In Part 1 of this series, we talked about the first step in establishing an analytics capability within your organization – building a team with the appropriate skillset and effective leadership to provide a solid analytical foundation. The next steps involve identifying opportunities where this team would be most effective and ensuring processes are in place to extract and communicate analytical value. We suggest applying a concept that drives our approach to client engagements: identify and act on “Why” the organization is trying to solve the problem.
Grab the low hanging fruit
Take inventory of your organization’s current analytics challenges and opportunities. What business opportunity provides the best forum for showcasing your organization’s existing analytical capabilities? Where can you create the most value, while absorbing the least amount of risk? Most importantly, what can be accomplished today?
Selecting a decision making process or project that is currently not leveraging analytical insight, but at the same time offers minimal risk of failure, is key. The opportunity to obtain a quick win can be a powerful motivator to your analytics team, as it provides context to the team’s efforts as well as the satisfaction of positively impacting the strategic drivers of the organization. While we want to push for enterprise wide adoption of analytical enablers in all decision making processes, we recommend approaching this decision with caution. Objectively evaluate the available opportunities and select the one that best satisfies an organizational need while also promoting your strengths as a team. Use a prescribed set of criteria centered on delivery capabilities, risk and the team’s understanding of why the process or project is organizationally significant. Successfully demonstrating the value of analytics will build momentum and generate enthusiasm throughout your organization, thus it is critical that the selection process yields the most effective showcase possible.
Speaking the language of business value
What good is your analytical insight if it is never injected into a decision making process? It is not enough to simply complete your analysis and throw it over the proverbial fence for business consumption. In many SEI engagements, the importance of conveying the data in an effective way is as crucial as the data architecture. Be sure to present the analysis through the lens of business value, with a focus on why the data collection and analytics effort is important and how it drives organizational value. Every successful analytics team we’ve encountered illustrates the value of the data and how it enhances the business’s decision making abilities.
Viva la analytics revolution!
Let’s review the steps to begin the analytical revolution in your organization:
- Find your analytical champion
- Select the right opportunity to demonstrate the value of analytics to your organization
- Develop and refine the roles and competencies necessary to effectively sustain an analytics team
- Learn how to communicate the value of analytical insights to the business with a focus on why these insights lead to enhanced organizational decision making capabilities.
As the successes build, so does the analytics team’s credibility and their business partner’s trust in both the data analysis and the team’s competency. To sustain this momentum, you must continuously evaluate your organization’s decision making processes that could be enhanced through the use of analytics. Take on realistic, achievable, and time bound opportunities to enable frequent success. Establish the clear expectation that the analytics team will provide evidence based, data supported, and objective recommendations in their analysis.
Will your organization undergo an overnight analytical metamorphosis? Surely not. You will have to overcome cultural, technological, and process related hurdles to establish a sustainable foundation. Each success will build on this foundation, slowly transforming your organization from one that relies on “gut” feel and loosely attributed data to one that leverages objective, actionable analysis in its every day decision making processes.
