Data silos are a common problem in organizations. Incompatible tools (and often a dose of departmental territoriality) cause actionable information to become isolated and stuck. Information can’t cohere, and valuable insights are lost. These silos kill the ability to adapt, collaborate, and integrate the big picture. As Patrick Lencioni put it in Silos, Politics, and Turf Wars, “Silos—and the turf wars they enable—devastate organizations. They waste resources, kill productivity, and jeopardize the achievement of goals.”
Product data is not immune. Product and user data are often in the hands of one product manager or a small team, and the temptation to hoard the data is strong. There’s a fear of other teams misinterpreting the data, or somehow “going rogue,” and the fear of a loss of control. Plus, the problem of capturing, cleaning, and reporting all that data can be overwhelming. We’re afraid of diverting resources from development, of being put on the spot, and of unleashing a flood of requests for ad-hoc reports. So a minimal and patchwork approach tends to prevail.
But, whether it’s born out of technical limitations or anxiety or both, product data silos have real consequences for an organization. Imagine these scenarios:
- A customer success team is working to increase participation in a value-added service. They’re a skilled group with lots of ideas, but they’re relying on scattered and outdated product data. On the phone with customers, they’re flying blind, and they don’t know how to gauge their success.
- A group of executives are in an informal meeting, discussing the state of the company and whether product decisions are driving adoption. But they’re missing basic information. Is net promoter score trending upward or downward? For which customer segments?
- Customer support is on the phone with a customer, but the support person has no information about how the customer uses the app, how often they use it, or whether they’ve tried to access in-app help.
- UX is redesigning a page, but they don’t have access to user data tracking tools. They don’t know how users use the current interface, so they’re not sure whether they can adjust the hierarchy of elements without causing problems. The team knows there’s a tool that tracks this data, and they’re frustrated by the product team’s reluctance to give them access.
- Sales is monitoring a trial, but doesn’t have much detail about the prospect’s use of the product. They wish they could see how many of the key value drivers the prospect has tried out so far in this trial.
So many lost opportunities! In every case, actionable information is missing when product data gets siloed. In some cases, even product teams can be in the dark. It’s not for a lack of opportunity: great data exists in the CRM system, and the product generates a massive amount of data every day, but basic questions like “what percentage of top-tier, high-value customers adopt the latest features within their first 12 months of service” frequently cannot be answered.
In an information vacuum caused by lack of access to genuine user data, product data tends to play second fiddle to marketing and sales data. These data tend to be easier to gather and quick for those departments to pull together in reports. It’s also easy for business intelligence efforts to look first toward data that have a revenue line item associated with them. In comparison, product data can be tough to wrap your head around. But ultimately it’s an invaluable measure of the health of the customer relationship, and the only way to understand the interaction between customer and product.
What can you do to free the data? Here are a few starting points:
- Share access to tools, dashboards, and reports. It might seem safer in the short term to maintain control, but consider the long term benefits of letting information flow.
- Fight perfect! Many organizations look for big-bang business intelligence initiatives, but by the time the project is finished, the needs of the teams have changed. It’s better to chase “good enough” solutions to answer real day-to-day business questions.
- Conduct exercises across the organization to identify data blindspots. What are people missing? Take a more broad view of “the product” that includes all customer touch points, and exploit these opportunities to improve the customer experience.
- Work to expose customer and user level data, not just aggregate data. Aggregate data is helpful, but for people to trust the data they need to dig down to answer their everyday questions. This often means individual users and accounts. This “little data” is extremely valuable for telling a compelling story.
- Work to banish spreadsheets (or at least see them as a sign that you need to do some work). Spreadsheets involve manual work and are frequently out of date. Try to integrate the reports you are commonly asked for into other business systems.
- Put product data everywhere! Get monitors in halls and offices and iterate from there. What do people gravitate towards? Try a mix of powerful aggregate data and “personal” data (like individual qualitative responses).
- Let other people play! Instead of hoarding your systems, figure out how to give other teams a sandbox environment to browse, instrument, and report on product data.
- …and even more real-world examples of why product data is for everyone.
In short, look everywhere in your organization for the missing user data, and ask what you can do to set the data free!
John Cutler is a product management and UX consultant. His passions are UX research, evidence-driven product development, and empowering the front line to solve business and customer problems. For more of John’s writing visit his Medium profile or follow him on Twitter. He is honored to team up with longtime friend and editor Katherine Maurer, a freelance editor and poet whose work has appeared in many pretty good literary journals. She is also a graduate student in clinical psychology, and drummer in the band Again is Already.