Data-driven organisations perform better. It’s a fact, backed-up by an increasing body of evidence to suggest that companies driven by data and analytics outperform those that aren’t.
A 2019 study by McKinsey & Company, for example, showed that companies where employees consistently use data in decision-making are 1.5 times more likely to report >10% revenue growth over the past three years.1
This study and many others are great at demonstrating the benefits data and analytics can bring to business. But if you just skimmed the headline figures you might miss the message on one of the key differentiators between a successful data strategy and an unsuccessful one.
The difference is data literacy.
Data literacy is defined as the ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied. Data is often described as a common language, so this all boils down to a simple question, “do you speak data?”
According to the same McKinsey & Company survey, the share of executives at high-performing organisations who understand data concepts is 44% higher, the share of managers who understand data is 39% higher and the number of frontline employees who understand data is 12% higher than other survey companies. The message from these figures is clear: data literacy enables higher performance.
Data literacy can empower employees to make fact-based analytics decisions that are more grounded in reality than the ones made on instincts or gut feeling. And you don’t need a PhD in data science to become data literate. There are some strategy-level actions you can take to help instil data literacy across all levels and functions of your organisation, which will help you on the journey to data maturity and unlock the benefits of a successful data and analytics strategy.
With all that said, I’ve put together 5 simple steps which your organisation can take, to help you become more data-literate:
Step 1: Start at the top.
The executive team should lead by example, showing that they support the idea that decision-making should be based on evidence and data, and using data in their communications. This helps to establish a culture of data as a language that will permeate through the rest of the organisation.
If team leaders and managers know that they have to use data or analytics information or dashboards in meetings with the executive team, they’ll begin to adopt data-based decision-making themselves and encourage their teams to do the same. Furthermore, those leaders will be able to effectively communicate and disseminate the analytical requirements that will drive their business making decisions throughout the organisation.
This is especially important because the people producing data outputs may not fully understand the overall strategic goals or how to effectively measure them like the executive leadership team would. Therefore, it’s vital that leaders at all levels communicate and encourage adoption and understanding throughout the organisation.
Step 2: Establish a baseline for data competency.
This varies for each company but can include teaching employees how to recognise data, ask the right questions of their data, understand the underlying analytic logic of that data and communicate their insight based on data with data storytelling.
Again, this doesn’t have to mean professional-level qualifications for all employees. It could be as simple as a checkout employee understanding what data is produced as a result of the interactions they have with the till and the need for correct input. With data, as with anything else, you get out what you put in. So, the more inaccurate or low quality the data you put into a system, the lower the quality of insights you’ll get from analysis of that data.
Step 3: Build role-based content
Try to think about what different teams and individuals need to learn regarding data and how they interact with it in their roles. Build role-based content and engagement tools to teach data literacy skills, which means presenting the training in ways employees will effectively digest it. Examples include blogs, webinars, in-person training sessions and providing dedicated time with data teams & specialists.
This is crucial to achieve buy-in and continued adoption throughout your organisation, as it helps employees understand how they can use data and analytics to perform tasks and how doing so delivers value both to them and the broader business strategy.
Step 4: Offer incentives
Make sure you offer rewards and incentives to get people excited about data literacy skills training and make it fun. It’s important not only to train new employees when they first start with an organisation, but also give existing employees reasons to engage in ongoing training.
Examples of this include internal initiatives with prizes, the chance to attend conferences and webinars, team-building activities around data and analytics and professional development opportunities that broaden the scope of your employees’ existing skills. Rewarding and recognising the development of individuals is a great way to gamify the learning, as it will encourage peers to achieve the same levels of expertise.
Step 5: Capture and publish key performance indicators
Any business strategy has KPIs attached and should measure success. Don’t be afraid to capture and publish these key performance indicators. It will help to demonstrate to employees the impact they can have on cost savings and revenue growth by applying data literacy skills in their roles. They’ll be more likely to use data in their decision-making if they know how it helps them perform better as teams or individuals.
Many companies are waking up to the realisation that data, and data-literacy, are key to success in the modern era. In a recent Forrester Research survey, 90% of data and analytics decision-makers saw increasing the use of data insights in business decision-making as a priority.2
However, less than half (48%) of decisions are currently being based on quantitative information and analysis, so there’s quite a bit of room for improvement. Whether you’re a start-up, an SMB or a large, global organisation, you can use these tips to begin the transformation to a data-driven culture and improve data literacy at the same time.
This article is part of our Data-Driven SMB series. For more information, advice and resources on how to accelerate your organisation’s data and analytics maturity, click here or contact us today.
James is an economist with 20 years of experience spanning the public sector (UK Government Economic Service), large-scale private sector consulting (with PwC and A.T. Kearney), and start-up through to scale-up business growth (with Concentra). Part of the founding team at Concentra Analytics, James established the Analytical Consulting practice and pioneered their brand of data-driven, technology-enabled, analytical consultancy.