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ANALYST INSIGHT

That  Time  Data  Integration  Software  Helped    Turn  Around  the  Sears  Auto  Center  Business  

Published: September 2016 Report Number: A0261

Analyst: Toph Whitmore, Principal Analyst Share This Report

What You Need To Know When it comes to storied brands, “Sears” is about as old-school as you can get. Catalogs, retail, Toughskins, and for a while, a name on the world’s tallest building. But that’s the past. The present? A still-dominant retail giant with extensive North American retail and service reach.

Sears Auto Center is the company’s automotive service division, and operates some 650 service centers around the United States. Sears auto technicians will change your oil, fix your broken taillight, rotate your tires, even replace your DieHard® battery.

Brian Kaner is the president of the Sears Auto Center division. Two years ago, he had to confront some sobering realities: sales and margins were down, and continuing to decline.

Revenue Drop? Marketing's the Answer! (Maybe Not.) My management-consultant-stained brain hears “retail” and I jump impulsively to the “marketing-will-save-you” recommendation. (I recently noted marketing value delivery as a key success metric for data-commercialization initiatives.) I envision a cool marketing-focused data solution, with web clickstreams integrated with point-of-sale touches and regional campaign results and local AdWords spend and … sorry. Got carried away. Breathe, marketer, breathe …

Perhaps Sears Auto Center could have invested more in marketing to try to right the ship, or at least make it list a little less. But that wouldn’t have addressed the underlying fundamental business challenges. Kaner and team astutely recognized that the core of the problem wasn’t the marketing or lack thereof … it was the data. Specifically, the way the org used (and wasn’t using) it.

AT A GLANCE

Business Challenges In 2014, Sears Auto Center faced declining sales and margins. At the same time, they had useful operations data, but it was inconsistent, difficult to analyze, and open to misinterpretation.

Solution Establishing a “single source of truth” through data integration software; in this case, Domo.

Benefits • Turning around a business

suffering from double-digit declines to single-digit growth in the few months since full rollout

• Improved ability to spot operational bottlenecks, limitations, and gaps

• Better customer targeting with the same data

• More transparency throughout the business to share best practices, identify understaffed locations, and determine where employees needed more or better training

 

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ANALYST INSIGHT

Sears Auto Center’s operations performance – particularly at the regional retail level – was difficult to analyze, let alone shepherd. Different management layers had different reports, and even shared data was open to misinterpretation. In a competitive business environment, static monthly reporting was simply not dynamic enough to enable Sears Auto Center to respond to in-market regional trends. When a location’s business is struggling, it’s tough to fix things when you can’t agree on what the data tells you.

Domo and the Quest for the "Single Source of Truth"

In an effort to reduce all the guessing, Kaner teamed with Joe Richards, who had come over from the Stanley/Black & Decker organization. Their initial objective was straightforward: Establish the vaunted (and oft-quoted-by-data-technology-marketers) “single source of truth” for Sears Auto Center.

In this example, Sears Auto Center’s digital transformation hinged on two simple, relatively universal goals. (I hope these don’t become clichés, because they’re so damn important.) First, get to a point where you (and everyone in the org) can trust data, and second, be able to act on it immediately. (The marketer in me wants to say “act proactively.” Let it go, marketer, let it go.)

Speaking of clichés, this is the part where I quote (or misquote, and undoubtedly misattribute) Peter Drucker, or maybe Lord Kelvin, or possibly Albert Einstein: You can’t improve upon what you can’t measure. For Sears Auto Center, the problem wasn’t that the data wasn’t there. It was that the data was everywhere. In pieces. It was nearly impossible for anyone to trust performance metrics when it was so difficult to reconcile disparities in expectations, analysis, and interpretation.

Kaner and Richards turned to Domo, a technology to which Richards had been introduced when he worked in the Sears home appliance division. Over the course of a few months, and working with Domo consultants, they prototyped and then deployed a data-integration solution that pulled from existing systems, including HR, POS, financial, even online.

Kaner and Richards wisely focused Sears Auto Center’s operational reinvention on productivity. Their Domo deployment highlighted operational bottlenecks, limitations, and gaps they had suspected but until then had not been able to address with any certainty. They looked at cycle times, employee productivity, even retail product mix data. That new scrutiny brought a new level of transparency to the entire business, all the way from regional retail service techs to upper corporate management. Technicians with low-turn times could be coached. Best practices at one location could more easily be deployed at others. Kaner and Richards and team could also identify understaffed locations (with overwork signaled by overly-high employee productivity metrics) and add techs to reduce stockout-cost risks.

So where are they now? Marketing! (Finally.) Now that they have a better grip on operational performance (in particular, capacity for new business), the Sears Auto Center team leaders have adroitly pivoted marketing to be more tailored to regional service- and product-demand mix. For example, data sourced via Domo from POS and CRM systems enables regional managers to target customers with enviable specificity: “Six months’ ago, your tread depth was 3/32nds, and we have a two-for-one sale on your tires this weekend.”

 

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ANALYST INSIGHT

Finding Proof in the Pudding

If this were a case study about data-integration technology, this is where I’d write about how great the ROI was, how flawlessly the implementation progressed, and how Kaner and Richards are now sitting on a beach sipping umbrella drinks. (It was, it did, and I don’t know about the beach.)

But this isn’t a case study. It’s an object lesson in turning around a struggling business. It’s about establishing an operational model that emphasizes transparency, efficiency, accountability, control, and continuous improvement at all levels. Kaner and Richards and team recognized that unifying data could make operations more efficient. Automotive service isn’t the highest-margin business, and for Sears Auto Center, keeping auto techs busy, optimizing cycle times, and recognizing opportunities for upsell were paramount to success. The entire business operation was measurable. (Say it with me, millennials: It’s like a SaaS business, only in the real world!) Implementing Domo meant that the data could be interpreted accurately across the organization.

In just the few months since full rollout to the retail service level, Kaner and Richards have seen a business that had been suffering double-digit declines grow by single digits. That’s a pretty dramatic turnaround. Imagine what they’ll accomplish when they crank up the marketing even more. (Let it go, marketer. Let it go.)

Copyright © 2016 Blue Hill Research

ABOUT THE AUTHOR

Toph Whitmore Principal Analyst, Big Data and Analytics

Toph Whitmore is a Blue Hill Research principal

analyst covering the Big Data, analytics, marketing

automation, and business operations technology

spaces. His research interests include technology

adoption criteria, data-driven decision-making in

the enterprise, customer-journey analytics, and

enterprise data-integration models. Before joining

Blue Hill Research, Toph spent four years providing

management consulting services to Microsoft,

delivering strategic project management leadership.

More recently, he served as a marketing executive

with cloud infrastructure and Big Data software

technology firms. A former journalist, Toph's writing

has appeared in GigaOM, DevOps Angle, and The

Huffington Post, among other media. Toph resides

in North Vancouver, British Columbia, Canada,

where he is active in the local tech startup

community as an angel investor and corporate

advisor.

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