I began my career in retail technology in 1992, a few years before Amazon began selling books online and would, as we all know, go on to forever redefine retail and consumer behavior. In all that time, data about customers, inventory, service, and marketing simmered below the surface of retail organizations — never rising to the level of prioritization that would have empowered us to leverage it to full effect.
But now, prioritization and integration of that data is at a rapid boil, and is already separating retail’s winners from the also-rans.
Why did it take us so long to prioritize something that was, largely, right under our noses? And is it too late for those who are just now waking up to the power of data? Spoiler alert: no.
As was the case when I began my retail career at Lowe’s Home Improvement, many retailers notoriously take a best-of-breed (rather than a holistic, integrated) approach in the way we build and deploy applications. Over time, this results in enormous technology debt and mountains of information stored in dozens of silos across an organization; marketing information in one place, customer service in another, inventory in another, and on and on.
This makes it impossible to build an integrated, seamless customer experience. Indeed, Salesforce research shows that, on average, retailers use 39 disparate systems to manage consumer engagement, including point of sale, mobile, call center, email marketing, social media, and more. That’s a lot of technology — and a lot of potential for crossed wires.
The legacy systems we relied on then and now were not built to support connected consumers and the myriad channels in which they shop. These systems often take a siloed or one-dimensional view of the customer to address a specific interaction or behavior. In short, these systems often serve the needs of the retailer, but not those of the customer.
This is a huge challenge for retailers.
Another issue is cultural. Historically, data governance just hasn’t been prioritized as something that can drive the retail business. It’s not sexy, and it’s not one of those things that you can go to business leaders and say “hey, look what we’ve done with our data” because it’s so under the covers.
There’s also the problem of, ahem, “unofficial data sources,” where departments collect and store their own data in isolation (circumventing whatever governance exists) and use it to achieve their own goals. This, of course, results in more than one version of the “truth” and hampers an organization’s ability to react accurately, in real time, to external or internal machinations.
Good data governance is what drives the ability to deliver meaningful customer experiences. With today’s focus on customer experience, the Internet of Things (IoT), artificial intelligence (AI), and machine learning, the data has to be right, and the data hygiene has to be right. That’s why, seemingly all of a sudden, master data management has become en vogue in retail and consumer goods.
Complicating matters is that no one person or group has been designated as the “owner” of the data or customer experience. Every constituency owns a piece, and wants to protect their turf. I’ve seen it.
Have you ever wondered why you see a particular description and product benefits highlighted online, but the store signage for the same product seems to be talking about something entirely different? Look no further than data governance.
I know as well as anybody how difficult it is to shed the vestiges of the past. Retailers (typically a risk-averse crowd) have decades of legacy infrastructure and ways of operating that are so ingrained, and the data governance issue looming so large, they may be tempted to simply throw up their hands and do nothing.
You must find a place to start. I recommend choosing one experience you want the customer to have, and focus on that interaction point. Where does it originate? Where is it falling short? Once you see precisely where you’re going wrong at one interaction, you can course-correct there, and build on that one example to start your journey. Here are some other pointers:
While thinking small in initial focus, think big picture in how you want to connect or integrate applications, data, and devices. Your efforts should move you along this path, not perpetuate a failed status quo.
Establish a data governance model with an internal group that oversees data.
Don’t ignore the citizen developer or the line of business developer. Embrace them, and provide the right tools and application program interfaces (APIs) that not only make their job easier, but also enforce data integrity.
You’ve got to get into the plumbing to understand your data and how it relates to your customer’s experience. And when building these experiences, remember you’re building them for the customer, not for yourself, so it’s critical to understand your shoppers and the path they take to discover and engage with your brand. If you don’t, you will never deliver an experience that truly resonates.
Fortunately, technology exists now to really deliver a holistic, data-driven customer experience. An API-led approach, for example, empowers you to quickly stitch together disjointed applications, and to bring in new channels of engagement (e.g., mobile, IoT, kiosks) much faster when they come online.
I should know. My team did this while I was CIO at L Brands.
Working with Mulesoft specialists, our L Brands team developed a layered approach to APIs (system, process, experience) that greatly expanded the number of developers who could develop and consume APIs. This significantly increased throughput and speed. Contrary to what many would believe, even with more developers building APIs, our quality improved as the layered model took advantage of true subject matter expertise.
Faster. Better quality. More downstream agility. Yes, please!
To my peers, I don’t have to tell you that our world is changing at a blistering pace, where yesterday’s innovations are today’s table stakes. The reality is that the data deluge is going to get even more pronounced as everyday items get connected and voice assistants make it infinitely easier to discover and engage with brands. That makes data governance, with integration of customer-facing touchpoints at its core, all the more urgent.
With an API platform, you can take the systems that have served you well and make them work for you rather than against you. The answer is a solid data governance program built around an API platform designed for change.
Nobody said it was easy, my fellow CIOs. That’s why the change must start with you.
Watch Steve discuss this topic live at Dreamforce: