Data is only useful if you use it!

The value factor

We have all become data collectors. This is true for corporations and individuals. Organizations store petabytes worth of customer transactions, social sentiment and machine data. SAP’s Timo Elliott recently wrote a nice blog post about the ‘datafication’ of our own private lives. Just to give you a personal example, I have over 2GB worth of exercise data (heart rate, running pace, cycling power, GPS info, etc.) ranging back to 2003. But there is a growing problem – too many people & organizations are just really good at collecting data. Not enough people are doing anything with it. Let’s face it – data is only valuable if we really use it!

The inertia problem

strava

There is a ton of data available

Leveraging data for your benefit can be a struggle: you have to process it, you have to look at it, you have to analyze it and you also have to think about it. Here is an example: let’s say I am a runner and I wear a heart rate monitor that is connected to my iPhone. I will only get value out of that data, if I am willing and qualified to analyze it after each run. Letting the data sit on my iPhone will not help me identify trends and patterns. And then there is also the step of developing and implementing specific actions: should I rest, do I need to run harder to improve my marathon time or do I actually need to slow down to accelerate recovery? The same thing is happening in organizations. Starting to trust your analytics is another whole big issue.

Take action

How can we prevent becoming masters in data collecting but rather champions in performing analytics? Based on my experience there are a number of actions we should all look at (personal & professional):

  • Examine your available data and make sure that you really understand what it all means. This includes knowledge of the data sources, meaning of KPIs, collection methods, etc..
Power data

Do you really understand your data?

  • Sit down and clearly identify why you are collecting that data. Identify goals such as increase sales, set a PR in the next marathon, increase machine performance.
  • Develop a habit of working with your data on a daily basis – practice makes perfect. Only cont
  • Acquire the right skills (attend training, read a book, meet a thought-leader etc.) – we all need to work on our skills
  • Invest in the right tools – not every piece of software makes it easy to perform analysis.
  • Collaborate with other people, i.e. share your data, discuss findings
  • Celebrate success when you are able to achieve your desired outcomes

What are your experiences? Are you really leveraging your data or are you just collecting it? What else can we do?

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