The building blocks

After clearly establishing their business objectives, organizations need to make important decisions about four distinct building blocks:

• Data – At the heart of every analytics solution lies data in its raw form. Enterprises need to have a data strategy in place to cope with increasingly large and complex data volumes coming from diverse sources in a wide variety of formats (text, images, audio, video, etc.)
• Technology tools – Core technology tools and platforms for data ingestion, processing, preparation, and visualization are critical. But they cannot be one-off implementations. Enterprises should focus on building integrated technology ecosystems to address immediate, distinct use cases without considering the mid-to long-term creation of sustainable capabilities
• Talent – This requires the creation of competencies around the specific, expected data and analytics capabilities. Given the huge demand/supply gap for data and analytics professionals, particularly data scientists, e-enterprises must proactively and enticingly attract and retain the right talent
• Infrastructure – The focus here is on ensuring that the IT infrastructure can handle the volume, variety, and velocity of the data and the complexity of the analytics.

Once they’ve laid the business objectives and building blocks groundwork, enterprises can develop their digital transformation analytics roadmap. In order to achieve the desired business outcomes from the analytics process, they need to embrace a structured, five-step iterative approach.

Getting this right is critical, and the stakes are high. The organizations that proactively embark on a data-driven digital transformation journey – i.e., every company– will gain a significant competitive advantage. Those that fall behind risk irrelevance.

For more information and insights on how to create a digital transformation analytics roadmap for your business, or to share what you’ve been able to achieve with your roadmap, please contact me at [email protected]

Organizations around the world have invested millions of dollars on digital transformation initiatives. Yet, many IT leaders struggle to measure how well their companies’ digital investments are performing, and others see just a portion of the ROI picture because they only look at one or two parameters.

Here are Everest Group’s two key recommendations for how IT executives should measure digital transformation ROI.

Think and act like a mutual fund manager or venture capitalist

Mutual fund managers and venture capitalists view their investments through a portfolio lens. They look at the portfolio’s overall performance to understand how it is doing, recognize that underperformance of one stock or seed-stage company doesn’t signal overall failure, and make as needed adjustments to individual stocks or investments that are underperforming.

They also make sure their portfolios are comprised of investments with different risk profiles. This is because higher risk projects create the opportunity for higher returns, and deliver a lot of learning take-aways if they fail. Note that when it comes to measuring digital transformation ROI, IT executives need to look at overperformance as well as underperformance. If every project in the portfolio is deemed a success, the organization is likely not pushing the boundaries enough, isn’t innovating enough, and will likely only reap incremental benefits.

Define a clear set of business metrics before you measure

IT executives should define a clear set of business metrics for the digital transformation effort well in advance of the measurement initiative. The metrics should be rooted in a hypothesis about the various impacts the portfolio of projects will likely have on the business. While it can be difficult to link individual projects to outcomes, . Examples of hypotheses include:

• Meeting customer expectation – as customer experience a more digital world, their expectations of how to engage with the enterprise will change. An hypothesis that keeping up with the evolving customer expectations could be that it will increase customer retention and potentially new sales
• Breaking down the silos between IT and the business – secondments between IT and business units can increase and understanding of the links between IT initiatives and business objectives. An hypothesis could be that a greater understanding could enable faster innovation

Many IT executives err by focusing only on cost savings metrics. While the business case for technology projects must include cost savings, organizations that make strategic and operational impact their objective consistently achieve higher returns across all dimensions, including cost. In a recent Everest Group study on next-generation infrastructure, the 88% of the leading enterprises were able to achieve some level of reduction in operating costs from their infrastructure transformation efforts with 65% achieving reductions in excess of 10%. Only 29% of the rest of the study participants were able to achieve savings at that level.

Thus, IT executives should employ metrics that fall into three buckets. This ensures they are looking at the total value of the digital transformation initiative.

• Strategic impact: revenue growth, increasing lifetime value of the customer, reducing customer acquisition costs, accelerating time to market of new products, etc.
• Operational impact: productivity improvements, greater scale, operational efficiencies, etc.
• Cost impact: reduced IT operating costs, reduced business costs, reduced total cost of ownership of IT assets, etc.

Once the measurement effort is underway, IT executives should regularly – quarterly tends to work best – look at every project in the portfolio for signs that it is delivering the anticipated type of impact, or is instead contributing in an unintended manner. This gives them the opportunity to determine if adjustments need to be made to how the project is being executed, if business requirements have changed (e.g. shifting customer demands, new competitive threat, etc.), if they have gleaned sufficient learning from the project (e.g. process optimization, technical limitations, success requirements, etc.), or to terminate the project it if they conclude it will not deliver results.

Please reach out to me directly at [email protected] to discuss how to measure the ROI of your organization’s digital transformation initiatives.