British astronaut, Major Tim Peake, takes data to new dimensions as he closes out Big Data LDN 2023
Picture this: you are leading a data transformation journey at your company. You’ve developed a great data governance framework, shopped around and invested wisely in the right tools for your business, and even received the right level of funding from the organisation’s execs. It’s a dream scenario… but these things alone won’t lead to a successful data transformation. There is one key ingredient missing, and that is people. The program's success relies on achieving buy-in, building data literacy beyond an understanding of numbers, and taking all levels of the business on this journey with you. But how exactly do you achieve that?
The first step is to appreciate the critical point that there is no “one size fits all” approach to bringing people along with you on a data journey. Having spent time in numerous organisations of varying shapes and sizes, my career has sometimes felt like I was on safari as I spotted various patterns of behaviour. There are many different data animals out there, each with their own personalities and needs.
At a glance, you’ve got the longstanding employees who prefer their data silo and bury their heads in the sand like an ostrich to protect themselves from change. These ostriches are closely tied to the gorillas of your company, those who are territorial of their data and beat their chests at the advance of outsiders threatening who may threaten their view of the world. In both cases, you need to help these employees understand the value of data sharing across an organisation. Explain to them why breaking down silos with the right governance framework won’t lead to worse data quality but will improve how they and others can do their jobs.
In contrast, there are also goats who will happily consume any and all data, regardless of its quality and irrespective of whether it is fit for purpose. Or the cheetahs, who like to run full pelt with data as quickly as possible and find it a drag to scrutinise the data and results they obtain. In both of these cases, we must help colleagues understand that not all data is created equally. There needs to be a healthy level of scepticism when it comes to the data you are using, and helping these colleagues to know how to consider the dangers of poor data quality will be vital in helping them unlock better data-led outcomes.
Yet on the flip side, are some people too picky about their data? Do they, like an owl, reject anything too hard to digest by demanding only data that is 100% accurate? This may seem odd to come from a data professional, but a ‘good enough’ approach, so long as it truly is good enough for all the destination purposes of the data, can avoid stifling creativity and delayed results. Can we provide these creatures enough assurance and trust in their data being fit for purpose that they will happily take flight with it?
Whilst it’s clear that there are many different animal tribes when it comes to colleague approaches to data transformation, there is one core feeling to explain their traits and link them all together – fear! Whether it’s a fear of change, overcomplicated rules or using data in any meaningful way, fear hinders adoption and without adoption across an organisation, a data transformation can never be truly successful. So the last thing the company needs is a herd of data governance wildebeest hurtling through despatching their wisdom but leaving the various bystander species dazed and confused, not knowing which way to run like rabbits caught in headlights.
There are many other data animals out there, and ultimately, no matter how great a framework is, it will struggle to be successful if business users feel data governance is being done to them rather than with them. Leaders need to identify what is holding people back and then show them what’s in it by striving to understand their instincts and communicating with each type of person in a language that they understand. Approaching data transformation as a one-size-fits-all, top-down strategy won’t work. Data leaders need to become the animal whisperers of their organisation and tune into the different natures within to communicate effectively with colleagues if they want to succeed