Analytics & Insights
Key Considerations for Selecting Data Governance Tools
Done right, data governance can maximize the business value of your dataRead More
Author: Ian Foley
The calendar has flipped to 2021 and with it comes a new year of opportunities for growth and innovation. Specifically, the new year is a great time to take inventory of your organization’s Data and Analytics (D&A) capabilities and plan for the next evolution. Modern businesses require constant information to thrive. Thus challenging D&A teams to be responsive and support the ever-growing demands for information. Taking a thoughtful approach to evolution can help provide the right technology, processes, and people to provide powerful organizational capabilities. I’ll detail some of the hallmarks of each stage and share some actions you can take to continue evolving.
Through my experience, I have seen organizations mature their Data and Analytics capabilities following a fairly similar cadence. With each evolution, organizations realize an increase in value from their investments in Data and Analytics. In most cases, I have observed three stages of evolution:
Initial forays into Data and Analytics prove business value opportunities
The Initial Successes stage is usually a start-up effort for an entire organization or within a specific department. These initial efforts tend to be focused on a few key use cases. For example, a finance department creates a data store to consolidate critical financial and accounting data from multiple, disparate sources. This increases visibility to more accurately forecast and realize actuals with minimal variance, which drives more efficient use of resources.
This stage typically involves adopting new technology, but that technology is typically not procured with the intent of supporting a broader Data and Analytics capability. This stage can be really powerful in that stakeholders gain an understanding of the business value of better insights and they always want more.
To move beyond this stage and capitalize on the initial “win”, consider the following next steps:
Cross-organizational alignment drives increased capabilities and collaboration among departments.
The Distributed and Collaborative stage typically involves building on initial successes to create centralized capabilities to empower the broader organization. Centralization inherently involves more stakeholders with differing needs and also identifies crossover data. A central data store is created by taking into account shared data elements while enabling flexibility for unique uses of data across departments. At this point, it is critical to establish sources of truth and agreed-upon data definitions. In addition, data champions exist in IT and as citizen data users in the business.
Key steps for evolving beyond the Distributive and Collaborative stage include:
Advanced data capabilities integrated into every facet of your organization drive significant value and competitive advantage.
Just as in nature, evolution of your organization’s Data and Analytics capability is never complete. Over time, evolution becomes innate to your organization enabling your capabilities to constantly incorporate and react to dynamic changes in data, new technologies, and competitive business forces. At this state, all members of the business rely on insights and visibility (the desired “data-driven culture”) and advocate for the continued investment and strategic importance of Data and Analytics capabilities. Most importantly, this stage requires constant innovation, speed, and flexibility.
Keys to continued success in this stage are:
Powerful Data and Analytics capabilities are table stakes to compete in the modern business world. With thoughtful and committed leadership, data will become a key engine of growth for your organization. A change of the calendar can be just another season of business, or it can be a launching point for evolution. Why not make a business resolution to double-down on Data and Analytics?