The technological tools available for collecting, storing and processing data may have come on a bit since Sherlock Holmes’ day but, more than 120 years ago, Arthur Conan Doyle’s great detective was applying principles that modern businesses are just beginning to get to grips with. “It is a capital mistake to theorize before one has data,” Holmes told his sidekick Watson. “Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.”
This is the idea that lies at the heart of the big data revolution. Data has no value in its own right; collecting and storing vast amounts of it is pointless for businesses that do not understand how to analyze the information in order to produce insights on which they can act. In contrast, farsighted organizations will become completely data driven.
So how ready are you and your business to make that shift? Although many organizations are making great progress, analytics is a technology still in its relative infancy. Honest self-evaluation is the key to moving forward. Only by assessing your current level of data maturity can you, as CIO, identify areas for improvement and then build data and analytics capabilities that have the power to transform the business.
As highlighted in a new EY report on realizing the value of data, a simple maturity test can help you start that process. Give yourself three points for anything you’re totally in control of, one point for something that is still a work in progress, and a zero for anything you’ve not yet thought about in any detail.
- To what extent has the organization set objectives for analytics? This refers to the strategic work the company has done on identifying what it hopes to achieve with analytics and how it plans to achieve it.
- To what extent has the organization developed analytics processes? Are business functions developing processes for extracting value from data? Is this being done on an enterprise-wide basis?
- To what extent does the organization possess analytics skills? Companies need to identify the skills they require from their data and analytics specialists and to measure any shortfalls.
- To what extent is the organization’s senior leadership supportive of analytics initiatives, or leading them? This is a question of where the push for data-driven decisions is coming from – the higher up the company the better.
- To what extent do the organization’s technology tools enable analytics capabilities? Does the business have the functionality it needs – everything from data sourcing and storage facilities to analytics tools?
- To what extent has the organization embedded a culture of analytics? IT may be increasingly aware of the potential of data, but are the opportunities being recognized throughout the enterprise?
- To what extent has the organization considered the legal challenges of big data and analytics? With opportunity comes risk – which ranges from data privacy concerns to competition law.
- To what extent has the organization sought to mitigate other potential risks related to big data and analytics, including cybersecurity issues? Businesses that do not confront such concerns risk financial and reputational damage as well as potential regulatory sanction.
So how did you score? Very few companies today are scoring 20+ here, but if you’re struggling to hit double digits, you should question how prepared you really are for the data-driven world in which we’re now operating.