Data is indisputably the foundation for success for any organization in today’s world. Not very long ago, investing in data and associated management strategies was touted as a way to gain competitive advantage. With the rampant and unceasing growth of data in the world today, data strategies have now become a necessity for survival.
The key to competitive advantage is to create data strategies which convert data into value. Data only becomes valuable to an organization when it is used to create action directed at improving performance, meaning that a fundamental principle of successful data strategies is the ability of business data users to understand and analyze the data with the objective of creating growth – in other words, the establishment and maintenance of a robust data culture in the organization.
As with any human culture, this process is an evolution, and takes time to absorb and spread. The anthropologist, James Spradley defined culture as “the acquired knowledge people use to interpret experience and generate behaviour.” Spradley talks about each individual as a proponent of a culture, understanding that cultural diffusion comes from socialization and comprehension of shared identities rather than the outputs of artists, writers or politicians.
An organizational culture is no different – people in an organisaton have a common identity in the form of shared values, traditions, behaviours and even language. Creating and spreading a data culture is a process that needs to therefore tap into and permeate this organizational culture, driven and shared from within, across all levels and departments of an organization. Lee, Morgan, Netherwood and Wong, in their article “The Behavioural Science behind Data Culture” talk about the development of a data culture starting with “being closer to people and their interactions, the challenges they face, and the things they care about achieving.”
Whilst each organization is unique, and will have varying schemes and preferences for spreading a data culture, there are several underlying factors that will ensure the success of their efforts. In-depth exploration of these factors are articles and books in their own right. Here I’ve aimed to summarise a few key points to think about, based on my own experience working with customers and within my own organisation. Most of these aim at changing behaviours. In line with Spradley’s observation of individuals’ behaviours as the representation of a culture – changing the behaviours will change the culture from within.
- Lead from the Top – top management must drive the objective of data-driven decisions, demonstrating that it is the norm rather than the exception. Even in our own data services company, lead by a group of data-heads, ensuring that all our decisions are linked to data is a process that requires us to consistently question our objectives and reasoning. This is a progression that has taken us to a new normal, where we keep each other on track and accountable for ensuring that our objectives can be reduced to quantitative and qualitative metrics that can be used to drive our business forward. To help us along this path, we’ve recently implemented the 12 Week Year (Brian Moran and Michael Lennington) at all levels of our organization to empower staff to set, prioritise, action and track their own metrics on a weekly basis, which in turn contribute to the company metrics.
- Focus on Storytelling – Whilst reporting on metrics is important to understanding where company performance is tracking, the true value of data comes from making sense of the story that the data is telling and creating action to take advantage of (or head off) the storyline. A true data culture encourages staff to take a strategic view and explain the metrics – the WHY of the data. As a simple example, sales are up by 20% due to a bundle promotion we ran. Volume movement was up, and although margin percentages were down, based on the past 6 months of sales, we would not have made the monetary profit we did without the promotion. The recommendation is to therefore run this type of promotion once a year.
- Reward the behaviours – To sustain the momentum of data culture evolution, it is crucial to reward the behaviours that create and diffuse the data culture. As company performance is linked to achievement of company KPIs, so should individuals be rewarded for not only achieving their KPIs, but also for their actions in propagating the data culture of the organization.
- Speak the same language – Language plays a leading role in establishing and maintaining a culture. I’ve worked with many organisations where people use different terms to refer to the same metric, refer to different metrics by the same name and use different business rules to define the same metric – a veritable tower of Babel! To drive a data culture forward, start with ensuring that everyone speaks the same language. Define the metrics clearly and create a single version of the truth understood by all and sundry, regardless of their department, promoting data driven cross-functional collaboration.
- Ease of Access – Whilst most organisations amass a ton of data, simply providing access to all of this won’t help the data agenda. Democratize access to data, but be artful about which data is provided when. Start by providing access to data supporting company KPIs. If all other metrics are related to this core KPI subset, and if the culture of the organization requires analytics and storytelling around these metrics, the requests for, and use of data will grow dramatically.
- Data Literacy – Finally, and, in my opinion most importantly, the process of empowering staff to access and work with data confidently is critical to unlocking true data culture. Gartner defines data literacy as “the ability to read, write and communicate data in context.” They further indicate that data literacy is “an underlying component of digital dexterity – an employee’s ability and desire to use existing and emerging technology to drive better business outcomes.” Many organisations fall short of the mark here as they believe that technical training is enough to create data literacy. In my experience, training business intelligence users to use a tool does not necessarily mean that they will be in a position to tell data stories. Without a focus on ongoing support for data literacy, tool usage spikes after the technical training session, then dies down as many users revert to what they know – even if the new tool clearly provides for faster and easier access to data than before. Creating a data literate culture will ensure that organisations get the most from their costly Business Intelligence technology investments. Training sessions should be one part technical, and 9 parts teaching trainees to use data to answer business questions. Ongoing data literacy initiatives require consistent support from those who understand the business and are confident with the technology. Support must be forthcoming rather than reactive. Identify enthusiastic data literacy champions who can reach out to their colleagues to assist them to find the stories in their data.
In summary, creating a data culture is about changing organizational mindsets and behaviours by empowering employees and demonstrating the positive impact that data-driven decisions can have at a company, department and individual level. It is an ongoing journey which needs to evolve as the business landscape evolves – just like any human culture.
“In God we trust – all others must bring data.” – W. Edwards Deming