“Tanpin Kanri” is the next “Kaizen”!

“Tanpin Kanri” is the next “Kaizen”!

Does this spell the death of Retail Category Management as we know it?!

Highlights: Tanpin Kanri will be the next big business process/ philosophy export out of Japan after Toyota’s “kaizen”. Why? Tanpin Kanri has yielded merchandising decisions that has decreased inventory levels, while increasing margins and daily store sales”, says an HBS case study. Syzen is finding a lot of enthusiasm among “high product density” Retailers for our predictive analytics SaaS solution that makes Tanpin Kanri scalable.

Dr. PG Madhavan is the Founder and Chairman of Syzen Analytics, Inc. He developed his expertise in analytics as an EECS Professor, Computational Neuroscience researcher, Bell Labs MTS, Microsoft Architect and startup CEO. He has been involved in four startups with two as Founder. He has over 100 publications & platform presentations to Sales, Marketing, Product, Industry Standards and Research groups and 12 issued US patents. He conceived and leads the development of SYSTEMS Analytics and is continually engaged hands-on in the development of advanced Analytics algorithms.

More at www.linkedin.com/in/pgmad

As a keen observer of the retail ecosystem’s demand chain portion for the past 3 years or so, I am struck by the inefficiencies in large portions of Retail. Shoppers finding what they want on the shelf is considered a BIG problem in the industry (the so called “OOS problem” or Out-Of-Stock problem) – to the tune of $170 Billion per year! There are many culprits – let us consider the systemic ones.

The following diagram illustrates the portion of Retail ecosystem on which we will focus in this blog.

The left half represents the current dominant model. “Push” model drives manufacturer’s FMCG (fast moving consumer good from “brands” such as Procter & Gamble, Kraft, Unilever and others) into the supply chain with store shelves as the final destination. As retailers move to the right half of the picture, they tend to be more agile and mature in their practices and are seeking a competitive edge through differentiation – they find that by focusing their store operations to satisfy the LOCAL customer via making available what she prefers on the store shelves, they can win. The poster-child of this revolution is 7-Eleven, the ubiquitous store at virtually every street corner around the globe!

7-Eleven’s use of the “Pull” model since early 2000’s has been very successful as captured in a case study at Harvard Business School in 2011 (HBS Case Study: 9-506-002 REV: FEBRUARY 23, 2011). Quoting from this study, “Toshifumi Suzuki, Chairman and CEO of Seven and I Holdings Co., was widely credited as the mastermind behind Seven-Eleven Japan’s rise” and goes on to say that ‘Suzuki’s emphasis on fresh merchandise, innovative inventory management techniques, and numerous technological improvements guided Seven-Eleven Japan’s rapid growth. At the core of these lay Tanpin Kanri, Suzuki’s signature management framework’.

Proof is in the pudding – “Tanpin Kanri has yielded merchandising decisions that has decreased inventory levels, while increasing margins and daily store sales” since the 2000’s, the HBS case study points out. So what exactly is Tanpin Kanri?

Tanpin Kanri or "management by single product," is an approach to merchandising pioneered by 7-Eleven in Japan that considers demand on a store-by-store and product-by-product basis. Essentially, it empowers store-level retail clerks to tweak suggested assortments and order quantities based on their own educated hypotheses . . . 

You can tell that Tanpin Kanri lies well to the right in the Retail Ecosystem diagram above. To call out some features:

·       PULL model

·       For a buyers’ market

·       Focus on How to satisfy customer

·       Item planning and supply driven by retailer and customer

·       Symbolic of Consumer Initiative

Looking at this list, you may be flabbergasted if I told you that this is NOT how all of Retail works! You may be wondering with all the emphasis on satisfying the customer and ours being a “buyers’ market” in virtually every case, why would any model other than varying shades of Tanpin Kanri exist in the decade of 2010?! That is exactly why I claim that there is an “inevitability” about Tanpin Kanri. And I conclude that Tanpin Kanri will be the next big business process/ philosophy export out of Japan after Toyota’s “kaizen”.

