After you've had your spelling corrected you listen to some music on Pandora or other music streaming systems. They happily predict what you'd like to hear. Then you visit your LinkedIn or Facebook page and again predictions appear as to who may be your friends or long lost colleagues.
All around us systems are predicting what we like, who we know, what we might like to buy. These predictions are often eerily correct...spooky in fact.
In the world of lawyers, prediction technologies are being used to predict outcomes of cases enabling clients to shut down lawsuits early if the outcome is predicted to be unfavourable. Other systems predict the amount of a settlement during negotiations.
Underpinning all of this is data analytics technologies sitting on top of huge piles of data. The amount of data that is being gathered and saved every day is truly staggering. As one small example I was talking to a farmer recently who was microchipping his cows so he knew where in the paddock they were, how much they moved around etc. The amount of data gathered each day was enormous. Multiply this to virtually every aspect of life and we have stores of data that is impossible to imagine.
Data Analytics at its core is the science of pattern recognition. Can software look at this mountain of data and see trends that might be useful in predicting outcomes. In the case of the lawyers, databases in the US now record all aspect of cases. Who the lawyers were, who the judges were, key aspect of the case and the case outcomes. From this data the technology can then look at any new litigation and attempt to predict its outcome. Rates of over 70% success in prediction are being seen. This can only go higher as the algorithms get more sophisticated and more data is gathered.
How is this relevant to the accounting industry? Well, the big development over the past few years has been the rise of cloud accounting applications. A consequence of this development is the amount of data being stored in the databases housed by MYOB, Xero, Intuit, Reckon and others. In effect these databases will probably have more knowledge about the performance of small business than has ever been gathered.
Putting privacy issues aside for the moment (and I don't think it will be an issue as the data used will be anonymous), imagine what a data analytics engine may be able to do with this data.
It may be able to predict the likelihood of solvency issues, it may be able to suggest new markets that the business may want to address, it may suggest product lines that should be expanded or discontinued. It may predict customers that might have solvency issues. It may predict optimum pricing for products. The list goes on and on.
Other opportunities exist to correlate financial data with non financial data to further assist business decisions and predict outcomes. What would be the impact of traffic volumes or the weather on business. How might exchange rate or interest rate changes affect demand? These are just some examples.
What an opportunity for the accounting industry to harness these technologies to provide highly valued advice to clients. The interpretation of these analytics will become highly valued.
In recent times there have been a number of significant investments by Big 4 firms in this space. Have a look at this KPMG video about the impact of data analytics on audit:
If there is a space to watch in the next few years this will be it. It will only be a matter of time before MYOB, Xero, Intuit, Reckon and others turn their attention to the potential of data analytics to add considerable value to their customers. As accountants we need to be at the centre of this revolution to harness these technologies and provide advice to clients that will make a considerable difference to their business and their lives.
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