Big Data Analytics: Aligning Insights with Business Strategy

The Role of Analytics in Sales and Retail

Big data analytics is critically important to sales organizations and retailers. Sales representatives in consumer goods brokerages, for example, routinely use analytics when pitching ideas to major retailers because analytics works: it helps stakeholders see how customers interact with displays, product arrangements, lighting, spacing, and more. As LaValle et al. (2011) point out, selling is as much a matter of logistics as it is about bringing a quality product to market. Marketing, customer service, customer engagement, and experience management all play a part in a retailer's ability to obtain competitive advantage. Sales representatives who work on commission — earning a percentage of every sale generated once a retailer accepts a product onto its shelves — pay particularly close attention to analytics for exactly this reason.

The Challenge of Data Overload

However, as LaValle et al. (2011) also note, a typical organization usually "has more data than it can use effectively" (p. 22). Simply having the data is therefore not enough. One must know how to interpret it and apply it to one's advantage. The key to using analytics well is to link it to business strategy and make it accessible for end-users to understand. That is what enables the right action to be taken at the right time.

Narrowing one's focus to achieve an obtainable goal should be the aim when using analytics. A company seeking competitive advantage, for instance, will apply analytics to make small, targeted changes rather than large, sweeping, universal ones. Organizations that excel at utilizing analytics do so because they examine one specific area of the value chain at a time — whether that is improving the customer experience, refining channel strategy, or advancing portfolio and process innovation. By focusing attention on specific, actionable areas, they improve sales and create greater value for the company.

Aligning Analytics with Business Strategy

Analytics should be aligned with business strategy with the explicit purpose of addressing a particular business challenge (LaValle et al., 2011). That foundational alignment opens the door to new possibilities. But those possibilities will not emerge if the right questions are not being asked. Rather than leaping directly into big data, the correct approach is to begin with questions and critical thinking (LaValle et al., 2011). An organization must first identify what it wants to achieve in a specific area, and then turn to the data to find answers. In other words, rather than sifting through data in an attempt to understand a situation, the organization poses its central questions first and then uses the data for a defined purpose.

Conclusion: Leveraging Data Without Being Overwhelmed

It is about leveraging information instead of being overwhelmed by it. Rather than burying oneself under a pile of data that are irrelevant to one's specific questions or challenges, one can think of big data as a salt dump: when the roads become icy, the salt is there to treat them and make them safe again. One does not unnecessarily dump salt on the roads when it is not needed, because doing so makes them less efficient. In the same way, data analysis is a resource to be applied purposefully — there to help, not to hinder.

References

LaValle, S., Lesser, E., Shockley, R., Hopkins, M., & Krushwitz, N. (2011). Big data, analytics and the path from insights to value. MIT Sloan Management Review, 52(2), 21–31.