Businesses were starting to prioritize a shift toward data-driven decision-making even before the pandemic; the ongoing economic fallout has only increased its urgency.
Given the attention awarded the “data-powered enterprise” of the future and all the success stories around Data & Analytics (D&A) adoption, one might expect to see enterprises proclaiming continued revenue growth, new revenue models, consistent cost optimization, dramatic operational efficiency, and drastic improvements in customer satisfaction. And indeed, D&A adopters with a resilient, scalable, and flexible modern data architecture in place are realizing strong results. But most organizations are finding the journey to becoming truly data-driven awfully slow.
Enterprise D&A initiatives fail to realize full benefits for a variety of reasons, including misaligned business and technology objectives, incorrect data monetization expectations, incoherent infrastructure and tools selection, inflexible operating models, lack of a compliance-based data governance system, and lack of adequate skills for transformation.
An ideal D&A strategy aligns priorities across business and technology to create an enterprise-wide environment of innovation to achieve optimized outcomes. When done right, it has the potential to rapidly transform both internal and external stakeholders’ experiences. The trick is to harness data from multiple sources across the data landscape, harmonize and transform it into an authentic state by utilizing emerging D&A technologies, and ultimately empower business units to substantially improve the quality of strategic decision-making at scale.
Everest Group recommends the following five commandments for enterprises to formulate an effective D&A strategy:
How has your D&A journey been so far? What challenges have you faced, and what lessons have you learned? To exchange perspectives, please feel free to reach out to [email protected] or [email protected].
Companies’ investments in digital platforms are becoming pervasive, thus moving businesses into a new era. They first moved from a functional orientation to a process orientation and are now fundamentally shifting to a platform orientation. Digital platforms are already changing companies, whether they recognize it or not. The implications of platform thinking are very deep. Data are the lifeblood of a digital platform. But the implications of what companies must do to be able to apply their data in a timely way is significant.