The Optimization Arc – From Black Box to the Cloud

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Joshua Trees

WHEN THE GOOD FOLKS at DemandTec asked me to commence writing a series of short commentary pieces on this blog, I accepted the assignment in large measure because the company’s story is a reflection of the story of merchandising analytics in all its facets.

Like DemandTec, an IBM Company, my history as an analyst in what used to be called the “price optimization” sector dates back more than a decade. In 2002 I was asked to try to make this very powerful new retail science more accessible by explaining its benefits and justification in terms other than technical. Price optimization was a new idea, and its target purchasers were wary of its mysterious mechanisms.

Retailers’ objections about the apparent “black box” nature of base price elasticity permeated the sales cycles of industry pioneers, DemandTec’s included. Prospects worried that using computers to model price elasticity and interaction effects to maximize margins was too manipulative. What kind of push-back would they face if shoppers found out?

It took some effort at first, but we correctly reasoned that since optimization is based on measurements of shopper response, it is inherently shopper-centric in nature. Overall, the process tends to deliver more consistent competitive value to shoppers, while retailers maintain sustainable gross margins. These ideas are familiar now, but they were new territory ten years ago.

At about the same time, other pioneers began applying the principles of optimization to other complex merchandising decision processes, notably to the depth and timing of markdowns, and the terms of in-store promotions. Other folks were advancing assortment and space planning tools from the category management side of the house. Pretty soon, it dawned on the smarter people that that the interconnectivity and interaction effects they observed within each of these areas of discipline also exist across these areas of discipline; and not just within the retail organization, but between it and its trading partners.

A simple example might arise when a lower everyday price for a popular item revs up its turnover rate. The existing number of facings may become insufficient, creating intermittent out-of-stocks. The lost sales may tend to distort apparent demand and delay re-orders, and the problem perpetuates. Fold in other concurrent events within the category, such as new item cut-ins and shelf capacity constraints and the problem grows very knotty indeed.

Fly by Wire

When I was first learning about all this, someone I respect explained to me why the mathematical model behind pricing optimization is related to the intricate “fly-by-wire” flight control systems that keep stealth aircraft from dropping out of the sky. Both critical objectives – keeping thousands of interrelated SKUs properly tuned, and keeping multiple interrelated flight surfaces properly tuned – share several traits:

  • The model is big
  • The model must be dynamic and continuous
  • The model must be highly reliable under duress
  • The model must be continuously updated at a time cycle that is rapid enough to support critical decision-making
  • The model must be appropriately accessible to decision makers

In one respect, those flight control systems may be simpler than retail demand models – there’s only one cockpit in an aircraft. A retail organization, by comparison, may have dozens or hundreds of individual decision makers and planners and trading partners interacting with the merchandising model through various dashboards. Each needs appropriate analytics and decision support according to his or her role.

To the Cloud

As DemandTec developed and acquired its portfolio of software offerings over the past ten years, it placed evident emphasis on connecting users with the data and with each other in practical and beneficial ways. It was an early advocate of the software as a service (SaaS) application business model, which placed the heavy application power in outside computer servers, relieving clients from the burden of maintaining these systems in-house.

Lately the tech industry tends to refer to service-based computing as “the cloud.” In fact DemandTec’s current positioning, “The Collaborative Analytics Cloud,” reflects that. The explosive growth of major social networks has reinforced this concept, as have some of the largest IT companies. IBM, which acquired DemandTec last February, uses the tagline, “Smarter Commerce on Cloud” to describe its core strategic approach.

The company’s DemandTec Connect™ social layer is a recent development in this regard. The platform leverages social-media-like interaction with embedded analytical applications to help shape collaboration across the merchandising ecosystem. Like any social media network, the platform is cloud-based. Its ability to provide role-appropriate access to a variety of optimization analytics is pure DemandTec.

© Copyright 2012 James Tenser
This article was commissioned by DemandTec Inc. which is granted the right of republication. All other rights reserved.

Call It Mobile Yellow

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Scan these tags!

I SPIED THE WHOLE grocery universe in a single bunch of fruit. This transcendental experience occurred just last week in West Des Moines, IA. (Quite rightly.)

It all happened in a bright, spacious HyVee supermarket in an upscale, verdant neighborhood that a decade ago was pretty much a cornfield. I entered the store thinking, “They built this, so I have come.”

