Retail execution is a methodology used by many CPGs to control and supervise how their products are positioned in stores, often centred around core KPIs such as price, presence and promo. Decades of data and analysis have built up a body of industry knowledge about the subtle ways in which CPGs can win consumer attention in front of the shelf, drive sales and capture the market share. Over the past 15 years, however, the competition has heated up, with almost all consumer product leaders developing their own in-store execution programmes.
By tracking a number of KPIs (such as product presence, promo, share of shelf, etc.) for retail execution in a systematic way, the top CPGs are able to gain a comprehensive view of their retail execution in stores. These insights are invaluable: producers can understand what kind of mistakes there are and where those mistakes are happening. When that data is processed and delivered in a timely way, these insights become actionable, allowing companies to deploy their resources where they are most needed and make corrections to execution as soon as possible.
Today, there are a number of tools and technologies available for retail execution and monitoring, affording CPGs greater choice and flexibility to tailor options to their needs. To help them understand how to use these, we’ve put together some best practices and strategic considerations below.
Best Practices
Reduce the number of KPIs you are monitoring. Bain has uncovered there are many KPIs for retail execution that realistically only add marginal value in terms of lifting sales. Indeed, the cost in time to collect this data (by internal field forces, agencies or other methods) may also negate any impact on sales.
Giovanni Arnese, Partner at Bain, has stressed that “The question is not ‘what additional data are we looking for? But ‘what is the essential data that drives decisions?“
Combine complementary data sources. Many of the interviewees in our white paper strategic use of data across the business, ensuring that key stakeholders not only have a broad overview of their retail execution, but also the granular detail at the store level.
Ensure that you are both collecting data and correcting problems. Industry leaders are shifting away from a model that focuses purely on periodic data collection and analysis, and gravitating towards iterative and continuous monitoring. This means that CPGs are also using real-time data to identify problems and take corrective action, building up a data set of historical data over time which can also identify which interventions work, and which don’t.
Strategising for Retail Execution and Monitoring
The first step in establishing a strategy for retail execution and monitoring is to understand what kinds of data sources and technologies are available. From internal field forces to the crowd, Sales Force Automation tools to Image Recognition, the scope for choice has never been wider. Different combinations of data sources with technologies each have their strengths, meaning that this choice is highly dependent on the company profile, its goals and its resources.
Chief amongst considerations for employing a different data source or technology is the ROI. In particular, the cost and reliability of cutting-edge technologies, such as IR, were key factors for decision-makers. Yet these concerns go beyond the desire to see a reduction in the costs of technology: when considered in terms of time saved for personnel during store visits, technologies like IR can be viewed as value-add. As an FMCG leader put it:
“Reliable technology like IR will allow us to capture key in-store variables (retail mix, OOS, share of shelf, promo in place) to free up sales time to reinvest in improvement. Scale and affordability are key, we want to free up time – not to save money, but to add value and shift from lower value activities.”
If you would like to learn more about Retail Execution and Monitoring, you can read the full outlook in our white paper “Perfect Sales Execution: The ultimate guide to data sources and technologies” here.
