Building Trust And Value Through Data

Firstly I feel that these days the value of the data gets lost in the noise or clamour for instant ROI, the need for instant reporting and answers, so inevitably leaders focus on the bottom line.

• Any data initiative needs to be described from the position of knowledge of the whats happening in the organisation, for example, data governance is often described as a control framework or with rules or it hints at additional work, all of which may be true, but don´t really engage people.  Outside of the board most people respond to understanding a real-world issue that they have that is getting resolved.  That by definition provides the basis to present the value case, whether that’s greater efficiency, saving time and money, reduced workload pressure etc.

• Inside the board, it’s a case of describing the key issues that have been discovered, the risks that are being posed and then monetizing those risks.  For some its easy, big problems with PII data you can tag to a potential fine from the ICO or other regulatory body.   The biggest problem with leadership engagement is the overhyping of the art of the possible, with little or no evidence to support the case.  For example some vendors will make claims about “solutions”, they will make promises about “solving” issues, those on a slide deck look great, the reality, the real world those statements run into difficulty because of workload, pressures and understanding.

This is really interesting and not easy to answer, because a P&L line as an of itself does not necessarily display the whole picture; for example, if I said there had been an increase in sales, how might my data strategy have enabled that, greater efficiency because of data governance, greater accuracy of the data being used, insights being improved because of better data, all of which could be true, the reality though is that someone still has to take those numbers and go and make the sales.

In many cases the answer would be its difficult to demonstrate the ROI of the data strategy because it touches so many things.

• Over the next 3-5 years we will see even great advances in technology, the use of AI (which will still have issues depending on the strength of the data foundations supporting it) and those things could bring much greater effectiveness to organisations (assuming they understand their data ecosystem properly). However, I think the mindset of CDOs needs to be around how the guiderails are put into place to manage the ever increasing use of technology and AI.  There are a great many things to consider, not just the advent of the technology, but also its ethical use.

• Another mindset I think they should have is understanding the behaviours of the people in the organisation much better, why do they create shortcuts, what are the workarounds, how much data is being fixed manually.  Those things will help close the process gaps, improve the feedback loops, increase data literacy, reduce the incidence of data issues and reduce the wasted effort in tactically fixing the data.  Today I think that the speed of advancement of the technology has highlighted much faster the flaws in organisations data ecosystems

• For me its around not understanding the data ecosystem properly and the behaviour ecosystems that exist in organisations.  There are gaps in processes, speed of response the ability to get something resolved and so the people in the organisation will be inventive and innovative by improvising, making assumptions, missing validation checks, creating shortcuts and workarounds all in the name of speed and reducing pressure.

• There are almost limitless areas where time and money can be saved and they don´t need to be technology driven, in most cases they are people driven, increase data literacy, get people to take more care when creating data, check the fitness for purpose and above all fix things when someone bothers to report them.

• In most cases the small fixes will build up to big savings, maybe not in the tens of millions, but who knows the value of a reputation because you don´t take care of the data.

Data democratisation, comes down to understanding your data ecosystem, what have you got, where is it, how does it move around etc and the data literacy of the organisation. People will take whatever actions they can (if the organisational processes don´t support them effectively) to “get the job done”.  So in order to have effective data democratisation you have to instil the idea of the value of the data, ensure they know the impacts of their actions and you have to have effective controls that ensure that access to the data and use of the data is there for the people that really need it.

There is a huge amount of data in organisations, does everyone need to see it? In my opinion no.  What they need to know is how its used, the impact of it and how they can get access if they think they need to.