Building a strong data analytics culture starts by changing the conversation about data

A data-centric culture requires both transformative technology and transformative thinking, and it’s one of the best ways businesses can gain a competitive advantage

Despite most businesses claiming to be data-driven today, common issues around siloed and unusable data are still stalling analytics projects and new technology deployments across industries – ultimately impacting brands’ relationships with their customers, and consequently, their profits.

The problem is two-fold. Not only do outdated technologies or practices often leave teams unable to access the data they need to uncover new insights or pinpoint where issues occur in their various operations, a lack of data culture means that even if insights are available, most teams think it’s not ‘their job’ to look at the data. Successful brands that are customer-focused prove every day why this thinking should be reversed.

When everyone in the organisation can interrogate, interpret and act on data in a self-serving way, this creates a hunger or buzz around insights that intuitively moves the company forward towards more innovation and customer-centricity. The first step to achieving this is ensuring all relevant data is collected and made analysis-ready for every team and department in the organisation.

Data democratisation with the modern data stack

Today, the simplest route to a business model where every team member can query company data and interpret the results is enabled by three core technologies that collectively make up the modern data stack – automated data pipelines, a cloud data warehouse and modern business intelligence. Together, these technologies not only eliminate the number one data challenge identified by customer-facing teams – the lengthy and labour-intensive task of integrating all relevant data from diverse and fragmented sources – they also allow for data to be visualised in company-wide dashboards that every team member can view and use.

The second hurdle comes to the fore at this point. Even once companies centralise their data and make it available for their various teams, the challenge of how this data is used still remains. Businesses must next mobilise their entire talent pool around this data by translating its benefits to users in terms of three simple functions:

Data as an answer

Nearly all decisions a business makes are related to data, yet you will hear a surprising number of employees say “my job doesn’t require me to look at data.” A lack of clear ownership and responsibility for data among team members means that when opportunities are missed, it’s difficult to pinpoint where issues occurred or where improvements can be implemented, or even that opportunities were missed in the first place.

The first thing leaders must do is show their employees how data can help them do their jobs more efficiently. They should begin by asking each department what their biggest challenges are; what their ideal outcomes would look like; and, connecting the two, explain how data holds the key to the solution. Soon enough, employees won’t just look at data as the answer to their existing questions, but as a springboard to ask new questions.

Data as a product

Data is often treated as a concept by those who do feel far removed from it, but it is in fact a product, which requires buy-in, usage, maintenance and a good return on investment (ROI) just like other tools. Demonstrating early on how data can solve strategic problems for the business will spring new use cases and help leaders scale data usage in the same way they would with a product. One of the best indicators of ROI is then how many active users interact with the dashboards and reports on a daily basis.

The more eyes there are on the data, the more questions a business can answer and uncover. This requires a high degree of independence, so it’s imperative the supporting technology makes data analysis, visualisation and interpretation as intuitive as possible. When fresh and relevant data is easily accessed and presented, its users will develop a self-serve attitude and increasingly draw on this data to inform their work.

Data as a language

Finally, being able to interpret this data is the secret sauce to creating a common language that enables out-of-the-box thinking and customer-centric innovation for organisations. Practice makes perfect, so the more chances team members are given to manipulate the data and use it for their strategic needs, the better.

When data-driven problem-solving starts seeping into the day-to-day life of employees, data will become like any other essential product a marketer, customer service agent or financial planner uses to do their job. Before long, meetings focusing on problems will turn into brain-storming sessions about the future, and data-driven decision-making will be second nature for everyone in the organisation.


About the Author

Nathaniel Spohn is VP EMEA at automated data integration provider Fivetran. He is responsible for the growth of Fivetran’s first European office in Dublin, Ireland, and provides consulting on a wide range of Data Warehouse, Business Intelligence and ELT requirements. Prior to Fivetran, Nathaniel worked in the 3D Printing industry spearheading a business development function based in California.

Featured image: ©eliahinsomnia

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