Whatever your position — whether you work in HR, consult others or handle the company finances — the need for data is ubiquitous. But only a few of us have direct access to it. As one of these lucky experts, I get lots of requests for reports. I thought it might be helpful to share a few thoughts on how to ask for data to get the results you need.
Here are the two most common mistakes I’ve found people make when asking for data:
Providing a detailed description of the exact report you need. At first glance, this seems like a great approach! My experience is that: (a) this kind of request is not interesting; and (b) you are not taking advantage of the analyst’s expertise by asking them to creatively address your need.
Not giving context. People often describe the data while completely leaving out the most important part: the context of the request!
You Don’t Know What You Don’t Know
When we ask for data, we have an idea of what we want to accomplish. But we don’t know the process of getting the data. Trust me, it can be way more complicated than you think. There are usually multiple sources of data. Each source has its own history, limitations, and nuance. Sometimes data you think should be readily available is nowhere to be found. Other times there is valuable data available that you had no idea existed.
It’s OK to trust the analyst to solve your problem without being given explicit instructions. Analysts love to solve interesting problems, and staying at a high level with your request will give them a chance to sink their teeth into the project while giving them the freedom to use their expertise. They’ll have the autonomy to run with it, think creatively, and have some fun! So be specific, but only to the point where you are being helpful. Never restrict your analyst.
The Importance of Context
I don’t think that people understand how important context is to an analyst. Without context, revisions will almost certainly be necessary.
Contextual detail is much more useful than specific detail. If I know context, I can fill in the blanks.
Consider these two options for requesting a report:
“Can you give me a report of customers who have interacted with us in the last 12 months?”
“I need to send a targeted email about a new product we are launching in Oregon. Can you give me a report for this?”
The first request doesn’t give much to work with. To actually pull data, the analyst needs a lot more than this. What counts as an interaction? For these customers, what information do you need? Do you need email addresses? Should we remove customers without known email addresses? The report that comes back likely won’t be enough.
The second request, while still a bit slim on specifics, provides enough information for an analyst to put a report together. It gives them freedom to scour all the available data and pull the information they feel is relevant. They get to think creatively and feel that they are an important part of the team working on the project.
In order for any of this to apply, you really do have to have a great analyst. Someone who loves their job and can take initiative to solve a problem without step-by-step directions.
Develop your analysts. Give them context and bring them fully into projects so they can build intuition. Challenge them to grow by not giving explicit instructions and allowing them to think creatively. It may slow things down for a period, but this is a strong case of “slow down to speed up” and you will be much better off when your analyst can work autonomously.
Bryce Chamberlain, Senior Information Analyst for Sales Operations at Vitality— data whisperer, credentialed actuary, and developer.
A longer version of this post originally appeared on LinkedIn Pulse.
