Three steps to Driving Customer Analytical Success


There are three simple steps to ensure Customer Analytics drive commercial success in an organisation

  1. Strive for excellence in customer analytics matters (vs merely good average).
  2. Establish a culture that values fact-based decision making and analytics
  3. Secure senior management involvement in customer analytics.
  1. Strive for excellence in customer analytics matters (as opposed to a merely good average). More than 85 percent of companies that report extensive use of customer analytics (in terms of IT, analytics, and its execution) claim their company achieves a significant value contribution from customer analytics. This compares with around 20 percent for low users of the function, and some 30 percent of moderate users—suggesting that companies start to reap substantial benefit from customer analytics only when they achieve excellence, i.e., when their function can be considered state of the art. Just moving from a low to a medium level of maturity will merely generate limited success

This has particularly important implications for managers and their decisions on what needs to be invested in their organisation’s customer analytics to be competitive in the future. They need to determine the performance gap between their current customer analytics and state-of-the-art customer analytics in their industry, and to ensure that their additional spending on customer analytics stands a fair chance of bridging this gap. Otherwise the additional spending will—despite the best of intentions—turn out to have been a sunk investment right from the outset (because it will not pay off eventually).

2. Establish a culture that values fact-based decision making and analytics. Vital is a culture that is not focused purely on IT and analytics topics, but approaches customer analytics holistically. Although investments in IT and skilled employees are important, these investments alone will not deliver value. Leadership that expects fact-based decisions and an organization that can quickly translate those decisions into action are qualities more likely to lead to success than companies focused exclusively on IT.

First, we find that the execution and organizational aspects of customer analytics (such as a culture of fact-based decision making, analytics valued by the front line, management attitude and expectations) correlate most with the value contribution of customer analytics (Exhibit 4). This suggests that IT and analytics expertise are obviously necessary to create value from customer analytics, but it is the culture and organizational setup that moves the needle.

Secondly, interesting findings emerge when we focus on the sub-dimensions within analytics, IT, and execution that are most relevant to ensure that customer analytics creates value. It becomes apparent (see Exhibit 4) that having pragmatic and actionable foundations with the right cultural mind-set in place within the organization is more important than the perfect solution.

Within execution and organization, for instance, fact-based decision making and management expectations are more important than the speed at which these insights are put into action. Within analytics, the focus is on delivering the right actionable insights, and less on the fast development of new models. Looking at IT, a similar pattern emerges: a pragmatic 360° data mart that builds the foundation for customer analytics is more important than the complete (automated) linkage of all IT systems.

A key success factor is therefore to examine customer analytics holistically, including IT, analytics, and execution/organizational setup, and to pragmatically improve on all dimensions.

3 Secure senior management involvement in customer analytics. High-performing companies are led by data-savvy C-level executives who understand the importance of and involve themselves in customer analytics. We find that of those companies where senior management is not involved extensively, only 28 percent report a significant value contribution of customer analytics. This contrasts with 69 percent of companies with senior management involvement in customer analytics that say that customer analytics drives value (Exhibit 5).

Specifically, looking at the level of management that should be involved, it becomes clear that what drives the value contribution is top management/board involvement. If the company has established a role within the top management team (TMT), such as via a chief commercial officer, more than half of the respondents (53 percent) stated that customer analytics contributes significantly to value creation. If only senior management is involved but not the TMT, this drops to just 29 percent, close to the value of no senior management involvement at all (20 percent).





Author: mannmannandrew

Throughout my career I have been about building strong commercial relationships across an organisation, enabling and building data driven capability and leading teams encouraging them to develop industry leading solutions for customers. Ideas develop from collaboration, listening, observing and learning

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