Episode #124: Navigating people, politics and analytics solutions at large companies with Alex Kolokolov

This post originally appeared on the KeyCuts blog .

We sometimes forget that a large organization is composed of groups and divisions. Within these groups, there are teams and individuals looking to advance their careers. Sometimes at the expense of others. When your advancement depends on the success of your project, the benefits of that project to your company may be suspect and the tools you use to complete that project may not be the best tools for the job. Alex Kolokolov started his journey in data like many of us: in Excel. He moved on to Power BI, PowerPivot, PowerQuery, and building data visualizations for the last 15 years. In this episode, he talks through consulting with a company as the analytics expert only to find out that the the underlying forces at play were company politics. He also discusses strategies to make your line charts tell a better data story.

The state of analytics at companies in traditional industries

Alex consults with large companies in "traditional" industries like oil, gas, and mining companies. The state of analytics and knowledge of analytics is not equal in these companies, according to Alex. You'll come across data science and AI groups at these companies who are, indeed, working on the cutting edge. But then when you approach other departments like HR or operations, they are still quite far from this digital transformation that everyone's talking about.

Alex worked with a mining company where there are cameras that can ID employees using facial recognition when they walk through the door. But when you sit down with the folks who are actually doing the work at the plant, they are still humming along on Excel 2010. Excel 2010! What a time...

In terms of creating dashboards, teams from these companies would consult their IT or tech team to create a report. But then the IT team comes back and says it will take three months to create this report given their current backlog. Hence the reason these companies outsource the analytics training, metrics collection, and dashboarding to people like Alex.

Internal battles for power and platforms

Alex once worked with a government institution and they were building an internal SQL data warehouse before Power BI came on the scene. This specific project was driven by IT as a warehouse solution for the finance department. a few years later, the head of this SQL project became the CIO, but started getting some pushback from the heads of the finance department. It turns out the finance department heads already had their own platform in mind and claimed Microsoft's technology was outdated for their purposes (the finance team wanted to go with Tableau to build out pretty dashboards).

The finance department proceeded to roll out their solution in Tableau and the CFO eventually became the Chief Digital Office and pushed the CIO who was spearheading the SQL project out. The project wasn't about Microsoft vs. Tableau at all. It was all about who was better at playing the game of internal politics and fighting for the resources to get your project across the line.

When digital transformation is 10 years too late

Large companies Alex has worked claimed they went through "digital transformation" but this was back in 2012. When Alex started working with these companies over the last few years, he found that individuals were still using SAP and Excel 2010. It's as if the digital transformation didn't go past 2012, and whatever tools were brought in at the time were meant to carry the organization for another 20 years. We've all seen this story. Large companies and enterprises move slow and digital transformation sounds nice and warm, but execution is where organizations may lose their place.

In my own experience, teaching someone an Excel keyboard shortcut that saves them X number of hours per week of manual work is a pretty awesome feeling. It's a visceral feeling of knowing you are having a direct impact on the person's productivity. Alex has done the same thing at these large companies which, at the heart of it, is explaining somewhat "technical" concepts in an approachable way. If there's one lesson Alex has learned over the years from helping people stand up dashboards, the one advice he always gives is: don't insert new columns. Adding new columns may ruin the way the data is laid out (if its a time series) or affect the look and feel of a dashboard.

When your line charts look like spaghetti

Alex published a blog post late last year called When Charts Look Like Spaghetti, Try These Saucy Solutions where he provides different strategies for "untangling" your messy line charts. The goal is to have your audience walk away with the key message from the line chart. For instance, you have a line chart where it's hard to detect trends (given the number of series on the chart) so you can selectively highlight a line (and gray out the rest) to make a point:

Another option is to simply break out each line into its own mini chart:

The one skill Alex believes analysts and dashboard creators should learn is compromise. If your visualization is overloaded with elements and colors and your target audience says they want to see all the data, you'll have to find ways to give them what they need and highlight the story. Imagine this scenario:

An analyst is tasked with plotting more data on a chart by their superiors and so the analyst goes off and makes more charts. Eventually, the analyst realizes there are too many charts and decides to make the dashboard an interactive dashboard with interactive filters and Slicers . This allows the target audience to manipulate the data however they see fit. But does the target audience even know how to use the filters in the first place? Do they know it's something they are supposed to interact with. There's a mismatch between what the analyst wants the dashboard to do and what the target audience expects (consume vs. interact).

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