5 Questions to Ask on the Road to Data Excellence – Part I
In this three-part series, we are going to ask five questions that strike me as most important in the quest for data excellence. These were formed after some interesting discussions with our in-house data professionals. We will start with data skills and data literacy. In the second post we'll take a look at how to establish both the foundations for a consistent approach to data across the organisation and a data-driven culture. The third blog will address data strategy and policy. In each section, we’ve provided a set of true or false questions. Ask yourself these questions to see where your organisation is on your quest for data excellence.
Do we have the skills we need?
The world of data has become a whole lot more exciting of late. An insatiable appetite for business insights has created a range of new roles that combine skills in business, statistics, mathematics and programming. Data scientists, domain specialists (in language and behaviour), data architects, business analysts and statisticians are now being recruited into almost every large organisation. Sometimes these roles work in IT and sometimes in Lines of Business. Either way, their arrival has been key to opening up access to intelligence across the business. At the same time, data tools have become more powerful, processing power has increased and analytical techniques have become more mature. Combined, these have enabled a shift from basic application based data capture and reporting to full-blown analytics and prediction.
However, these specialist skills are in short supply. Moreover, outside of these specialists, most organisations lack data literacy. This is so acute that Gartner predicts that by 2020, 80 percent of organisations will launch formal competency initiatives in this field, "acknowledging their extreme deficiency."1
A recent Commvault Survey2 highlighted the same problem, with both the executives and IT personnel surveyed expressing concern that data-centric skills problems were likely to hamper business success going forward.
Data literacy across the organisation is different to the deep data expertise of data specialists. The scientific approach to data used by data scientists and other data professionals involves asking questions like, "Is the sampling adequate in size, balanced and unbiased? What are the positive and negative controls? Are the data properly cleansed and normalized?"3
A data literate employee is more likely to ask, “Where does this data come from? Is it current and accurate?” and “What does this data tell me?” Whilst the data scientist’s specialist knowledge is deeper and more rigorous, this is balanced by the sheer number of non-specialist employees. As Gartner recently observed, "Data literacy is crucial to achieving digital business success,4 which should make a data literate workforce a priority for every organisation.
True or false?
- We have recruited data specialist roles to help us get the most out of our data
- There is a plan to develop specialist data roles in the organisation
- We have high levels of data literacy across the business
- We have a plan to increase data literacy
How did you score? Let us know on social media!
1 Gartner, Data-Centric Facilitators Are Crucial for Enabling Data Literacy in Digital Business
2 Quadrant Strategies, Poll with IT Executives and IT Personnel, 2017
3 Science Direct Data Literacy, How to Make your Experiments Robust and Reproducible, https://www.sciencedirect.com/science/article/pii/B9780128113066050016
4 Gartner, Data-Centric Facilitators Are Crucial for Enabling Data Literacy in Digital Business