How to get organisations to be better at using data

Ben Proctor
Data Orchard CIC
Published in
4 min readNov 22, 2018

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Photo by Josh Applegate on Unsplash

Spoiler… it’s not about tech or skills.

Data is great

There’s been a significant increase in the appetite for data collection, analysis and interpretation in the public sector (or at least the bits of the public sector we deal with).

This is good stuff but, as regular readers may be aware, we argue that the main barriers to getting better with data are not technical or skills based, they are cultural. You can have as many dashboards as you like. You can recruit as many data scientists as you please. But dashboards don’t change anything. Nor, shock horror, do data scientists. At least neither change things by the fact of their existence.

I am specifically aiming this post at business analysts, researchers, performance teams etc. The sort of people that really care about data and are locked in the corporate centre with their Excel, PowerBI and R installations (or maybe dispersed across departments with their Excel, Tableau and R installations). But the general concepts of encouragement vs praise are useful to managers, professional leaders and, basically, everyone.

Getting better means behaving differently

Ultimately what we need is for individuals and teams to change their behaviour as a result of the data that they, or the business intelligence team, gather and analyse.

The factors that affect our behaviour are complex, highly culturally determined and affected by our history and experiences. It would be naive in the extreme to believe that simply presenting people with some numbers on a graph would lead to radical shifts in behaviour.

Instead we should think of data as a form of feedback most effectively provided over a long period.

And when providing feedback we need to understand what sort of feedback we are providing.

Encouragement vs praise

As an analyst you are in the business of giving feedback to teams. Feedback can be presented as (and received as) in the context of encouragement or praise.

Encouragement
Encouragement is given in private, it focuses on effort not attainment, it encourages the recipients to own their actions and to link their actions to the outcomes for customers / service users.

Encouragement is when a coach takes a runner to one side and quietly says “do you see how all that work in the gym has paid off today”. Encouragement is when a manager sits down with a planning officer and asks them to reflect on what they have learned over the past 6 months and how that has affected the quality of their work.

In the context of data: encouragement is where individuals see the data as a tool they can use personally to understand the impact of their own effort. Encouragement is where individuals see the data as linked to their actions and to the impact on customers.

Encouragement is likely to be effective in helping people shift their behaviour as a result of the feedback.

Praise
Praise is given in public, it focuses on achievement not effort, it encourages the recipients to link the consequences of their work to their status amongst their colleagues and peers.

Praise is when a coach singles out the runner who, once again, came first in the race in front of everyone in the club. Praise is where a manager in a team meeting points to a planning officer and says “the chief executive was very impressed with your work on the Marchford case”.

In the context of data: praise is where individuals see the data as an external system by which they will be rated (league tables, awards, nice letters from the Chair). Praise is where data is something that is seen as unrelated to the work but just measures the (usually arbitrary) outputs.

In short encouragement is helpful in promoting a data-driven culture. Praise is unhelpful.

So if you have the role of providing feedback (data/analysis) to other individuals and teams think about the context in which you provide that feedback.

Praise is likely to entrench or strengthen existing patterns of behaviour.

Do you encourage?

As a business analyst/performance specialist:

  • Do you work with individuals and teams to understand how they work and what their challenges are?
  • Do you tailor your commentary on monthly reports to the individual emphasising how the data reveal the relative impact of their efforts?
  • Do you present reports to people in such a way that they can clearly see the link between their effort, the output and the impact on customers.
  • Do you fiercely resist the use of performance data to provide a mechanism for the celebration of success?

Carry on, try to do more of this sort of thing. You are moving your organisation up the ladder of data awesomeness.

Do you praise?

As a business analyst / performance specialist:

Do you share the feedback in public? For example

  • circulating reports on an big email list
  • presenting monthly data at team meetings
  • (even worse) sending reports directly up the management chain

Do you emphasise the importance of hitting targets and ensure that success against metrics is celebrated across the organisation.

So far as you are able: Stop it. It will not help and you are making things worse.

Encourage yourself

Reflect on your own behaviour. How effective have your efforts been in changing the behaviour of the teams that you support? Don’t worry about what the boss sees, consider what you can evidence. Try new things and reflect on what the data tells you about the impact. Stop looking for praise. Look for encouragement.

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Ben Proctor
Data Orchard CIC

Data and digital innovation director at Data Orchard CIC helping make non-profit organisations awesome at using data. Like maps, open data, dogs, bikes & boats.