So you’ve selected your business improvement project. You’ve gone an investigated the business function (perhaps done a Gemba walk, or reviewed the issues). You’ve determined that specific areas of the process require further investigation and have decided that you’ll produce some metrics to aid that investigation.
So the next step will be for you to gather some data relating to the process for analysis, but where do you start?
If you consider many of the continuous improvement tools such as PDCA or DMAIC, data capture and its subsequent analysis is essential. Data is key as it provides the context of your journey – where you started and where you’ve got to.
Alas, data can be one of those areas that despite its initial ease, can be hugely challenging to get right. Remember, just because Data is everywhere it doesn’t mean that it’s accurate or timely. Getting off to the right start usually means that you’ll need to
* Review the data that’s associated with the process you’re reviewing
* Determine how you’ll obtain it
* Review for how long you’ll record it (5 mins, a week, a month?)
* Decide what you’ll do with it (i.e. produce a metric)
* Figure out what issues you may have with the data (e.g. Accuracy)
* Decide where/how you’ll store the data
* Gain consensus in how the data will be interpreted.
Having a data collection plan is vital and I’d recommend that you do this step up-front. Obtaining lots of data can be costly in terms of time and resource and it’s often pointless if you’re not going to use it or if its value is questionable. Part of the trick here is reviewing
* does my data already exist
* is it captured at the right time?
* Is it going to support an argument/point of view.
In many cases your business may capture data already – for example, many businesses have corporate metrics systems that collect and utilize large sets of data – it could well be that your dataset already captured and analyzed?
One of the trickiest things is determining how long you’ll need to track the data to obtain a reasonable sample size. Obviously, you want it to be a representative sample and to highlight issues but it can be a difficult one to balance. You don’t want your data telling a story that might not actually be true! One way around that is by way of developing a sampling plan – for example, you may take data sets over a period of time, this could be done randomly or with a pre-determined sampling plan. The key is that you want your data to identify important contributory factors that feed into the issue that you’re reviewing.
The other factor to consider is how you will present the data, could it be considered subjective? Is the root cause behind the data clear? Is presenting it likely to be contentious (i.e. team members may have a different opinion than you!). I’ve often found that getting the data is one thing. Selling the root cause and improvement steps is something completely different!
The other plus point in documenting your data collection plan is that post-process improvement you can then use the same mechanism to monitor the success o the change you’ve implemented. This helps close the loop and ensure your improvement project has driven the value expected.
* Data collection is a vital step in any continuous improvement process.
* Understanding what you want to measure, why and how is crucial.
* Considering what issues you might have with the data can help in presenting your argument.
* Don’t waste time capturing data if it’s already captured through other routine methods.
* Review Early on how the data will be used and consider the audience that it will be presented too.
Have some thoughts on collecting data for improvement projects? We’d love to hear what you have to say in our comments section below!