A Changing Landscape
In the modern hyper-competitive landscape, the ability to proactively anticipate trends and make timely, well-informed decisions is more important than ever. Advancements in data management, cloud computing, and AI technologies have unlocked new methods of delivering actionable insights to improve decision making. These trends, coupled with an exponential increase in the volume and richness of data available, present opportunities to gain a competitive edge. Terms like digital transformation, self-service BI, and prescriptive analytics have become ubiquitous, but only a small sect of organizations are successfully capitalizing on these trends. With the rapid pace of innovation and a difficult labor market, successfully garnering the talent needed to advance data & analytics maturity is no easy feat. Those who successfully navigate the labyrinth are rewarded handsomely, but speed is of the essence.
Mounting Competition
As leading enterprises brought their data to life through sweeping transformation initiatives, competitors quickly took notice. These innovators monitor enterprise performance in real time, anticipate the future with unprecedented accuracy, and unlock hidden insights not available through more traditional means of analysis. These advantages allow data-driven organizations to report over double the revenue growth of their peers, measured over the past three years. The fact that each dollar spent on business analytics implementations typically returns five sheds light on why such efforts are pursued so aggressively. And while every organization must advance data & analytics initiatives, doing so efficiently is more nuanced.
Sparking and Sustaining Innovation
At this point, most organizations are exploring analytics tools and techniques. However, they typically do so without sufficient upgrades to their data management infrastructure and without a comprehensive strategy to ensure measurable progress towards business goals. Part of the problem is a fragmented approach, with more progressive teams driving change without support from the broader enterprise, leading to a host of issues including an erosion of trust in analytics. Instead of taking an ad-hoc approach, data-driven organizations begin with overarching business goals and asking the right questions. How do we improve the accuracy of our financial forecasting? How do we react to supply chain complications? How do we improve customer loyalty?
From there, innovators identify the data sources needed to answer these pointed questions. Once this process is set in motion, effective change management becomes critical. Success looks like incremental change, with rapid prototyping leading to broader organizational change. Such an approach maximizes speed to value and ensures that employees are comfortable embedding new tools into their decision-making processes. With a pragmatic strategy in place, garnering talent becomes a top priority.
Talent Tribulations
Having the right goals, asking the right questions, and crafting the right strategy collectively lay the foundation for companywide data-driven decisions. But the transformation of potential into progress comes to a grinding halt without the right talent. And in the current labor market, finding adequate talent to keep up with the appetite for analytics is no easy feat. Add to that the lag time of onboarding and training (it typically takes a new analyst 18 months to generate a return on investment), and talent becomes the most impactful barrier to achieving speed to value. While there is long-term value in building an internal team to advance data & analytics initiatives, most data-driven organizations leverage trusted partners for support. With strategic guidance, on-demand technical talent, and proven methodologies, consultants accelerate the data & analytics transformation journey, all while helping upskill internal teams and setting the groundwork for predictive and prescriptive insights.
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