By Peter Ellis
In a million ways our lives are being reshaped by new uses of data. From the risk-analysis calculator our banks use to decide whether to give us a loan to the optimised route our satellite navigation system suggests for our drive home to the diagnostic tool our doctor uses to review an x-ray, all sorts of activities are being influenced by the accumulation and analysis of terabytes of data.
Three things are driving the change: a revolution in statistical methods that started late last century and is still ongoing; cheap and powerful computing power; and new data sources generated as by-products of everyday activities.
The age of big data relies on the rapid growth of computing and communications horsepower – some 90 per cent of the world’s data has been generated in just the previous two years, according to one study.[1] But it would not be possible without the massive databases of information compiled by government and private organisations, and without the willingness of those organisations to act on the insights that emerge from analysis of those databases. Both of those require the organisation’s staff to have a high level of data skills.
The cumulative effect of leading-edge organisations intelligently exploiting data is that consumers expect the organisations they deal with to use data-driven insights to improve the user experience. By next year, there are estimated to be 50 billion devices collecting data as part of the Internet of Things.[2] Users expect the services that result to be highly personalised, lightning fast and available anywhere at any time on any device.
For organisations that do not think of themselves as technology organisations, this heightened expectation can be intimidating. Many executives find complex decisions about the use of technology to be at the outer edge of their comfort zones and are spooked by nightmarish stories of technology projects that made big claims about what they would achieve but left only a legacy of big costs and big headaches.
Several organisations whose primary capability is not technology have made innovative use of data to improve their performance.
For example, the Australian Taxation Office’s data-matching program electronically compiles, validates and analyses information from third-party sources. Its data-matching efforts are used to create pre-filled tax returns, thereby making it quicker and easier for taxpayers to lodge their return, and for the tax office to identify possible incorrect claims. The productivity and performance benefits of the ATO’s use of data are immense.[3]
But identifying and using opportunities like this requires careful preparation. The technology alone is not enough. Instead it relies on organisations understanding the data capabilities of their people and taking a strategic approach to developing those skills. Without data-skilled people – across all levels in all parts of the organisation – opportunities will be lost.
Recently NSW Health launched the Health System Performance App, which enables hospitals and other local health organisations to analyse performance against key performance indicators.[4] While the app obviously deploys data technology, crucial to its success is that users understand how to interpret and interrogate the data. Without people able to understand the information, the data risks being a blur of numbers and graphs, with no clear course of action resulting from it.
When many people think about data literacy, their minds go to computer code, graphs and complex economic modelling. It is true these are important for getting the most from data. At Nous, we even have an “Analytics Team Maturity Model” we use to help specialist areas work through the challenges of IT platforms, source code version control, statistical skills and data governance.
But number-crunching is only one aspect of working with data. And just like war and generals, data is too important to leave to the data scientists. Complementing the specialist skills expected of statisticians and data professionals, data literacy for organisations also involves:
Essentially, data literacy is the ability to contextualise, critically appraise and communicate insights from data and information to support an organisation to achieve its purpose.
Every organisation can benefit from a capability framework to improve their data skills. From Nous Group’s work supporting organisations to make real progress in this regard, we have identified five fundamental steps. There are some powerful tools that can help to put these steps into practice.
It is understandable that some staff may take a sceptical approach to an effort to achieve a step-change in data capability. For people who feel use of data may challenge their judgements made on instinct, or who find numbers intimidating and would prefer to leave them to specialists, it can be difficult to accept the greater prominence of information-based analysis.
To achieve buy-in it can be effective to involve staff at all levels and in all roles, so the effort is rightly seen as organisation-wide rather than targeting particular individuals. Broadening the pool of people benefiting from the data upskilling can help to achieve shared responsibility for learning and development. Ultimately, it can also deliver the shift in culture and expectations that are required to embed these new skills in the organisation. ‘Change champions’ and training tools can help to promote and facilitate organisational changes.
So, what would an organisation with a high level of data skills among staff look like? Clearly it will vary a lot according to context, but we can expect that decisions are made based on thorough analysis of data, that new products and services are tailored to the individual needs of users and that emerging trends are spotted early, allowing the organisation to get ahead of the curve.
Put together, these can give an organisation an edge that can set them apart from their competitors.
Get in touch to discuss how we can work with your organisation to build data skills.
Written by Peter Ellis during his time as a Principal at Nous.
[1] “Exciting facts and findings about Big Data you should know”, Big Data Made Simple
[2] “The Internet of Things”, Cisco
[3] “Data matching”, Australian Taxation Office
[4] “Health System Performance (HSP) app”, NSW Health