Data & AI: It’s (still) all about the customer
Lessons from the branch for scaling up Data & AI at Reece
Data & AI at Reece is at an exciting inflection point — poised at the heel of the proverbial growth hockey stick. As the core Data & AI practice is coalescing, ‘customers’ of our services and capabilities have growing enthusiasm (off a high baseline) for realising the value of data in improving operations, decision-making, and service innovation. The primary challenge at hand is ramping up, ramping in a sustainable way, and ramping the Reece Way.
What got us here won’t get us there
Our team works with a strikingly diverse swathe of the business — operations, marketing, pricing, finance, logistics, people experience, reecetech through to our C-suite — each with unique needs, and each deriving value from data in different ways (e.g. direct & enriched access, analytical tooling). Many at Reece have experienced the ebullience of early success on their data efforts, stoking demand for more. Demand that will require the Data & AI practice to use advanced analytics, data technologies, and cloud platforms to empower the business to make better decisions — for delivering personalised customer decision support, optimising prices for thousands of products across hundreds of locations, and creating new data-backed products. To paint a clearer picture of what exactly is needed to scale, we’ve begun characterising the growing volume and complexity of requests alongside our strategic priorities. But more than just contemplating data-intensive technologies, we’re being driven to re-think the backbone of our business.
It’s (still) all about the customer
At Reece we make no secret the customer is at the heart of everything we do, but Branch Time really brings this to life. One month on from my stint at the Caulfield branch, I haven’t tired of talking to anyone with ears about how our people live out a customer mindset every day. Often, the impression is that delivering a great experience is giving customers what they want. But deciphering what customers actually want (and what they need) is a less probed topic.
Perhaps this is a by-product of delivering such frictionless experiences that the ‘natural’ explanation for our success simply revolves around the surface-level observations: “customer-centric = customer-wants-it-now + customer-get-it-now” — a simple linear equation. However, to accept this explanation is to greatly undersell the subtle, but truly valuable skill that has been honed over a century in our branches; skills that upon reflection I realise are also critical to ramping up intelligent data use at Reece.
Branch Time lessons for Data
“What are they actually saying?”
was Team Caulfield’s frequent response to my pleas for help while serving a customer. In trade services (especially plumbing), problems arrive through our doors/phones like patients in an emergency department in need of triage and diagnosis. Behind any request for plumbing supplies can sit a high-stakes work-site situation, where a crew is actively trying to solve a conundrum behind drywall. What we hear though, are just supply requests — our branch teams are prodigious in their ability to infer, from just part names, what the real problem is (“ You want a P-trap.. hang on, there’s only that much space between the cistern and the wall? Nah mate that doesn’t sound right..”). Having distilled the problem, they work tirelessly with our customers to deliver what they need, as soon as physically possible.
There are many parallels in data. Across virtually any domain, more often than not a data problem/request often presents first in the form of prescribed action (e.g., “I need you to build a random forest model”) — yet the value sought is in the true, unarticulated / unformed need (e.g., unsaid: “We really want to understand cross-channel conversion attribution”). What defines a Reece-like experience in data, therefore, is our ability to (1) navigate from the customer’s prescription to their need, (2) place greater importance on sound solutioning than under-considered issue closure. To do this well, we must take a genuine interest in our customers’ problems, and we must be postured to treat their problems as our own.
“Let me make you what you need”
is the typical extension of a problem-solving conversation at Caulfield. To this end, what I observed was sheer mastery in play: fine-grained knowledge of the make, mould and application of over 5000 in-stock goods, enabling the team to configure bespoke, yet exact solutions, en masse.
Again, this is analogous for data: we need to be really skilled where it counts. All data consumables, from dynamic reporting to data products, call for much more complex craft than can be assumed in job titles. Just as branch counter staff are called to a greater capability than routine payments-processing, so are data engineers building customer products and services, who must embed a deep care for ethics, data security and privacy in their craft on top of sound engineering skills. A less discussed, but defining skill of masterful data practitioners is the ability to reason about the second and even third -order effects of architectural decisions made now, and how these impacts will play out years into the future.
Creating joint agency
Underpinning these productive collaborations is the joint agency we have created with our customers. Our branches’ exceptional understanding of their customers’ businesses is well-known; but our customers have just as rich an understanding of Reece as an enabler of their success. I believe this is how we deliver a Works For You experience across over 800 branches, and that the same is needed for our Data & AI practice to drive high-integrity, intelligent data use at scale.
As a coda, Data & AI at Reece is filled with opportunities to shape productive partnerships with the wider business, our customers, and our customers’ customers. The heel of a hockey stick is a daunting, but exhilarating place to be — if you’re a skilled and thoughtful practitioner with a passion for building long-lived data solutions and teams alike, I’d love to connect.
