We sometimes get so caught up in the hype of big data – the huge, fast moving, complex and diverse data sets – and the potential value they can deliver to companies, that we forget its little brother.
We sometimes get so caught up in the hype of big data – the huge, fast moving, complex and diverse data sets – and the potential value they can deliver to companies, that we forget its little brother.
Big data’s little brother is ‘small data’ or traditional KPIs (Key Performance Indicators) that help to measure success in companies. Any data, and in particular ‘big data’, only becomes meaningful and relevant in the context of the business success, measured by KPIs. Let me explain.
By itself, data has little or no value to a business. Value is generated when the data is able to deliver new insights that improve decision-making and improve the performance of a company. If designed well, KPIs are the measures of company performance and therefore the ultimate measures of big data value.
Here are three examples to illustrate my point:
1. Take the big data a company holds about its customers that allows them to map customer preferences, identify new trends, and target specific users with customized offers. This is all well and good, but if it doesn’t improve traditional measures of success such as revenue growth, profit margin, customer satisfaction, customer loyalty or market share, then it is not generating true value.
2. Big data is increasingly used to improve internal operations and processes. For example, companies use geographic positioning and radio frequency identification sensors to track and optimize supply chains and deliver routes. Again, the data is only really delivering value if this translates into improvements tracked by traditional KPIs such as shorter delivery times, reduced deliver costs, etc.
3. Big data is also increasingly used in HR and talent acquisition, the same applies here too, KPIs will determine the value of big data by helping to assess recruitment costs, staff engagement, staff satisfaction, staff churn rates etc.
So, the point I want to make here is that we shouldn’t forget traditional KPIs in all the hype about big data. In fact, traditional KPIs such as revenue growth, profit margins, customer loyalty, relative market share or staff engagement are vital components of any big data initiative and therefore more important than ever before.
Instead of ignoring traditional performance metrics, it is important to put even more effort into those to ensure they are the true measures of business success. Only if we have well designed KPIs that measure the key aspects of a company’s performance in a meaningful and reliable fashion, can we maximize the value of any big data initiatives.
My message therefore: Big data is nothing without its little brother – traditional KPIs.
I have put together a library of over 100 traditional KPIs that can be used to measure the value of any big data initiative, check it out here.
Any views on this? Please let me know your thoughts…
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Finally, please check out my other posts in The Big Data Guru column and feel free to connect with me via Twitter, LinkedIn, Facebook, slideshare and The Advanced Performance Institute.
