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How to ensure the ROI of your analytics implementation

Sajid Usman, global managing director for technology, Accenture Analytics | Oct. 16, 2013
Although companies are increasingly investing in analytic capabilities, many fail to see a positive impact on the bottom-line. The good news is proven tactics exist to help businesses get it right. Here's how to overcome the five main challenges to achieving ROI from an analytics implementation.

When narrowing down specific KPIs to measure, these questions should be top of mind for all industries:" What matters most to the business?" What would be achieved by tracking this KPI?" What will its impact be?

Establishing the right set of KPIs is important as they set the stage for faster and better decision-making. Once determined, it's also important to communicate the fine-tuned KPIs with colleagues who are also involved in tracking performance within the organization to ensure a constant is known and followed.  

Challenge #3: Limiting analytics to traditional dataSolution: Capitalize on new sources of data
Companies tend to stick to the mantra "tried and true" as a basis for gathering reliable sources of data to analyze. Businesses should move beyond traditional structured data types and chase the new opportunities that could be created by tapping new sources of unstructured and semi-structured data such as: social media, voice, web, geospatial data, geo-location data, visual data, and behavioral data. Additional insights can also be created from looking at data outside of a company's walls and into third-party external data and public data.

Various industries have already benefited from this approach. For instance, seed suppliers are now using new satellite data to understand the impact of soil temperature on the growing of seeds.The ever-growing volume and variety of data can be overwhelming for businesses. In fact, a recent showed only 39% of organizations say the data they generate is relevant to their business strategies, and only 50% say their data is consistent, accurate, formatted and complete.

To manage the expanded data sets, businesses should only analyze the data that matters for your decision-making task. This can be done by reverse engineering determining the desired outcome first, and then backtracking to identify the data sets needed to find the insights that will support the outcome. Adopting data discovery technologies is also an option as they allow for less-stress data experimentation. Both approaches can help businesses massage the data mountains down to molehills so the impactful data can be found and applied for the business.

Challenge #4: Analytics in the rearview-mirrorSolution: Look through the windshield via advanced analytics
Historically businesses have looked in the rearview mirror, analyzing historical data, believing it is critical for operations. Over the past few years, a shift has occurred and businesses are now starting to change focus and look through the windshield to figure out their destination and where they're headed.  This can be accomplished through advanced analytics.

Businesses now have the opportunity to hone their functional analytic approach and incorporate advanced components for greater insights. Why? Today's analytics technology, talent and culture have the capabilities to get together on this effort. It's important to keep in mind, though, that exploring advanced analytics and its insights is only a first step for businesses. Placing action behind the insights is the necessary next step that will enable a business to truly take advantage of analytics, where a competitive advantage can be generated and analytics ROI be achieved.

 

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