Econsultancy just published a really useful free report: Big Data Trends Briefing: Key takeaways from Digital Cream London 2013.They were kind enough to include a few quotes from me but the reason I like it even more than that is the huge number of examples, case studies and other resources that it highlights. It’s a really useful gateway to all things Big Data: the main issues, opportunities, barriers and potential solutions.
Big data analytics is inherently ‘multilevel’ – it’s not just about very big, company-wide issues; or about very personalised and immediate consumer issues. It’s about both of these and every level in between.
Making it work at every level of the organisation, and in real-time, is now possible. One size fits all is no longer mandatory and as a result much greater efficiencies can be gained. This is an example of ‘good complexity’ – using an data analytics strategy that personalises customer experiences and staff insight and information requirements at every level.
But Big Data’s scale means that it crosses organisational silos, you can see this in the fragmentation issues that have been thrown up already. The upshot is that the sponsorship for Big data projects needs to be much higher up, i.e. a board-level sponsor for board-level issues.
Which means that you need to talk about board-level benefits when you argue the business case, e.g. a commercial director of a big ecommerce site recently told me that he was really interested in increasing Stock Turn (i.e. greater overall sales volume with the same working capital).
That got me thinking about analysing sales data to highlight products with characteristics that impact Stock Turn (sales value, velocity), then checking for the specific customers who buy them or would buy them and then influencing those customers using direct marketing like texts and email. Marketers in different digital areas do this stuff all the time but I haven’t seen it linked to how to influence specific Board members.
Big Data is now moving towards being more about analytics and Organisational Change, i.e. there’s no point in deciding what to do next if you can’t then do it.
This is what we are researching right now:
- the need for arguing business cases, persuading and visualising Big Data analytics in terms of different staff roles, current needs and choices of options;
- using analytics to shift the balance a bit from centralised to decentralised decision-making whilst still maintaining control; and
- the other things on this blog.
We’re looking for research partners so if you want to have your Big data itch scratched and get the benefits of a few of the opportunities that I blog about then let me know: duncan.shaw@nottingham.ac.uk.
Duncan R Shaw - The qualitative data scientist 