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5.5: The Feedback Process

  • Page ID
    45078
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    Learning Objectives

    • Describe how consistent feedback can make the process iterative and roundabout rather than sequential

    Previously, you read about implementation and control as the 5th step of retail strategy planning, dealing with how a firm organizes cross-functionally and communicates priorities. But, it also includes how the firm tracks progress toward its objectives, measuring performance so that adjustments can be made, if necessary. Effective monitoring helps firms react and adjust to uncontrollable variables, which can impair progress toward a strategic objective. It’s this control through monitoring, measuring, and adjusting that helps a firm remain agile and able to react to changes in the competitive environment.

    Feedback, of course, is fundamental to effective control and it can come in many forms. It could be quantitative like change in store traffic, sales revenue, customer satisfaction scores, or operating profit. Quantitative data is data about quantities, meaning it can be measured. The feedback could also be qualitative like positive comments left on the firm’s Facebook page. Qualitative data cannot be expressed as a number. It isn’t less relevant than quantitative data, but it is harder for decision-makers to assign relative significance to it.

    Regardless of the type of feedback data, quantitative or qualitative, it’s important to understand the difference between leading and lagging indicators of success. You’ve read a bit about leading indicators, so it might make sense for us first to describe trailing indicators and their limits. Two of the measures we described above, sales revenue and operating profit, are lagging indicators. They’re the product of the actions that have been put in-place. But, we cannot influence them further, we can only monitor and measure them. They reflect history.

    Let’s return to our example of HEB and their goal to increase sales revenue by 5.6% by updating their assortment with more fresh & all-natural products. If we measure YOY change to sales revenue, we get a data point. But, we can’t make any changes to that fact or really understand what is likely to happen next. Consider this fictitious data for HEB YOY sales revenue:

    • +4.5% vs. LY (last year) for January, but missed expectations.
    • +0.3% vs. LY for February, but missed expectations
    • -1.1% vs. LY for March; missed expectations
    • +6.2% vs. LY for April; exceeded expectations

    As a manager, the results might make you nervous or impatient and ready to make changes. But, the data is backwards looking; it reports what happened, but doesn’t give any tools or perspective on what to do next to influence performance in May and beyond.

    Again, particularly important is identifying and tracking leading indicators: meaningful factors whose change indicates or predicts future change. These predictive measures give a firm confidence that their strategy is on-track. Let’s think through the HEB example and identify some potential leading indicators they could use. Perhaps customer satisfaction, purchase intent (how likely they are to buy), and/or basket composition.

    If the fresh and all-natural products are generally on-trend with consumers, it would make sense for HEB to measure customer satisfaction levels about their offerings, assortment and pricing BEFORE the strategic initiatives are put in place and throughout the implementation and control period. While high(er) levels of customer satisfaction wouldn’t guarantee that HEB meets its financial goals, performance on this metric might imply how well the changes are meeting customer needs. If there’s no change in the metric, it could be that HEB hasn’t made the right assortment choices or that they are not “getting credit” for the changes and need to promote them more.

    Purchase intent is a good complement to customer satisfaction because it builds on satisfaction and takes it a step further—are you planning to buy? By tracking this metric, decision-makers at HEB can see how their changes could impact shopping behavior. Of course, what consumers say and what consumers do can be two dramatically different things. But, if purchase intent is not favorable, it may indicate that the changes have not resonated with the shopper or that there are other barriers to trial like price-point. However, if satisfaction increases and purchase intent increases, we should feel confident that HEB has made the right decisions in updating their assortment the way they have.

    Another metric to consider is basket composition, which measures what’s in a shopper’s basket and what percentage of the total spend it represents. For example, consider these purchases:

    • Bananas- $2.00
    • Chicken Breasts- $8.00
    • Cereal- $5.00
    • Rice- $2.00
    • Milk- $3.00
    • Total- $20.00

    In this case, produce would represent 10% of the basket ($2.00 for bananas/$20.00 in total purchases). Meat would represent 40% of the basket ($8.00 for chicken breasts/$20.00 in total purchases.) This, of course, is over-simplified. But, imagine extrapolating this out across all shoppers and all purchases. In measuring this, HEB could assess whether fresh and all-natural products have taken a larger role in the consumer purchases. Thus, it takes intent to buy a step further and assesses whether that purchase activity is actually taking place, relative to all departments, categories, and sections in-store. Again, if this metric trends favorably, we’d have confidence that the assortment decisions HEB put in-place were right and have been well-received by the customer.

    Of course, there are other metrics HEB could use; these are just a sample. And, yes, sales and profit are important. But, it may be worthwhile to think of lagging indicators like them as the destination. That is, they’re backward looking. So, once you’re able to measure them, you’re unable to make corrections. Leading indicators, by comparison, provide insight about how well a plan is taking shape, exposing areas to influence strategy, implementation and execution.

    Contributors and Attributions

    CC licensed content, Original
    • The Feedback Process. Authored by: Patrick Williams. Provided by: Lumen Learning. License: CC BY: Attribution

    5.5: The Feedback Process is shared under a CC BY 4.0 license and was authored, remixed, and/or curated by LibreTexts.

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