But my Field of Dreams reverie dissolved when I stepped up to the produce department. My first view was an abundant display of bananas – the largest selling produce item in most supermarkets.

I pulled out my smartphone and snapped this picture, with the classic lyric by Donovan resonating in my brain like a prophetic soundtrack:

Electrical banana is gonna be a sudden craze
Electrical banana is bound to be the very next phase

You see, what really blew my mind were the two little stickers on this hand of bananas. On the left, a stacked UPC bar code and on the right a QR (quick response) 2D code. Each of these artifacts tells a little story about the impact of digital technology on our business. (Quite rightly)

The UPC bar code is of format known as RSS_14 designed to convey more information than old-style 9-digit codes. When I scan it with a gadget on my smart phone it correctly identifies the product as Dole bananas. Presumably the POS scanners in this HyVee supermarket are just as smart. The advantage: it saves the checker a few keystrokes and accurately enters the PLU (price look up) code for this variety of produce which is sold by weight.

The QR code on the right is used to direct shoppers to a web site called yonanas.com . When I scanned it with the same smart phone app, it led me to a page pitching a simple kitchen appliance that lets consumers make a soft-serve dessert from frozen ripe bananas and other fruit.

The Dole brand is featured prominently on the target Web page. Presumably there’s a deal behind it all. The Yonana appliance is marketed by Healthy Foods LLC, itself a division of Winston Products LLC in Cleveland, Ohio.

Peering at my smartphone screen under the fluorescent lights in that immaculate HyVee store in one of the greenest places in America, I found myself thinking, “It really has come to this: agricultural and digital have converged in America’s heartland.”

Then the digital banana concept set off a minor cascade of linguistic play: Bananas come in hands… Digit is Latin for finger… Smart phones are made with gorilla glass… (Quite rightly)

So in tribute to Donovan, the iconic Sunshine Superman inducted this year into the Rock and Roll Hall of Fame, I’d like to offer this (somewhat less lilting) variation on his theme:

Digital banana is gonna be a sudden craze
Digital banana is bound to be the very next phase
I call it mobile yellow (Quite rightly)

© Copyright 2012 James Tenser

Of Habit and Target

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THE New York Times Magazine made people nervous with its February 19th cover story by author Charles Duhigg. Its chilling headline, “How Companies Learn Your Secrets,” seems to have compelled readership as a matter of personal protection. I make this inference from the number of acquaintances who asked me about it.

[Author’s Note: This column was originally published on March 13, 2012 in the TradeInsight CPG Chatter blog.]

“Creepy” was the adjective repeated most from individuals who read about how Target Stores applied data mining techniques to shopping baskets to infer which shoppers were most likely pregnant, then sent them promotional offers for pre- and post-natal products.  Motherhood is pretty personal business, so I can’t say I disagree with the folks who were offended. What gives them the right?

Focusing on this creepy surveillance was a pretty crafty editorial decision by the editors at NYT Magazine, who used the cover line: “Hey! You’re Having A Baby!” The analytics behind pregnancy detection was actually just one example from Mr. Duhigg’s just-released book “The Power of Habit: Why We Do What We Do in Life and Business.” Having a baby, as it turns out, is one of a handful of predictable moments in life when our consumption habits change big time. For eager marketers that information is, well, mother’s milk.

Even if we look past the intrusiveness of offering coupons for cocoa butter lotion to stretchy young mothers-to-be, Mr. Duhigg’s larger thesis about the enduring nature of habit remains compelling in a different, less sensational way.

It tends to strengthen my own observations of long-lasting retail shopper behaviors, such as trip planning, coupon clipping, list-making and response to promotional cues within the store. In “Shoppers’ Perspective,” research I helped co-author for CPG manufacturer Henkel USA in 2009, we learned that shoppers could be sorted into fairly stable groups based on these enduring habits. It took the pain of the subsequent economic downturn to disrupt the patterns. As a result, coupon redemption statistics turned upward to what we may hypothesize to be a new norm.

The central example of the Duhigg article – Target’s effort to target “new natals” in its promotion marketing – is interesting too, but it offers little, truly new insight about behavioral segmentation analytics. Food, drug and mass retailers have understood the buying traits of new and soon-to-be parents (and other behavioral segments) for decades, without the need for sophisticated data mining tools. These insights are easily inferred from examining the contents of shopping baskets from the store’s point-of-sale transaction records – or better, from frequent shopper data.

