The Optimization Arc – From Black Box to the Cloud

Joshua-CloudsWHEN 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.

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

“Omni” What? It’s Da BOMB

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

Tenser Presents Webinar on MPM

NARMS Webinar Merchandising Performance Management

IMPLEMENTATION means to carry out; to give practical effect to and ensure of actual fulfillment by concrete measures. In this NARMS Webinar, James Tenser takes a look at new considerations in the ever important issue of implementing marketing plans at retail. The hour-long session is another event in the NARMS-U educational platform titled – What is Merchandising Performance Management? The webinar, sponsored by Natural Insight, will take place Thursday, December 17, 2009 at 1:00 P.M. CST and is brought to you through the technology of ReadyTalk.

© Copyright 2009 James Tenser