Every team has their list of strategic initiatives that (in an ideal world) they hope to devote the time to investigate, plan towards and solve. Typically, these are high value questions of the business that require extensive planning to complete or to simply move forward in an impactful way. Regardless if they are intended to achieve answers quarterly, annually, before or after the holiday chaos, finding the time for teams to devote to the strategic plan is always a big problem - somehow these initiatives are the first to get pushed down the priority totem poll.

The week of a merchandiser is consumed by the ongoing analysis and investigation of what occurred the week prior, drowning in questions as to what led them off plan. When Monday is entirely consumed by reporting, followed by days of data mining and metric firestorms, it’s no wonder that the time to devote to “big picture” initiatives is the first to fall off the to-do list. Week after week, merchandisers arrive to Thursday and Friday, and have no time to dive into the larger projects that they could (or even should) be focused on. Ironically enough, most merchandisers are initially hired (in part) to drive the actionable recommendations that address these larger plans. However, their roles seem to always shift to analysis, report generating and endless data inspection. With every KPI fire that arises or every metric drop to be explained, precious time is reduced in order to tackle the more immediate concerns.

So how do retailers get time back on their side and open the opportunity for merchandisers to focus on these initiatives? The missing piece amongst most retailers is connecting their existing silos of data. The answer here is not just a data warehouse, but a system by which all data sets are linked, providing visibility to cause and effect across the organization when any action is taken or when any condition occurs. What good is looking at conversion rate and return rate side-by-side, if you weren’t aware that 60% of your return rate belongs to a poor fit across multiple products. More importantly, it is futile to further invest marketing dollars in these high converting products when they keep coming back in the door. The only potential indicator to a problem in this situation is a steady return rate. Deceptively, if the ROAS continues to appear positive, along with a consistent conversion rate, without a drastic spike in return rate to raise the “red flag,” the issue would remain unchecked and continue to simmer below the surface. A single source of the truth that highlights cause and effect, not only drives more efficient business practices throughout the week, thus freeing up critical time for these initiatives, but also provides a platform by which strategic initiatives can be solved through data and not just gut “trial and error”.

A recent example comes to mind to further illustrate this point. One of the key strategic initiatives for 2015 set by a retailer was to reduce returns, as it had been determined the cost and profit lost through managing returns was drastically impacting their business. Halfway into the year, the merchandisers (due to bandwidth) were only able to generate a list of the products with an increased return rate. A place to start, but clearly not an answer. Reaching an impasse, this retailer invested in a connected data system and immediately the resolution to mitigate returns became quite clear. Merchandisers needed this technology to connect all of their data in order to highlight the root cause. In this case, it was through connecting SKU-level returns, inventory, product reviews and ratings, manufacturer codes, product conversion, as well as all cost data associated with shipment and returns in order for the teams to pinpoint the cause. The system flagged that a large set of returned products, all produced from the same manufacturer, were all receiving reviews with a similar sentiment of quality dissatisfaction. The increase in negative reviews occurred within 30 days of a manufacturer switch - coinciding with an immediate surge in return rate across these exact products. It wasn’t until the data system was in place that the decision to change to a less expensive manufacturer the prior year was actually found to be a significantly less profitable decision and the primary culprit to their return issues. Without systematically connecting all of these data assets, attempts to pinpoint the root of the return issue would still be under investigation, along with ongoing profit loss.

How were they able to arrive at that conclusion only after the adoption of this technology? The original path to investigation was akin to finding the proverbial “needle in a haystack”. Prior to the addition of this technology, the team was able to identify the products that were being returned at a higher rate, but assessing the “why” meant combing through 100’s of different possibilities in an ad-hoc manner.

• Would return reasons shed light on an obvious answer? No, because the directionality of that data was weak due to non-specific reasons for return of the products.
• Would the returned merchandise itself highlight an issue, such as product color not properly reflective in the image or unclear description on the product page? No, and sifting through 100’s of products in this manner would ultimately be counterproductive.
• Were there any commonalities to the size guide vs. the fit? Should the business re-evaluate their sizing guide? No, unfortunately this was not the issue either.

The litany of possibilities that needed to be investigated and ruled out were leading the retailer down a path of uncertainty and wasted time, time that was never there to begin with. After 6 months in the dark, the launch of the new system changed the game.

For retailers to achieve continued growth and stay competitive, they will need to focus even harder on their strategic initiatives that push the business further year-over-year. The challenge to win back time will play a heavy role in how retailers move into the next phase of their success. Retailers will need to invest in a system that provides a connected data point of view to empower teams to arrive at the right conclusions. The optimized week is an essential piece to push forward. Check back in the New Year to understand the signals of a delayed week and how to drive effectiveness for you and your teams in order to finish out the week with actions made for notable improvement.