3 top takeaways from the DTX Conference

26th October 2022

Stephanie Jatta

Data Visualisation Analyst

5 minutes to read

I recently had the pleasure of joining colleagues, industry leaders and keynote speakers live at the 2022 DTX Conference in London.

It was great to see everyone come together again, to discuss the future of digital transformation and hear how brands’ are bridging the gap between data literacy and data-driven culture within their organisations. Here are my top 3 takeaways:

1. Get teams to speak the same language

A big question for organisations — large and small — is how to bridge the gap to create a data-literate and data-driven culture. Improving employee data literacy in any organisation results in teams speaking the same language i.e. understanding the data, the benefits and outcomes. Needless to say, data is only as valuable as your ability to understand it correctly, and a team that understands data makes better data-driven decisions. It’s that simple.

But how do you create a data-literate and data-driven culture? The keynote speakers from brilliant brands such as ITV, Lloyds Banking Group, ONS and Specsavers highlighted upskilling and reskilling as a key approach. Some key skills required include; critical thinking, maths, statistics, coding and even an understanding of cloud computing. Now, this doesn’t mean that everyone suddenly needs to know how to code. However, the bottom line is that if we all understand the basics of the problem/product/goal it facilitates a collaborative approach to solving a problem or achieving a goal. Put simply, good data processes allow you to conclude why a new strategy worked or didn’t — so you can avoid making the same mistakes in future or better, recreate the magic of something you successfully pulled off.

Another method of making data literacy the default standard across the organisation is via encouraging questions about data literacy. Getting a wider variety of perspectives can strengthen your data and the validity of what you take away from it. Data is human and therefore flawed, so the more humans you have involved in interpreting it, the better. Questions like, “What are we missing?”, “How does this help us get closer to our goals?” or “Is everyone looking at the same thing?” can be valuable conversation starters that help you discover more about the story your data is telling.

Data literacy empowers team members to be more successful in their roles and makes cross-functional collaboration easier and more impactful. There are endless ways to encourage team members to get better at navigating the complex world of data. Still, the most important thing is ensuring your company emphasises data literacy as a valuable skill across all levels. This might mean hosting data-led workshops, or rewarding those who level up their data skills. Whatever your company’s data journey looks like, it’ll be one worth going on.

Once the data literacy side of this has been worked on, this facilitates a data-driven culture. What does a perfect data culture even look like, one might ask? The speakers shared that in their organisations this involves moving beyond specialists and silos, to achieve deep business engagement and cultivate a sense of purpose, so that data can support their operations instead of the other way around. The key is that you don’t approach data analysis as a cool “science experiment” or an exercise in amassing data for data’s sake. The fundamental objective in collecting, analysing, and deploying data to make better business decisions.

2. Don’t just talk about the data, showcase the benefits

Establishing a data strategy and roadmap from capture to automation, and everything in between starts with the senior decision-makers. But while a commitment from these key stakeholders is essential, it must be manifested by more than just the occasional pronouncement; there must be ongoing, informed conversations with the decision-makers and those who lead data initiatives within the organisation.

In most cases getting the decision-makers on board can be a challenge. However, leading with the benefits usually has a higher impact. Also, demonstrating the ROI and cost as well as providing a show and tell which encompasses things like: “Here’s what we’re doing. Here’s what the challenges are and here is how we are spending the budget”. Most importantly, here is the value we’re seeing - transparency is important. This approach is an effective way of drawing the decision-makers into buying the data strategy.

3. Democratisation of data

Get data in front of people and they get excited. But building cool experiments or imposing tools top-down doesn’t cut it. To create a competitive advantage, stimulate demand for data from the grassroots. The speakers emphasised the need to figure out how to democratise the data-analytics capability, which means creating a self-serve platform where people can easily access data. Doing this will help people to believe in it and to deliver solutions that don’t require an expensive data scientist. When people begin to believe in the data, it’s a game changer: They begin to change their behaviours, based on a new understanding of all the richness trapped beneath the surface of traditional systems and processes.

To conclude, a data-driven culture can be a compounding problem or a compounding solution. When an organisation’s data mission is detached from business strategy and core operations, it should come as no surprise that the results of analytics initiatives may fail to meet expectations. But when excitement about data analytics infuses the entire organisation, it becomes a source of energy and momentum. The technology, after all, is amazing. Imagine how far it can go with a culture to match.