Compared to organizations in the retail, communications and financial services sectors that are gaining noteworthy value from advanced analytics, it is arguable whether consumer packaged goods (CPG) companies have yet to achieve the same results. Often they are still using outdated approaches to sales and marketing, and many are also not using social and mobile data to their full potential.
In a highly competitive CPG marketplace, the opportunities presented by analytics are pronounced. For the companies that are getting it right, significant top and bottom line growth can be a direct result.
As consumers browse and buy across an array of digital devices and channels, they generate a volume and variety of data that is proliferating daily. By turning this data into insight, marketers can understand consumer intent, develop innovative offers, and connect with shoppers in a way that makes sense to them. This can help CPG companies keep up with rivals and forge productive long-term partnerships with retailers. It also explains why senior marketing executives in CPG — along with the majority of their peers from other sectors — are planning to increase their spending in this area.
And yet, as they invest in these capabilities on a function-by-function basis, CPG companies are encountering many of the same fundamental issues that organizations across all sectors face. Inundated with big data sets of variable quality, they often struggle to derive usable insight. Rather than telling a compelling story about consumer behavior, many end up simply producing hindsight descriptions of what happened. Indeed, our recent research suggests that less than half of companies with localized analytics capabilities believe them to be a differentiating capability for their organization.
To achieve success, a new mindset across the entire organization is needed. We are seeing leading companies re-thinking how they organize for analytics and reassessing what talent they will need in the future – making room for skills such as econometrics, customer segmentation, investment optimization and predictive analytics. They are also aligning on what functions will drive the most value for the business, such as marketing and sales, and putting focus there as a priority.
The effectiveness of this approach is illustrated by the experience of one global CPG leader, which wanted to use analytics to engage consumers and improve competitiveness.
This global, decentralized company had pockets of analytics excellence in place, but lacked the mechanism to make use of its capabilities across the organization. It therefore set out to develop an operating model that would help generate the enterprise-wide analytics and business insight it needed. The first step was to make analytics part of the strategic process by fully understanding what it required from data and then re-engineering decision-making across business units to make it more analytics-driven. To this end, the company assessed the views of dozens of senior leaders and several hundred stakeholders to agree on a vision for analytics, as well as a mission and guiding principles that would enable growth and drive competitive advantage.
The company then designed a new analytics organization and allocated resources based on the maturity and needs of its business, carrying out a diagnostic and capability prioritization to deploy the right analytics skills where they were required across the global organization. Finally, to understand talent needs as the capability grew in importance over time, it projected out its future needs in terms of resources, roles and responsibilities, as well as lines of reporting, within its operating model.
As the case of this CPG leader shows, using analytics to drive marketing in CPG is no small undertaking and involves change and senior level buy-in on an enterprise level. The analytics-driven success the company has experienced as a result, however, demonstrates that the reward easily justifies the means.