Ever heard your Exec say “My gut feeling is…..” or “I think we should do it because I have a gut feeling that our competitor….”? Many businesses today still operate on creating and making business decisions based on ‘gut feelings’. Scary I know!
I recently had a debate with my Exec on ‘data driven actions’ rather than relying on the HiPPO’s (Highest Paid Persons Opinion) ‘gut feelings’ to drive business actions (which most often turn out to be incorrect or harmful to the business itself). How can anyone drive action through their own ‘gut feelings’ when they have no data to back up their feelings or tell them otherwise? This lead me onto the question:
“How important is data to a business in order to make better business and marketing decisions?”.
Marketers have had a whole new world opened up to them in the last few years in the form of analytics or business intelligence through various tools and technologies which gathers and sorts various forms of data such as website visitor data, transactional data, campaign data and then when segmenting this data for more data you get a whole new level of data. An important criteria of a marketer today is not just creativity but must also be able to understand and read data in order to gain valuable insight that could lead to better business and marketing results/performance. Keyword here is ‘insight’. Read and analyse data to give you insight to drive actions. Marketers are now seen as the ‘intelligence’ within organisations who’s focus it is to use current and predictive analytics to give execs information on future trends and forecasts and collaborate with other departments to drive further action. Is the marketing department suddenly the feeders within the business to other departments?
A recent survey of 600 managers at more than 500 blue-chip companies in the U.S and U.K conducted by Accenture Analytics found that:
43% had failed to employ professionals dedicated to analytics.
5% use analytics to support supply chain and resource planning
33% are worried about the data being exposed to non-management staff
46% agree that technological resources and systems greatly hinder the effective use of enterprise wide anlaytics
So 57% of businesses had realised the importance of analysing data to drive better business decisions but only 5% use it to support the supply chain of information which begs me to ask the question “What is the data being used for?” Ok, I think its important to establish at this point that not everything needs to be analysed, every business should define the business questions which the data should answer.
Almost half of those surveyed see resource as being an issue which I can almost agree with. It takes time, effort and skill in order to get the best out of data. I have to go back to 2006 when Avinash Kaushik wrote a post about the 10/90 rule:
Cost of analytics tool, technology or service: $10
Required investment in ‘intelligent resources/analysts: $90
Bottom line for magnigicent success: It’s the people!
Agree? I do.
The problem businesses face today is that they don’t know what the data is telling them, whether the data is actually what the data they should be looking at and if the data they have is accurate. This is where ‘data driven cultures comes into play. It take people to understand, mine and draw information from the data and thus takes intelligent people to do so. This video by John Lovett is inspiring and I hope more businesses adopt ‘data driven cultures’ in the future: Building a Culture of Measurement
Every business action should have evidence behind its decisions in the form of data. Not gut feelings.
Love to hear thoughts from businesses who use data successfully.
why do you think companies are so paranoid about sharing data outside a few trusted people in upper management?
I have no idea Jason. I can only assume that sometimes truth hurts and data will sometimes bring you and your business back down to reality.
Execs love to assume that things are going ok, sales are up and everyone is busy so can ony assume that everything is ok. Then the data comes in and BANG! Sales are poor due to low order quantities or increases in the number of complaints, product defects which led to refunds which leads to lower revenues etc etc.
Data hurts sometimes.