In the modern landscape, organizations of nearly every size and type are exploring the applications of data and analytics to their business in order to enhance decision-making, mitigate risks, and unlock new opportunities for efficiency and growth. Analytics success, however, has proven elusive for many. With new solutions and technologies hitting the market every day, it’s easy to try to lean on a quick-fix tool or software but sustainable, value-driven, and impactful analytics success requires an understanding of the practical drivers within your business. Below, we’re covering those drivers, why they matter, and how your business can create an ecosystem that enables analytics success in 2019.
1. Focus on Value-Driven Analytics
The most helpful mindset shift your team can make in working toward a stronger analytics function is to start thinking about analytics projects based on the value they will add to your business, rather than buying a tool or a data set to ‘do analytics’. There is no intrinsic value in a dataset, or even in insights; the value lies in what you can do with that data and what action you can take based on those insights.
Start by defining business value propositions outlining a specific question that, when answered, will lead to defined actions that will drive a quantifiable and measurable business outcome. The next step is to score these propositions on various dimensions like time to value, alignment with strategy and goals, and feasibility. Focusing on expected value upfront will help limit lower value, exploratory analytics.
2. Activating Analytics Across the Organization
Organizations are investing in growing analytics capabilities and adoption broadly by moving it out of small specialized groups to every corner of the organization. Many activation programs include broad-based analytics training, executive coaching, and providing next generation analytical tools.
In the process, new roles and capabilities are also being developed like data engineering and/or analytics translators that help streamline the analytics process. Additionally, well rounded programs will include organization-wide analytics process training that includes use case identification, project scoring, project execution, and long-term analytics product support. To make it all stick, organizations are launching mini-projects and hackathons guided by a data science team so groups can begin to practice and leverage their new found skills while delivering value back to the organization.
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Coauthor and contributions by Tim Plummer and Elise Watson