As a data leader, it is important to know your audience. They are the people consuming your data products and using them, hopefully, to make better decisions. Their preferences extend beyond the substance of what you provide them, to how they consume that data, in what quantity, and how much interactivity they are allowed (or expected) to have in exploring it. Understanding and accommodating these preferences is critical to ensuring your users get the full value from the data products produced by your team.
I find most data users fit somewhere along what I informally call the Apple/Salesforce spectrum. Salesforce is well recognized for providing enormous flexibility to its customers. They maintain several different versions of their CRM system and are slow to deprecate features. At the time of writing, they have over 20 versions of their API listed in their documentation. They integrate famously well with just about every other sales tool, and individual users can customize their experience in depth. This ‘give everyone everything always’ philosophy puts control and choice in the hands of the user.
At the other end of the spectrum sits Apple. Apple is well recognized for aggressively paring down and removing features seen as redundant or unnecessary. They tend not to follow mass market trends or user feedback, but rather take the lead on what they believe to be the right path for a product, even if it is controversial; like removing a headphone jack, or keeping a tight grip on the 3rd party app ecosystem. This ‘tell the user what they want and do not give them anything else’ approach keeps control and choice very much in the hands of the product owner.
These approaches have parallels when it comes to working with data products. Consider two SaaS sales leaders in similar roles, interested in their team’s performance. One favors the ‘Salesforce’ approach, the other ‘Apple’. Your goal is to ensure they have the data they need to do their job effectively, presented in the manner most appropriate for them.
When working with the ‘Salesforce’ style leader, it can help to take an iterative, collaborative approach. They may appreciate comprehensive reporting with filters and in-depth analysis on different topics; reporting that they can explore themselves. They may regularly request additional data points and they tend to be more quantitative in their thinking. Not only do they seek out analysis, but they may also carry out some basic analysis themselves. Providing them with ample choice and space to get hands-on and explore is the best way to satisfy these users. When nurtured appropriately, they can become advocates or champions for the use of data on their teams.
Working with the ‘Apple’ style manager requires a different strategy. They don’t necessarily want any data at all, so it is important to limit choice and keep things simple to ensure engagement and that data is utilized effectively. A simple high-level report may be sufficient. The right enablement is key; by framing the data product in a focussed and specific way, they can get value out of it quickly and effectively. These folks are generally not anti-data; they just do not yet have the time or inclination to explore data in detail themselves.
Users may not always fall into one of these extremes, but understanding how much a user wants to explore versus ‘be told’ is fundamental to putting data into their decision-making processes. It is worth spending the time to figure out where your key users sit on this spectrum and working with your teams to strike the right balance in your data products so that all your users have what they need to make better decisions.
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