At the beginning of December 2021 I had the pleasure of co-hosting a webinar about data literacy with a few of my data friends Steve Adams, Steve Prokopiou and Neil Richards.
Steve A and Steve P approached me back in August 2021 about putting together a webinar and I jumped at the chance to work with them both. Then we roped in Neil a few weeks before our planned webinar to see if he would facilitate the Q&A session and fortunately for us he said yes!
After lots of preparation and many iterations of our session and some marketing we hosted the webinar on 2nd December. Now here is where I let you into a secret that I didn’t share on the webinar at the time; I had COVID and was feeling pretty ropey. I was determined to do the webinar especially as we had been planning it for months, so I put all my energy into that hour to ensure it was a success. I am pretty sure it is not obvious I was suffering. Fortunately, I made a full recovery over the following week, feeling blessed and extremely grateful that had all my vaccinations!
We spent a lot of time thinking about how to structure the webinar to ensure that our attendees got some takeaways, so decided to set the scene and then focus on some key messages and practical top tips here is a very brief overview of our webinar and most importantly our 12 top tips.
Why do we care about data literacy?
According to a Gartner Report in 2019 90% corporate strategies will mention information as critical enterprise asset and analytics as essential competency by end of 2022. 30% of chief data officers will partner with chief finance officers to formally value the organisations information assets for improved information management. By end of 2023 data literacy will feature in 80% of data and analytics strategies and change management programs. Data and data literacy therefore can’t be ignored; it’s here and its vital for business success.
What are the familiar symptoms (that could be associated with poor data literacy)?
- Poor data quality
- Excel used as the main tool for analysis and presentation
- Unused dashboards in business intelligence tools
- Too much data to handle and use
- Limited confidence in data
- Poor business performance and compliance
What are the possible causes?
- Capacity – staff simply not having time to ‘do data’ as it is not seen as a core element of their role
- Limited data skills which are related to legacy; not a skill that has been recognised as essential for all roles and all businesses
- No training or support plan to help staff develop data skills
- Accessibility challenges – data is not available to the right people in an accessible format
- Reactive cultures vs proactive – looking at pass performance and not seeing opportunity (or able to) to use data to look forward.
‘Data literacy deficiency’
There are however loads of definitions that cover this area, and important that you chose the language that you feel comfortable in your business. i.e. ‘data fluency’, data competency’’, ‘analytics capability’, ‘information literacy’, ‘helping people feel comfortable and confident using data’ etc
Our medication/self-care plan:
It is critical to have data literacy action plan to address the challenge, and people are a huge element to this plan so change management is also essential.
As part of the webinar we identified 12 (4 each) practical tips to help improve data literacy:
- Sell, sell, sell – you can’t underestimate the need to promote the use of data. Share the benefits data has in other areas of the business (or/and other businesses). Help people see that data will help them in their role. Think about a marketing plan, make data attractive not scary or boring!
- Create stories – collecting good data requirements is key to success and great way to do this is by creating user stories. Find out who they are and what role they have in the business, what problem they are trying to solve and what success will look like. The ‘5 whys’ is a great way to get underneath the surface of the business problem to ensure that the product that is to be developed makes a difference.
- Intuitive designs – create products (dashboards/analytics tools) that guide the data consumer. Make sure to do the heavy lifting, remember most people don’t have time to wade through lots of data. Make sure to keep the end user in mind and ensure that what is develop guides them through the data and enables insight. Make it efficient, effective and keep it super simple.
- Enable – skills for both those presenting and analysing data and those using should be considered. Make sure there are development frameworks in place for the analysts/developers, with clear milestones to work to. These skills can’t be learnt over night, they take practice so ensure time is given to practice and to grow. Provide feedback using positive language so they are encouraged to act on the feedback and not feel criticised. A coach and mentor will also be useful to provide this guidance and help them grow. Try to make it fun too this will help with motivation!
- Empower – devolve and trust your colleagues to use data to make decisions. Ensure they are provided with support and training, both for using the tools in place as well as support reading data. Find champions in the business that can help with this so that this support isn’t reliant on a small central resource.
- Iterate – Make sure to get feedback and build in improvement loops into the development time. Look at adopting agile project management methods into your processes. Continuous improvement is key in helping engagement and ensuring the products are reliable and useful.
- Always be wrong (Steve A’s controversial tip) – If people don’t trust your data you need to help fix the problem. Validate the data with your end users. If your dashboards aren’t being used enough, this is your fault, find out why, maybe the requirements collected weren’t right in the first place, maybe you didn’t understand the problem that needed to be solved. You need to build trust in your intention, in your process and in the future developments.
- Standards – visualisation standards. Increase the speed to market for your data products and increase the speed to insight. Create some standards so that your products have a consistent look and feel this will help the consumers get used to knowing how they work making them super-efficient. Consistency in the application of colours, in the application of shapes and in the notations and rules to help provide guidelines.
- Know your Why? – why are you going on the data literacy journey? How will you know when you get there? What does good look like? Any data literacy strategy needs to tie into your business strategy
- People First – data literacy is about giving everybody within your organisation the muscles, the muscles to be capable and confident to work well with data. Behavioural change is the biggest obstacle for any transformation, whether it’s analytics or otherwise. Everybody will be at different levels with their data literacy and understanding – put yourself in their shoes. Your role is to help is to support their learning and likely push people out their comfort zone.
- Borrow Ideas – lots of people and information that can help you in the huge data community. There is to need to reinvent the wheel loads of great ideas already out there; books, blogs, social media communities. Use the ideas and adapt them to fit your business and purpose.
- Make it fun – for you, for your community, for your team. It doesn’t have to be dull.
I am extremely passionate about data literacy and the webinar was loads of fun to do. It was great to work with the guys on this topic and be able to share our ideas and experience. We also had some great questions from our attendees which were well handled by our fantastic compere Neil. It was brilliant to see that our attendees had engaged with the session, and the questions really helped to enhance the content and provide more food for thought.
If you would like to watch the full webinar which will provide a better overview of some of the tips and includes the Q&A session at the end then you can find this through Steve Adam’s write up here: link to webinar/transcript
I hope you found this blog useful. Good luck with your data literacy adventure!
Feedback always welcome