In working on my latest client’s portfolio review and strategizing the pain points moving to growth areas; I repeatedly ran into the question of “…what’s our customer data strategy”? Ran it up the chain, asked around, attended sessions internally and I ended up with the verbal shrug challenge of nobody really owning it. More importantly, the leaders who I asked would not own it and on top of that had other priorities. Crucially, I could see the need for an enterprise-wide strategy (if possible). If not, then at least a better direction on how to scale and integrate so many parts feeding a shapeless hole of what or who our customer is. So, I dug in and went at finding out what could fit an uncertain strategy.
Gap Analysis/Research
The first step was defining what we are missing. I did my own internal research and analysis of our spending plans, and operational and capital expenditures. We have data lakes, data warehouses, data hubs, sales data hubs, eCommerce components, middleware, operational data, forecasting, loyalty, pricing – reams of data but no clear insight into what or who our customers are. Personally, I like to do recon and innovation to see what might fill or augment the gaps. So, off I went to CIO conferences, segmentation sessions, webinars on marketing funnels and how to acquire and keep customers. They were a start, however not a clean fit for our multi-faceted business model. I found potential solutions from multiple markets: transportation, logistics, hospitality, technology, travel, and retail. Nearly all the solutions say they are agnostic technology or platforms (more on that for a later post). That wasn’t the issue; it’s determining what solution we can hire, retain, and execute on. Based on our capital and operational spend, I focused on the discovery and (minimum) viable products to contextualize our customers into segments and predictive decision-making models with AI, ML or RPA to assist the manpower gaps.
Governance, Vision & Knowing What’s Achievable…
Like any endeavor that pushes the envelope into new territory, I needed to know my leadership’s limits. Years ago, I began using this calculus in consulting that has been very apt: 2 versions of ROI = Return on Investment and/or Return on Influence. Perhaps it’s one or both, but when getting approval or asking for forgiveness, this has proven to be quite successful. Any proof of concepts or new directions in innovation would need a future governance model and milestones that are achievable.
Seems Easy…Look at the Landscape and Pick
Choosing one (or many solutions) to begin a Proof of Concept on is always a dicey proposition. I wanted to have free reign on examining potential insights or outcomes of the data models but not waste time on dead ends. I narrowed the scope of test data to match my vision of what a multi-faceted customer of our business could be. The compute power or cores cost, type or formatting of data, ML learning time and UX/UI weighed in on the discovery.
Beyond the Integration, Governance and Crafting the Vision of What Our Customer Data Should Be – Politics, $ and Fiefdoms
My data points and overlaps were/are (still in process) focused on sales channels, loyalty and new customers, digital footprints, eCommerce funnels, and physical locations. I chose them because they cover large parts of my leadership’s portfolios and do not specifically identify any as a weakness. At this point, the more buy-in I have the better. My plan is to be able to have enriched data and insights with a projected drawdown on labor for too many enterprise systems.
You can see why defining customer data strategy is crucial, but also a complex task. Have you done this in your organization? Are you planning on doing this? Please share your wins and takeaways. I look forward to your feedback.
About the Author:
Oren Gruber, Director of Strategy at Amtrak
With over 15 years of experience in various roles in IT and management consulting, Oren is a strategy and business transformation leader currently working at Amtrak (a $4B company) as the director of the strategy and digital workforce to grow and lead teams to execute a portfolio of high priority, enterprise-wide efforts in Customer Data Strategy, Innovation, and Product development. His key focus is on developing a strategy for customer data, innovation of technology and engineering, business plans and enhancements across the organization.
Prior to Amtrak, Oren served as a senior advisor at BayFirst solutions and a senior management consultant at Atlas Group.
