In the last article, we addressed applying the proper analytics to the business problem at hand. Now, I would like to share with you a concept for making your data truly actionable with a focused outcome to drive increased value out of your trade promotion and retail execution work processes.
Many manufacturers are similar to TW Garner in that they successfully use a data analysis solution, (TW Garner use AFS™ G2) to help sales manage their trade spend and identify issues. This case study describes a great working example of how to get started using analytics to better manage your business. But imagine if your sales team could be alerted about issues that are either “current,” based on having increased visibility or are “predictive,” based on a trend that will move your KPI’s outside their targeted range? This is where “Management by Exception” can make your analysis actionable.
Management by exception (MBE) is a style of business management that focuses on identifying business performance issues where key metrics either have, or will, soon deviate from targeted guardrails. This allows management to not only focus on today’s problems but to also address tomorrow’s problems before they occur. When an analytics solution is used to automate MBE, it expands the scope of what can be monitored, and as a result, less management time needs to be allocated to monitoring every situation on the off chance that an issue may occur.
On the flip side, when something does happen, MBEs can be designed to escalate to the right management level. For instance, it can be set up so that the promotion manager is alerted at <40% compliance, the boss is notified when the threshold is <35% compliance, and the VP of Promotions is only brought in when it is <30%.
Image 1 below illustrates how MBE works using AFS G2. Data from AFS solutions such as AFS Trade Promotion Management Retail or AFS Retail Execution is pushed into AFS G2. Within G2’s MBE engine, the key performance indicators (KPIs), guardrails, business rules and frequency are defined. Additionally, dashboards and alerts are set up when the data indicates a deviation has occurred including who should be notified. Then, based on the defined situation, G2 will run a root cause analysis, and send an alert that includes a recommended action. This information can be displayed within an AFS solution dashboard and/or communicated via text or email.
Image 1: Management by Exception Model
Now that we have a basic understanding of how MBE can be applied with AFS G2, let’s take a look at a couple of examples. In Image 2, we want to use MBE to monitor trade promotion compliance by chain. Corrective action is designed to be taken whenever compliance dips below 30 percent. In this example the analysis is scheduled to be run daily and will alert us to any issues. Business rules will route an alert to the trade promotion manager whenever established thresholds are exceeded.
Here, we see that the compliance point 3 was the issue with the root cause being that the products were not merchandised properly. The recommended actions include a target visit to ensure the displays are stocked properly at the chain as well as having a rep schedule a follow-up visit to re-check compliance or potentially escalate the issue to the national account manager.
Image 2: TPM Example – Promotion Compliance by Chain
As a result of using MBE, the manufacturer should see a higher return from its trade spend investment because an effective promotion was executed that generated sales lift. They also have a clearer picture of promotion compliance in relation to cost and have more details that can be used as part of subsequent negotiations with the retailer.
Image 3 highlights an example in the retail execution space. Here, we want to monitor distribution gain/loss by brand. The manufacturer wants to monitor shelf share gains and losses by analyzing the segment activity for the competitors’ brands, viewing out of stocks by chain and SKU replenishment volumes. With these analyses and recommendations, the manufacturer should be able to increase share-of-shelf, leverage secondary placements and reduce out of stocks.
Image 3: Retail Execution Example – Distribution Gain/Loss by Brand