It is not necessary to know individual identities, but such knowledge does enable the delivery of more personalized offers and services. These may be welcomed by opt-in frequent shoppers, but can be downright creepy when they seem to be the outcome of cyber-stalking.

The NYT Magazine editors correctly surmised that an article excerpted from Mr. Duhigg’s book could quite possibly be a snooze for readers not already fascinated by human behavior, retail analytics and segmentation and targeting. So they focused – perhaps a bit unfairly – on Target’s stalker-ish behavior toward new moms.

For us retail pros, however, divining the nature of repeat behavior is solid stuff – part of our every day thought work. It reminds us that when we try to influence purchase behavior positively, we also take on the challenge of overcoming pre-existing habit.

© Copyright 2012 James Tenser

“Omni” What? It’s Da BOMB

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IN MY MEANDERS around the vibrant NRF Expo hall (#NRF12) in New York this month, I tried my best to spot the visible stars of the show and detect the invisible three-degree background radiation that lurks behind the retail firmament.

The atmosphere was energized, the crowds were large and buzzwords were flying. Shopper insights swirled in the cloud, mobile technology hype charged the atmosphere, and business intelligence oozed out of every software booth into glowing puddles on the Javits Center exhibit floor.

Ultimately there was too much for one greying, recovering journalist to absorb. This is surely why I wound up at the bar in Manhattan’s Landmark Tavern one evening with a group of senior retail business writers (a.k.a.,”ink-stained wretches”) who gather each year to drink beer and tell lies.

The BSQ 

We talked about how NRF has become primarily a retail operations exhibition, and how that had evolved to be primarily about software solutions. Egged on by my fellowship of professional cynics and emboldened by many lagers and stouts, we began evaluating the first day’s bullshit quotient. The BSQ is a pretty simple ratio – buzzword repetition divided by genuine new ideas. (This is a party game only old journalists could love.)

The buzzwords were easy: “Insights” (every retail software solution promises better ones); “Analytics” (every retail software solutions promises faster ones); “Business Intelligence” (how every solution promises to deliver the insights and analytics); “Big Data” (what results from gathering so many insights and analytics); “Cloud” (the place in cyberspace where every vendor proposes to house its Big Data); “Dashboard” (a screen where retail practitioners are supposed to want to access their BI); and “Omni-Channel” (a state of retailing where online commerce coexists with mobile commerce and bricks & mortar, empowered by – you guessed it – insights, analytics, Big Data and BI).

As ever, the genuine new ideas were harder to detect. “Performance Management” may be a good one (the quaint notion that retailers might want to measure the outcomes of their insight-driven plans to see if they are really paying off). “Retail Industry Creates Jobs” is another, presented as a core theme by the NRF itself.

Readers familiar with basic arithmetic will quickly reason that for the umpteenth consecutive year, the BSQ on the exhibit floor was off the charts. The principle factor here is buzzword repetition, which drives the numerator toward infinity, while really genuine new ideas to pad the denominator are rare indeed.

Da BOMB
There is a lot to say about each of the major buzzwords and concepts that enlivened the NRF Expo. Right now let’s focus a little on “omni-channel retail,” which is recent nomenclature for an idea that has been around for quite a while. As far back as the dot-com boom in 1998 we began discussing the interplay between virtual and physical stores, catalogs, kiosks and call centers. By 2000 we identified several multi-channel players – like Eddie Bauer, and JCPenney – who had succeeded admirably (we thought then) in melding online, offline and catalog businesses to the benefit of shoppers.

The “shop anywhere, buy any where, return anywhere” principal was captured in the final edition of VStoreNews, where we labelled it “Broadband Merchant,” re-purposing a popular adjective. By then much of the industry had adopted “multi-channel” as the nom de jour.

At NRF this month, alot of folks were calling this “Omni-Channel,” I think because of the stunning influence of mobile technology within the mix. We can (and will!) argue long and hard about the appropriate understanding and application of mobile technology in retail, but for now let’s just stipulate that mobile is colossal in its influence. Explosive even.

Which is why I’d like to humbly offer an “omni” alternative. Call it BOMB retailing – Blend Online, Mobile & Bricks into a single entity where every channel shares a common information platform and consistent shopper interface. One brand, one shopper relationship, one inventory, one set of service standards, many moving touchpoints.

Surely after 14 years on the interweb machine, the omni-present, omni-channel, but hardly omniscient retail industry is ready to blow up the status quo.

© Copyright 2012 James Tenser