Push model exists virtually everywhere in US grocery retail, super and hyper markets, smaller store chains. The method of “Category Management” referring to a joint-decision process by CPG (consumer product goods) manufacturers and retailers determine what will be on the store shelves for the next 6 or 12 months. Often, all the stores in a chain (some as large as 3000 stores) will have the same “planogram” (a visual representation of product SKUs on the shelves) irrespective of the local clientele! Obviously simple to implement, why has Category Management not evolved to reflect customer preferences explicitly.

A FederalTrade Commission study may hint at the underlying issue; to quote, “The retailer and supplier also typically discuss funds – slotting, promotional, co-op advertising, or other introductory allowances or discounts – some of which would lower the retailer’s per unit purchase cost for an initial period of time”. As is obvious, this exchange of funds can short-change the customer since they are not directly part of the equation! CPG’s are hyper-wealthy compared to razor-thin margin Retailers – that the CPGs can improve the Retailer’s bottom-line directly with these funds will have a distorting effect on commerce due to the joint-decision process of Category Management.

I believe that it is simply a matter of time before Tanpin Kanri variants dominate the Retail demand chain model. If another FTC study finds the exchange of funds between CPGs and Retailers as collaboration of an "unsavory" nature, the transition to Tanpin Kanri will be rapid. If not, as shoppers clamor even more for their preferences to be made available, Retailers will evolve incrementally kicking and screaming – ultimately, we the shoppers pay them more money than CPGs!

So, where does Tanpin Kanri provide most bang for the buck today?

Where ever Product Density (number of products to be stocked per unit area) is high, “customer pull” will help prioritize what products to stock. Today’s Tanpin Kanri at 7-Eleven Japan accomplishes “customer pull” incorporation via super-diligent store staff manually making the choices. Surely, in these days of Big Data and Analytics, there must be a way to provide a helping hand to the store staff to predict “customer pull” or as we call it “Shopper Preferences” . . .

Syzen Analytics, Inc. has accomplished exactly that using Machine Learning and a new development in Analytics called “SystemsAnalytics”. Syzen is able to provide SKU-by-SKU, store-by-store and week-by-week predictions using typical T-Log data that every Retailer has in its data archives. A typical prediction of Syzen’s ROG-0 SaaS product for a typical SKU at a particular store looks like this.

·       The purple uneven “picket fence” is the weekly predictions. This is obtained by combining different “masks”.

·       The papaya-colored mask is the new and most significant one. The values are predicted based on appropriate past intervals of T-Log data digested via Systems Analytics and updated adaptively.

·       The numbered masks in the middle accounts for things that the store manager knows that will happen next year such as a local festival or a rock concert in the nearby park.

·       The MANUAL part of Tanpin Kanri now only involves the store staff simply making daily small adjustments to the SKU “facings” based on local shopper “gossip”!

As we discussed, many retailers are NOT ready to embrace periodic refinement to reflect shopper-preferences, especially if it involves foregoing lucrative fees from CPGs. However, the “old timers” can take advantage of the outputs above for old-fashioned assortment optimization – average the height of the purple figure and use the average as the SKU volume that they order every week; our result is store specific but they can average each SKU over all stores in the chain and generate one Planogram. Of course, they will be throwing out a lot of value (and revenue) by not being responsive to customer preferences on a store-by-store and SKU-by-SKU basis!

Convenience stores are drawn to this “predictive” Tanpin Kanri method because of the maturity of operations they already possess. With more agile supply chains and the desire to differentiate their store in response to their local clientele, Syzen is finding a lot of enthusiasm among “high-density” Retailers for our predictive solution that makes Tanpin Kanri more scalable due to lesser dependency on super-diligent store staff. Advances in Systems Analytics and other quantitative methods will refine products such as Syzen’s ROG-0 SaaS in the future to sharpen shopper-preference based product assortment predictions.

More on ROG-0 SaaS: http://advancingretail.org/product/syzen-rog-0-saas/

Syzen website: www.syzenanalytics.com