Why data analysts need to get out of the building

Over on LinkedIn Paul “The FP&A Guy” Barnhurst wrote this post starting with a real throwdown:

FP&A needs to spend less time with Excel and more time understanding the business.

This can be expanded well outside the FP&A space to almost any professional, although we’ll focus on its applications to my “home tribe” of data analysts.

“Get out of the building”

My favorite expression of this sentiment that professionals need to shift their schedules outside of all spreadsheet comes from Silicon Valley entrepreneur Steve Blank, who likes to use the phrase “get out of the building:”

You can read more about this concept here.

Blank is particularly aiming this advice at technology founders so they can speak directly with customers and validate their products. This same idea of getting out there and speaking to the business firsthand can work for data analysts, too.

Deal in realities, not symbols

It’s still wild to me that as analysts we are expected to report on and analyze products that we’ve never seen, or provide recommendations for how a manager should run their business when we’ve never talked to that manager or experienced their business.

Unfortunately, that seems to be the case in most analyst roles. That type of on-the-ground factfinding is left to executives or field staff; analysts are firmly “inside the building” putting the dashboards and reports together to help them.

Here’s what this “division of labor” is missing: data is great. We see things in the aggregate using data that are easily missed from the day-to-day anecdotal. However, data is a mere representation of that reality. As I said in my book Advancing into Analytics, “It’s your world… the data’s only living in it!”

So if we get so caught up in the reporting, dashboards and so forth that those take priority over actually living in and understanding the business, we’ve got things backwards. Unfortunately that’s the case in too many organizations, where the thinking I guess is that data analysts just analyze data without domain knowledge…

Domain expertise is a pillar of data knowledge

Here is Drew Conway’s famous Data Science Venn Diagram, which has appeared on my blog quite a few times. I’d say this applies pretty well for data analysts, too:

It’s easy to focus on the first two, more “technical” areas of analytics: can you get the computer to do what you want? Can you use the right metric at the right time?

What gets often overlooked in this battle of technical wits are the domain-based skills: Do you understand the economics of the industry? Do you understand the operational implications? This kind of knowledge is hard to get just from a weekly report! You’ve got to “get out of the building” and learn it.

Back in that LinkedIn post, Paul offers a few ways to do this that would work for data analysts too:

1. Go on a customer visit with one of your salespeople
2. Spend part of the day with your customer service team
3. Read your 10K/10Q and read your competitors’
4. Subscribe to an industry newsletter
5. Request demos of your product and spend time with your product team

The experiences of subject matter experts is data too!

Sadly, analyst time “out of the spreadsheets” is seen as counterproductive in too many organizations. In fact, this may be the best opportunity for “data analysis” out there.

You see, we think of data as belonging in rows and columns, carefully tucked away in databases and data warehouses. In reality, far more data is unstructured and exists out in the wild. This can be images, text, you name it. It’s collected and analyzed much differently than that in a table, but it’s still data.

We are converging into the world of design thinking and qualitative research here; check out this post on what data analysts should know about it:

Get automating, then get out

So, what’s the answer to spending less time in spreadsheets and more time “getting out of the building?”

This is such a counterintuitive answer, but it’s the truth: get really good with computers. Automate your work away. At first, this means spending more time in spreadsheets. In fact, you may even be there longer than if you just did it the manual way! But automation is that rare investment that just keeps on returning.

I would hope that in the age of remote and flexible work that more managers become amenable to their analysts getting out of the building (since they’re out of it, anyway…). If you’re able to do it, let us know how you did it and how you benefitted. If you’re struggling and feel like the data is driving your workload rather than the other way around, let us know too.