The Profitability Challenge: Why SKU-Level Visibility Matters

Profit-and-loss visibility at the stock-keeping unit level is so critical, yet so difficult to attain.
Published: October 20, 2021

Ed. Note: This article was previously posted at  Retail TouchPoints.

My days as a merchant are long over, yet I remain a retailer at heart. Having spent many moons in retail, with a short departure for my masters class in mobile adtech, it is exciting to be back among my brand colleagues crushing it in ecommerce. As an advisor for industry groups such as the Ascendant Network and the Digital Shelf Institute Executive Forum, I’m surprised to hear my industry friends are still frustrated by ongoing online profitability hurdles. It was a challenge in 2015, and it’s hard to believe this puzzle hasn’t been solved yet by some combination of tech, process and operating model advances. Stock-keeping unit (SKU)-level profit-and-loss visibility is so critical and yet difficult to attain, with challenges including:

Product profitability varies greatly depending on channel: While being an omnichannel brand seems smart—why not be everywhere?—when you sell your product on every marketplace, it’s hard to know your exact margin by SKU. Due to the fact that each platform has a myriad of fees (e.g. referral, storage, fulfillment costs—the list goes on!), it’s common to have four or five entirely different net profits from a single SKU depending on the multitude of contributing factors.

Amazon will penalize you for unprofitable items: If your product “Can’t Realize a Profit,” it gets labeled as CRaP—yes, that  started internally at Amazon, almost as a joke. This occurs if the algorithm determines that even under the best circumstances (e.g. high quantities, supported by marketing, an accrual or co-op program), the item still loses money on a per-unit basis and therefore is structurally unprofitable for the company to carry it. What happens next, though, is not funny at all, especially for brands in the Top 100 sales ranking. The brand loses all the goodness achieved with the algorithm. When labeled as CRaP, the product falls out of Amazon’s “free marketing,” the automation and personalization feature that keeps top-selling items the most visible.

For CPGs in particular, the sheer size of their product portfolios is what necessitates this driving need for SKU-level understanding. An  analysis by PwC of one global CPG revealed that half of the SKUs in its portfolio drive less than 5% of the gross margin, and this does not even account for the cost of complexity within the long tail. More than a third (35%) of SKUs drive zero incremental profitability. Imagine what could happen if those weeds were identified and yanked out. How do we solve these types of challenges? Ecommerce leaders must address the source of the problem and be both proactive and collaborative to find the solution. Translation: You can’t do this alone.

Reimagine the Retailer-Brand Relationship, Particularly Around Data
At my young niece’s birthday party last week, she came running at me with a scowl on her face and said, “Olivia won’t share!” My response was, “Did you even ask her to share?” And just like that, the problem was solved. While I don’t want to trivialize the issue around data sharing, I will say that if you’re a brand and you haven’t asked for the data you need from your retail partners, you’re not helping yourself. Participate in your own rescue by first, putting in the request, and second, collaborating to create a process around responsible and ethical data sharing. Tip—your Chief Privacy Officer is a great partner to leverage in defining smart, sensible and privacy-sensitive solutions.

Improve the definition of internal accounting methods: If you don’t have a strong connection with your finance leaders, start there. Heads of ecommerce should partner with the CFO to create a mutual understanding of the category and SKU-level P&L and establish appropriate accounting methodologies. Which types of costs should and should not be included? How should they be allocated? Together, determine responsible business assumptions to inform your allocation decisions.

Leverage AI for speed and sophistication: Technological capabilities are moving faster than we are currently applying them. Specifically, artificial intelligence has made more possible than we have had the time or opportunity to execute. Take forecasting: there’s no reason why demand forecasting should still be done manually, yet many teams remain buried in spreadsheets, failing to leverage machine learning to support them. The same goes for SKU-level profitability. We can and should have visibility into each and every item in our product portfolios—and not in 30 days, but in real time. Or okay, within 24 hours. We’ll take that if we must—for now.

With an automated operating system that can pull all costs across the entire ecommerce ecosystem, you should be able to get a unified view of SKU-level performance. And don’t stop there, because what’s a report but a look at the past, even if it’s the very recent past? A platform that doesn’t just gather and surface SKU-level data, but provides actionable insights so you can make decisions that inform future growth—that’s the real solution. We can solve the SKU-level visibility problem, but until we can solve the SKU-level profitability problem, our work is not done.

Julie Bernard is chief marketing officer at  Tradeswell. She is a strategic marketing leader and C-suite executive with a reputation for innovation, enthusiasm, progressive business judgement, and most importantly, building world-class teams. Following her tenure spanning merchandising, marketing and technology at Saks Fifth Avenue, she joined Macy’s as senior VP, launching a transformation initiative to modernize the iconic brand and its omnichannel efforts in customer strategy, data science, loyalty, credit and marketing technology. She then shifted into B2B, taking the helm as both chief marketing officer and product officer at Verve, a mobile marketing platform. Bernard brings to Tradeswell a unique combination of retail, technology, media and analytics expertise.