In the last decade, “analytics” as a craft and discipline has gained increasing attention. Once an esoteric set of techniques practiced by professional statisticians and quantitative analysts, today’s analytics must be understandable and usable by the masses.
In the last decade, “analytics” as a craft and discipline has gained increasing attention. Once an esoteric set of techniques practiced by professional statisticians and quantitative analysts, today’s analytics must be understandable and usable by the masses. Analytics has expanded beyond data manipulation to encompass a broader range of activities from harnessing and storing data to applying algorithms that tease out nuggets of insight—a prospect that is attracting interest from most businesses.

Can we benefit from analytics?

Most certainly! We experience the benefits every single day. For instance, when Netflix recommends shows and movies for us based upon our viewing history and demographics, it uses analytics. On the other side, Uber, a mobile application that connects passengers with drivers of vehicles for hire, uses real time analytics to determine customer demand, and during peak times introduces “surge” pricing – increased fares that the market can support due to the limited supply at a given time.  Even though Uber has recently come under fire for these practices, they are harnessing the power of analytics as part of a core business model.

Before an organization can start reaping the benefits from analytics, it must understand the challenges that come with integrating analytics throughout your enterprise and realize that the foundation of robust analytics is the availability of high quality data. Since data is not the fundamental focus of analytics, the discussion that follows assumes you already have a robust master data management framework in place.

On a scale from Developing-Foundational-Advanced-Optimal (i.e., the amount of value gained from analytics), most enterprises typically fall closer to the low-end (i.e., Developing). Many have invested in some type of ongoing reporting or business intelligence solution and have the ability to do some manual query and data analysis. But even if these capabilities exist, companies still struggle to keep up with increasing data volume, reporting complexity, and increasing end-user demands.

Where do we begin?
To successfully incorporate analytics into your company’s DNA and increase your analytics maturity, you will need to identify gaps in your organization’s analytics readiness. A good framework for assessing your readiness is to look at your people, process, and technology.

People. Three tiers of employees will help shape your path to analytics integration. A people assessment begins by looking at the extent to which the organization’s leadership (tier one) understands the benefits and limits of analytics as well as leadership’s commitment to the advancement and use of analytics throughout the organization. The next tier includes analytics professionals—a critical middle layer of individuals who have very strong quantitative fundamentals, possess strong business acumen, and are exceptional project and program managers. They are especially valuable in developing analytics methodologies to address business questions. The third tier is a team of analysts. Analysts possess a rigorous quantitative background, but with little or no industry experience. Analyst skills can vary greatly from novices to expert modelers.

Process. Start by asking these questions: Do you have a documented process for sharing analytic results with your business stakeholders to support decision making?  Are reports sent to a distribution list on a regular basis with little narrative or insight, or is the data shared in a portal where different users access their own reports or insights?  Do users have access to interactive reports and deliverables to further explore the insights?  What about alerts and exceptions?  Is there a process to quickly notify business stakeholders when key indicators change and an action or intervention is needed?  Finally, do analytic results flow vertically, horizontally, or both through your organization?

The bottom line is that it is critical to understand how your users of analytics currently receive insights and take action. This will help you determine how best to evolve your analytics functions to drive the most business value.

Technology. Enterprise technology is an integral part of any business. So the best way to embed analytics into your organization is through already existing technologies and allied support systems that enable tasks from data preparation to insights. Ideally, this happens within a single tool or within a single platform; however, it can be achieved with a combination of tools as long as they can be easily integrated. While proprietary tools have historically provided best in class analytics technologies, big data and open-source tools have matured to deliver world-class analytics at much lower costs.

Business today is increasingly driven by analytics rather than by intuition.  The most successful or disruptive businesses have placed analytics-driven decision-making at the core of their enterprise. More than a function, analytics defines a culture of thinking and problem solving that is quite different from the culture of other disciplines. To paraphrase Aristotle, our habits make us who we are, and companies who embed analytics decision-making into the core of their business are able to improve efficiencies, predict customer behaviors, mitigate risk and reduce costs.

For more information about West Monroe Partners’ advanced analytics capabilities, please contact Ramani Natarajan at rnatarajan@westmonroepartners.com.