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Want to improve performance? Improve your data.

James Marrable 6 minute read Data quality

Performance may mean different things to different organisations, but essentially it’s a measure of success that needs to be monitored, maintained and improved. In my role as Sales Operations Manager, I spend a lot of time thinking about how we can improve our own performance. In my case that’s about how well our solutions help our customers meet their requirements. When it comes to driving better performance, I would go as far to say that I am obsessed with it. I read blogs, books, am top mates with TED and even have my own website dedicated to it.

This obsession has consumed my life for nearly two years and so I can confidently say I know ‘a thing or two’ about it. Something however has just struck me - what all these theories, models and approaches to performance have in common is that they rely on two things:

  1. Data
  2. People (You’d be hard pressed to improve performance without them)

Can you imagine trying to make a change to something as complex as the performance of a human being without any data? How would you create baselines? Monitor progress? Set goals? You just couldn’t do it, certainly not in any meaningful and long term way. Not a chance.

As the performance of your people ultimately rolls up to your overall business performance you can quickly see how a reliance on data to help your business is broader than you might think.

Get hands-on with data – access and accuracy matter

My day to day role means I understand the importance of data. I spend my days looking at it, using those numbers to direct us in the most effective way forward. However, it’s not always straightforward and I’m one of the lucky ones. I work for a data company with the skills and resources to support me. What if you don’t?

To add further complexity to the issue, what if you have the data but you can’t access it, or you can’t trust the quality of it. I’m pretty sure that performance enhancement experts don’t say “Hey Bob what time did they record that last run in?” “Er... not too sure… just call it 45 seconds”. I mean that’s just not going to happen. You need accurate data to drive forwards, anything else is just assumption and we know where that gets us.

And this isn’t just relevant to performance enhancement, but all aspects of business from finance to marketing, customer data to product itemising and so on.

If the quality of data is an issue in your organisation, a good place to start is by thinking about your data across the following four stages:

1) Investigating the data: (Is there a problem?)

  • Are you happy with the data you currently have?
  • Is the quality satisfactory to do the job?
  • What other data might you need?

2) Assessing that data: (How much of a problem is it?)

  • If the data you have isn’t accurate, missing etc. - what impact does that have?
  • Can you work with it to drive meaningful insight?

3) Improving the data: (How do you make it more effective?)

  • Do you have other data sources you can bring in to support the data you have?
  • What broken processes could you fix to drive overall better data quality?
  • How are you going to enhance the data – through technology / process etc.?

4) Control: (Has it worked?)

  • Are the changes working?
  • Do they need ‘tweaking’?
  • How are you going to monitor the data over time to ensure on-going accuracy?

I appreciate the above is easier said than done but looking at the data is an incredibly important activity before you can even consider making changes and reporting. Without doing this you’ll only ever be working off the assumption that the data is correct. To drive any meaningful long-term change in performance, whatever business, team or department you’re in, you need to wipe away those assumptions and ensure that the data you’re working with is fit for purpose.

Get your people on board – create a ‘data culture’

If your data is in good shape then getting your people on board is the last piece of the jigsaw.

I recently read a great book looking at the popular concept of marginal gains, I’ve also heard the author talk at one of our conferences (another perk of working at a FTSE 50). He talks about creating a culture of data where you are constantly able to track and monitor progress to clearly defined goals. To be able to do this you must have a clear process in place to detail how you are going to collect, manage and report on progress.

However, more challenges come up here. In my role, I don’t own or input the customer data. I have to rely on others for that. This means it can become fragmented, inconsistent, missing or of poor quality and I’m not going to improve performance with that.

So it’s incredibly important to create a data culture where everyone understands their responsibility and roles towards data. You can only work with what you’ve got right? Often people don’t think about what the true value of data is and how they contribute to the quality of it, or how data actually affects their own role. If you are thinking about focusing your organisation on better data quality to drive performance, I’d start there – awareness. Here are a few ways I’ve come across that can help do that:

  • Introduce data champions – why not task key people in your organisation to promote the data cause? They could be responsible for data quality at a departmental level or someone who works across teams to influence how better data processes can drive better business outcomes.
  • Promote your ‘wins’ internally – many of our customers tell us that getting more visibility for the business benefits of better data management can really impact the appetite to do even more with data. Newsletters, posters or internal roadshows are all examples of ways to move data up the agenda.

Good luck! And if you’re not sure where to start on your data journey, then take a look at some of our resources. I particularly recommend this blog which outlines some interesting tips for building a data quality business case or our whitepaper ‘Laying the foundations for an effective data quality strategy’.

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