Awakening asset: time to review data protection and privacy policies

A good friend of mine is a loyalty card junky.  She appears to have loyalty cards for every retailer she does business with.  The cards are stored in multiple business card holders.  The flurry at the time of payment to secure the correct card can be an amusing, earnest dance.  However, when I question her on the benefits, except for a few, there seem to be minimal tangible benefits to him for using these cards.  This while the retailers aggregate data on his buying habits.

From a different perspective, the rise of web page tracking with cookies, social networking sites and Google analytics have been instrumental in helping companies like Google, Facebook and LinkedIn collect and sell information on individuals.  Over the last 13 years loyalty cards have been joined by Facebook and a myriad of social networking options to broaden the sources for companies to collect customer data.  Companies have been sourcing, buying and storing this data from the various sources for many years. 

I know a few people who do their best to stay “off the grid” and keep their personal data as their own.  Invariably, they need to be technically literate.  Their initiatives, driven by passion for privacy, are admirable and seem extraordinary, but also futile.

The collective data stored by companies is now at historically high levels and continues to increase. In a recent article by Matthew Denham (and IBM) he states state that, globally, there is now 2.5 quintillion** new bytes of data generated per day.  To date, except for the largest and well-resourced companies, little has been done with the data.  Solutions have been perceived as too complex and expensive.

Welcome to the era of the data scientist; the new rising star. According to Denham, the US now has more than 2.5 million data scientists and the demand for more is very high.  Roles in IT and other industries which are less in demand or becoming redundant due to AI are allowing professionals to transition into the data science space.  Several specialist training institutions are catering for the retraining requirement in Australia. 

More generally, a data scientist is someone who knows how to extract meaning from and interpret data, which requires both tools and methods from statistics and machine learning, as well as being human (University of Wisconsin).  Using algorithms and raw processing power the options for data use and leverage are wide and powerful.

From a compliance perspective, the standards around data protection policies and privacy policies are now mainstream for organisations.  Having them in place is one thing but ensuring they reflect the organisational culture and the required robust process against improper use is an ongoing and evolving endeavour.

The challenge for directors and company executives is to leverage the available data while protecting the privacy of the clients and the employees. Of course, the stories that make for sensational reading are those about stolen and hacked private data.  Stolen credit card details remain a hot product. These incidences seem to be occurring more frequently.

Companies entrusted with personal data have responsibility to protect and use it ethically.  There is a balance between providing a competitive, personal & targeted service to clients and protecting the privacy of that individual. 

The intent and the actions on how the data will be used should be guided by the culture of the organisation.  Hence the directors and senior executive have a key role in determining this.

Companies also collect data about their employees.  A recent report published by McKinsey gave a wonderful example where data gathered about employees was used to improve engagement, retention and productivity.

To stay competitive companies must use the data available to them.  Data scientists and their tools can help with decision making and targeting customers to drive sales.  The correct, robust data protection and privacy policies will ensure the culture set by the directors is reflected in its ethical use.

** Quintillion is 1 x 1018

References:

“Grow your own Citizen Data Scientists with these five tips” by Matthew Denham April 19, 2017

University of Wisconsin – What do Data Scientists do?

“Using People Analytics to Drive Business Performance” McKinsey Quarterly-  July 2017