Analytics is on the Rise and on the Agenda

The adoption of analytics by businesses and organizations has been surging in recent years, particularly since the appearance of Competing on Analytics: the New Science of Winning by Thomas H. Davenport and Jeanne G. Harris in 2007. Research from MIT and Capgemini showed that skill gaps are hindrance to drive digital transformation. One of the four capabilities needed are those regarding analytics.

As the pace of change drives businesses to be more nimble, and as enterprises become more skilled in the advanced application of analytics, it is unsurprising to see more than twice as many organizations reporting that analytics is being used as a primarily predictive tool today than in 2009. Recent research by Accenture gives us an ‘update’ on the state of analytics.

Practitioners must move beyond traditional sources of data in order to seize the opportunities for new insights being created by new sources of data such as these:

  • Text analytics from social media and digital interactions
  • Voice analytics from call center interactions
  • Monitoring the customer experience in real time using web analytics
  • Seeing things from the sky (geospatial data)
  • Understanding patterns of physical movement from geo-location data
  • Monitoring movement (visual data)
  • Understanding attitudes/behavior (customer, employee)

The following insight offers us a peak into a tough challenge, a shift in decision-making that is based on intuition and personal experience to a more data-driven one.

Analytics in the organization

Accenture Analytics believes that having the right people focused on the right set of problems is one of the most important components of an effective analytical capability. Companies need to have deep functional skills and deep industry context, together with an optimal sourcing strategy and structure for accessing scarce skills as needed.

When analytics does not work as expected for a company, it is helpful to look for the source of the problem in the three most common reasons why:

  1. Measuring the Wrong Metrics: Companies are measuring the wrong things or have gaps in the way they are measuring (e.g. around the customer experience).
  2. Flawed Insights: Users are not identifying and validating cross-functionally the correct insights and associated actions suggested.
  3. Faulty Execution: Companies fail to embed analytical insights in key decision processes across the enterprise so that analytics capabilities are linked to business outcomes.

According to Accenture, the smartest businesses are creating a virtuous feedback loop that lets them

collect data, analyze the data, harvest insights and then make decisions and respond in an increasingly agile style (see figure below).

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