Understanding Your Data Is In Every Employee’s Job Description

There was a time, in the not so distant past, when companies would employ a data team. It might have been known by other names - ‘Business Intelligence’ maybe, or ‘Analytics’ - but the goals were similar. These were the people who could ‘build a report’ for the CFO, ‘crunch some numbers’ to ‘get a deck together’ for a sale presentation, or ‘work til midnight three nights on the run so the CEO can speak with confidence to the board on an important subject they really should have no business talking about’.

They were where the data lived.

Time went on and these data teams got more sophisticated; they collected data in a single place so it could be reused, modelled it, moved it, aggregated it, and ensured its quality. They owned it. In fact, they would have so much ownership over the data that no one else in the company could do anything with it.

The Mess, Shame, and Tragedy of Hidden Data

Without sophisticated SQL skills, the sales team couldn’t pull a customer revenue report. Without setting up an ODBC connection, marketing couldn’t measure how well the latest campaign had performed. Instead, they’d get a weekly, or daily if they were really lucky, puke of data in their inbox and be left to fight over which team had the ‘right’ numbers.

It was messy, it was a shame, and it was tragic.

It was messy because having multiple sources of data in different places meant that no-one could agree on what data might mean.

It was a shame because it meant that the expensive, time-consuming work the data team had done was wasted. Employees still had to rely on anecdotes, ‘sniff tests’ and guesswork instead.

And it was tragic because not knowing what data meant left highly skilled team members unable to succeed in their jobs.

The Crazy, Free-Wheelin’ World of Self-Service

Luckily, it got better. We’re not in that situation anymore. (If you are, get in touch. We can help.)

Data analysis is easy to produce and share. We have simple, powerful front-end products like Tableau, Looker, and Power BI that surface data to anyone who wants it. People can pull data, measure their KPIs, analyse their performance and share with their peers or the wider world.

With more data, employees can look at their role in the business with a new perspective. They can pinpoint where they can affect change and see where they can improve performance. They can gain ownership, align themselves with other groups to work towards common goals and quickly identify where they are going in the right, or wrong, direction.

In its ubiquity, data has become a new language; bar charts are cut and pasted into marketing decks, pie charts plastered over infographics, trend lines worried over. Data is everywhere and we can measure anything.

Far from being a rarified preserve of a specialised team; businesses in the 21st Century are swimming in a glut of data.

Modern Employment Is Dependent on Data Literacy

But what happens when that data is wrong, or misunderstood?

Is that average savings per customer metric you are leading your sales pitch with accurate? How do you know? Does the axis on your growth chart look like this? Are you defining your successes with a kpi that can’t be affected by anyone on your team?

What happens when one part of your company understands a metric to represent one thing, and everyone else thinks it means something else?

The availability of data has led to a growth in its impact, but sometimes it’s just… wrong. More data does not necessarily mean better data.

Expecting people to measure their daily work and use data to improve it means that they must have modern data skills. This can be simple statistical knowledge (understanding the difference between mean and median, for example), or a comprehension of how data can be represented visually - and how it can be manipulated to show a particular viewpoint.

If people understand the importance of metrics, how they are derived and what they mean to their daily workflow, they will be empowered to ask questions, dig deeper, and share knowledge. Experiments (not just online) can be attempted with confidence and people will know when they have failed more quickly, getting them back on a successful track.

A Common Language

When you define your company successes through data your employees can only share in that success if they have a clear understanding of how they can influence it. That means understanding how their work is measured and how they are judged. It also means defining their relationship to the data they produce, consume and change, and how that data fits into the bigger picture.

To talk about data in that way requires a shared understanding, a common way of communicating ideas. Something as simple as a data dictionary, giving clarity around data, objectives and the metrics that support them, will reinforce a team’s common purpose. Company metrics must be calculated transparently, business objects clearly defined. A company where everyone in the team shares a common understanding of its targets - of what makes the company move - can align goals, have simpler conversations and more success with data.

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