Data Product in Changing Environments: Rethinking and Updating Investments
Today, I wanted to revisit an earlier article I wrote, and elaborate on what it means to to evolve a data product as personas (and organizational needs) change. Why? Because as I think more about this space and reflect on the current environment, my own thinking changes and I hope it can be useful to share.
In one of my first data science roles, I sat near the marketing and sales teams. There were two amazing people in those groups that I talked to every day. They were highly successful at the company, commanded the respect of those around them and were viewed as de facto leaders in the space. So when they asked me to build a dataset and corresponding dashboard for them, I didn’t think twice.
I wish I had. The dataset and the dashboard took me a solid month of extra work. I put all of my extra time and even worked over the nights and weekends to push it over the line. The day I showed it to them, they were elated! Then they both left the company in the next month. No one ever touched that dashboard again.
I was pretty upset. I actually got quite frustrated with sales and marketing. After all, I had built something outstanding, right? Nope. I built something for specific people, not the personas they represented. Here’s what I mean by this:
Personas are general representations of a user or customer. We build personas to represent different user types and characteristics of those users that use the product we build in a consistent or similar way. People are not personas. An individual person is full of nuances and unique background, intentions and training. We need to actively create personas, we do not just “find them”.
So what exactly did I do wrong? I did not stop to think about what general needs and desires the sales and marketing teams’ requests represented. I did not spend time thinking about whether they represented a general need for all of sales and marketing or if they were one off requests that served the needs of those particular people. But I didn’t know this. I just wanted to help. I wanted to add value.
This desire to help without thinking about personas is exactly where data products go off the rails.
The builders of the data products are well intentioned. They are trying to do their best. They are listening to customers. It just happens to be the customers they are listening to are the loudest in the room and often those they are most familiar or comfortable with in the organization. We need to work actively against this tendency.
Here are 5 things I suggest organizations consider to think about personas, not just people:
Spend time defining the key personas in your organization that use or are impacted by data products. It is much easier to define these personas upfront that do it in an intense moment of planning or prioritization where time and patience are often much lower in availability. If you have these personas and socialize them in your company, you’ll be much better off when it comes to hard decisions.
Centralize the decisions about what to build either in a product management, project management or some other variation of them. There will always be embedded data teams but that does not mean the decision about what they build needs to be embedded. The more eyes you have on a data product decision, the more likely it will be the questions about what general personas it addresses will arise.
Push actively against the “Person X wants us to build Product Y” mentality. Many organizations I have been a part of justify product decisions with a name of someone who wants it, rather than the personas that they product actually serves. Specific people and decision makers are temporary at companies, but personas are long lasting. Ask about the persona. This is where having the personas laid out already pays off.
It sounds simple to say focus on the persona. But power structures in an organization are a very real thing. It is hard for a data scientist or product manager to tell a VP that the product doesn’t clearly address a persona. This is where leadership matters a great deal. If you want to see change in this space, it cannot just be put on individual contributors. Leadership needs to sponsor these ideas and these processes.
Be patient. Changes like this take a lot of time in most organizations. The decision making processes that often rely on highest paid person in the room or biggest title in the room are fairly well ingrained in corporate culture. Even asking about personas might be strange at first. But we need to start somewhere. If we don’t ask the questions now, we have little chance of real progress later.
Additional, Present Day Thoughts
As I look back on this post and the thinking that drove it, I realize that the thing I took for granted was stability. Well, looking around us now, stability is the last thing we should probably assume. People changes are the norm, not the exception. Growth is giving way to “keep the lights on”. Businesses are pivoting quickly. Areas of investment are being cut as companies try to lower burn rate. That is to say, the world in which we build data products for 6 months ago is likely not the world in which we work today.
I thought it would be useful to share some key questions I’ve been using to think about continuing investment in data products in a fairly tumultuous environment. Specifically, how to think about “who benefits” and how to support them.
Hone in on a sponsor, hopefully part of the “personas” you’d like to support. It is not important if I think the data product matters, the key is answering “who is the organizational sponsor for this product?”. We may have built something a year ago that the head of marketing loved. But that person may no longer be around. We may have built an amazing dashboard but that area of product is no longer someone’s major areas of focus. In an environment like this, it isn’t just important to identify the persona that benefits, but also critical to identify the person in the company who will say “I absolutely need that”.
Don’t be afraid to prioritize personas. In a growth environment, capital and people seem unlimited. We spin up new teams and capabilities because “things are really business critical”. It is actually stunning how easily investment happens. We need to be just as aggressive in dropping things now in a slow growth environment. Not everyone can get everything they want. There simply isn’t enough time and investment to go around. This likely will produce some hard conversations, but it is critical to set expectations and say what is being prioritized and what is not.
Plan for what you’d drop, not what you’d add. The last few years have been full of “here’s what we need to do next” or “once we have this team, we can do this”. We plan how we’d support more personas and areas of the business with more investment, but we don’t think about what we’d do if we had to cut support. I get it. That doesn’t feel very comfortable. But just like succession planning for people, we need to have a plan for what we’d do in hard situations. In some cases, you might drop support for particular personas on a product. In others, you might drop support for a product altogether. It isn’t easy to say what the “right answer” is. But spending time thinking about your answer is important.
If your company deprioritizes an area of investment, think about how your product investment should reflect that (or not). It is really common for a company to pivot investment in an “area” (which might be a key persona for your product) but the rest of the company does not quickly update to reflect that pivot. Specifically, you might have close relationships with key stakeholders who tell you “yeah, that isn’t important to the company, but I need it to do my job.” Be very wary of this type of situation. By focusing on people, it is easy to get confused about “what matters”. By focusing on where the company is headed and how different personas are part of that, it is easier to think less through the lens of working relationships and more through where the company needs to go.
I have to be honest, my thinking here is not as clean as I’d like it to be. But as I read this post again last week, I realized that some of the biases and assumptions I had made in writing it needed to be updated to reflect the environment we are in now. I suppose that’s going to be a theme of this newsletter over time - constantly updating beliefs based on evidence :)
Thanks for reading!