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Pushing pricing to the final frontier

Monday, June 25, 2018 - 07:00
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Pricing strategist Dr. Jim Sills is giddy on the data science behind how much a car battery should cost. To feel his passion for building profitable product assortments, just look at the hundreds of scribbled red and blue colored lines of software codes dancing across a row of white boards in his office. Sadly, however, too few businesses in the auto care industry can obtain affordable big data technology to quickly spin grains of unruly data into purified, actionable information that matches his vision.

According to Sills’ consultancy, Clear Demand, big data alone is a half-baked solution. In a speech before the Category Management group at the May 2018 Auto Care Association conference, he suggested alternative strategies that this industry’s have-nots will require to elevate their competitive advantages. To assure a sustainable price architecture that will fit the auto care industry dynamics, more finessing is needed by progressive thinkers like Clear Demand.

Why are the have-nots stuck in a rut? For starters, selling items off invoice cost is not a sure-fire money maker. Albeit convenient, cost-plus pricing ignores the shopper perspective with no guarantee that this approach will cover fluctuating business expenses. Competitor based price matching also faces limitations. While useful for benchmarking, website scraping technologies fail to stay apace with instantaneous price changes. Moreover, syncing the online channel with the physical store can become a messy chore, which leads back to second guessing on how much to sell an item.

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Industrial sized information management specialists like Oracle, SAP and IBM make big data their business by vacuuming gigabytes of unformatted bits. For a big outlay, national retailers and tier-one suppliers are contracting these software companies to curate this intelligence from e-commerce sites, social media, exit surveys, panel data, and the like. As a result, unless any of the weaker outfits have an on-site IT ninja, their strategies to effectively promote, markdown, or otherwise makes it harder to establish a differentiated assortment to appeal to the repair shop or the serious do-it-yourselfer.

By design, Clear Demand has labored at great lengths to automate a real-time profit optimization model at a fraction of the expense that a global information management firm would charge. Much growth can be reaped from available data to identify assortment gaps that shoppers care about, says Dr. Sills. Item to item price matching only promises more profit loss because managers do not quantify the competitive forces on the market place’s most coveted products versus those items that shoppers don’t care about.

Sills’ claim on big-data interconnectivity hinges on two premises. First, empowered shoppers enjoy vast omni-channel transparency on things like price and attributes, which makes it easier for them to value what is truly substitutable or what is most distinguishable. Second, these purchase behaviors exert pressure that is measured by price elasticity, the index that measures someone’s willingness to pay for something ―a direct impact on how many units are sold. By extension, cross-elasticity gauges competitor movements from moment to moment that pings an alert of any seismic change. Here’s the rub says Sills: This accessible data is more manageable than you think to forecast sales, stock product, and retail it at a competitive value.

Helping retailers like a Home Depot to gain an edge by managing and optimizing pricing, promotions, markdowns and space will not easily convert to a replacement parts industry that caters to a diverse set of customers. Auto care experts may point out that e-commerce channels, or a physical retailer face the tricky balance act of setting multi-tiered price levels for the same wiper blade or water pump sold directly to a jobber store, installer, and a do-it-yourselfer. Moreover, these three customer segments undergo their own unique buying path.

Another concern is how advanced analytics will tackle the evolving life cycle of replacement rates, predicting exactly when a hard part―window regulator, electrical system, or exhaust assembly―might fail in a given year, make, model vehicle. Granted that for almost two decades that there are plenty of inventory control modules in full circulation.

And of course, consider the obvious difference of the front-end product assortment line up that speaks to the DIYer while the back room houses the parts on behalf of the repair shop or the independent auto parts store. While a consumer may easily part ways with a TV set that cost $500, it’s not the same purchase journey for someone buying parts and chemicals to extend the life of a ten-year old vehicle.

But these hurdles can be cleared if a software company is able to modify their processes to those specific market conditions.  In Clear Demand’s case, they are currently applying an “intelligent” rules-based algorithm that monetizes violations assigned to brands and private label assortments, competitive prices, and margin volume. During my visit to his firm, Sills took me on a virtual reality dash board test ride. By ranking each rule to each price point at each frequency, the penalty is expressed in dollar values. Conversely, when every rule is respected, the reward is expressed in profit volume.  Multiple “what if” scenarios can be run until the retailer manager is satisfied before finalizing the inputs.

Admittedly, the finanicial calculus that Clear Demand is currently using in the consumer goods industries are vague, and its direct application to the auto care industry is untested. Nonetheless, this rules alert system that signals price deviations from its preset targets is worth exploring, especially if Sills can prove how optimization science can yield a profitable outcome. Never forget that the bigger picture is less about Clear Demand, and more about innovative tools aimed to rattle old methods and expand the auto care industry across every facet.

As one celebrated business management specialist Peter Drucker once wrote,” The thing that got us here will not get us there.” So far Clear Demand has put their best foot forward. Halting progress is far better than no progress. An afternoon at the Auto Care conference is symbolic, but now Clear Demand and related software firms should be introducing industry focused tools that makes sense for more than just the big players. That means junking the one-size-fits all consumer goods templates. A canned solution like that will only put everyone back to here than at the efficient frontier that they wish to push.


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