Six tips for extracting more value from big data
Andy Crossley, a management consultant at Oakland Consulting, provides six tips how organisations can extract more value from the data – big or small.
1. How much is too much? – Having the ‘right’ amount of data within your organisation is important. You need just enough of the right data about your processes to run the organisation efficiently and effectively. But you also need more of the not so obvious data to spot the trends and opportunities for improvement. Getting the balance right between the two is critical, and an age-old challenge of business.
2. What does ‘good’ look like? – Having the right amount of data, with the requisite level of quality is important. Being able to trust the sources of your data helps in being able to apply it. Don’t trust the source? Are the sources automated or prone to human error? Do you have consistency in format and structure? These are all issues that need careful consideration and mitigations applied in tailored ways. For the areas of data that you rely on most, quality should be at the top of your agenda.
3. Data, processes and relationships – How you apply data insight (especially the value that ‘big data’ can bring) is more difficult to assess. Many recent discussions centred on data and its relevance to the processes. However, you also need to consider the type of data with your process. For example, the consumer goods industry does a great job of applying the right data to the right processes, partly because they use a blend of sentiment data with purchase data to build a full understanding of customer behaviour, but they also have very well established and mature processes. The relationship between the two is also well understood and so maximum value can be extracted and applied.
If your processes aren’t well established, controlled and mature the data will be limited in its use. Those organisations which have data attached to well-structured and managed processes can use the data more effectively for real time decision making.
4. Big, and small, data can mean big trouble – I saw a great quote from Tableau in 2014 (7 tips to succeed with Big Data in 2014) “Big data is fun like a sandbox. You can get in there and build and shape things and even pick up sand and put it down your best friend’s pants…only under adult supervision”. This is still true today. Most people I spoke to showed a real enthusiasm for data, what they could do with it, the insights it gave them and the ideas they developed to improve things.
However, in the same breath they were all increasingly concerned with the control and governance of the data – especially those from highly regulated industries. The clients which seemed to be more ‘calm’ had Information Governance programmes in place that were building the foundations for the right culture and approach to data management. This is helping to ensure that data is handled correctly and supports the relevant compliance obligations that face organisations in these regulated industries. ‘Bid data’ shouldn’t be treated as a separate concern, to be maintained independently. It is part of the business environment we all interact with and therefore it shouldn’t be an IT ‘thing’ only. In fact, I’d suggest it’s very much a ‘business’ thing, with IT supporting the mining, delivery and maintenance of it
5. Accessibility – Having all of the above ticked off is great, and you’re probably way ahead of many others, but still my clients talked about accessibility. If you can’t easily access that rich data, it becomes difficult to convert it into information, and near impossible to share as knowledge! The access to your data actually helps improve the other areas, through constant learning and re-application. Make it available in a straightforward and easy to use way, so that users are empowered.
6. Do you have the capability to change? – Probably the most interesting thing that came from discussions was that people recognised that the growing application of data often means the speed of change is ever-increasing (how can it get even faster, I asked myself!). This means that an organisation with all the other elements ticked is no better off if it can’t apply the knowledge from that data in a quick way…and continue to learn and improve. So as I’ve seen so many times, all this technology is great, but only if you have the people, skills and culture to apply it correctly.
These elements are proving interesting discussion points around ‘big data’. Ask yourself whether you have all the ingredients for utilising all that data!