5 ways to improve data culture

Data culture is at the heart of data success, but there is always room for improvement, particularly in departments outside of the data team.
DataIQ members discussing data culture

Data culture often sits hand in hand with data literacy as the two have a symbiotic relationship. The difficulty, however, comes from getting decision makers to understand the importance of a strong data culture and any buy-in that it would require. It is often down to CDOs and data team leaders to take the first steps in improving data culture to highlight the business benefits.  

 

Establish strong internal messaging 

Ensure there is a regular and well-developed route of contact between the data team and any internal (and external) comms teams. Options can include sending weekly updates that cover things such as: 

  • Progress of ongoing data projects 
  • New data products 
  • Uses of data 
  • Ambitions for data in the business 

 

If the profile of the data team is consistently shown across the business, other departments will start pulling on data resources for their own targets. This is a core milestone in any data culture evolution as the business should pull on the data team, rather than having data forced upon them.  

Data leaders need to get into the habit of clearly explaining data-driven decisions and demonstrating the ways in which data can influence operations and the direction of departments and the wider business. This can be achieved with assistance from internal comms teams that can help edit stories and ensure the right messaging is achieved for the target audiences.  

 

Data culture needs a top-down approach 

A business that has a strong data-driven culture will have top level managers and executives that expect decisions to be backed up by data; they lead by example. There needs to be a series of practices about utilising data that trickle down through the business hierarchy to every corner.   

Ways that this can be achieved can include: 

  • Starting all top-level meetings with a briefing on data updates. 
  • Ensuring that all summaries and proposals are backed up with evidential data.  
  • Sift through the evidence of controlled trials with business leaders to decide on product launches. 

 

A major challenge is making it relevant for data consumers, which is why a top-down approach to data culture can be so beneficial. Most colleagues find their roles challenging enough, so finding time to upskill and adopt new data tools is often a low priority. However, if those tools provide relief from a routine pain point, for example, it becomes compelling to engage, and this can be best demonstrated by business leaders outside of the data office. 

 

Develop and publicise common data language 

Data comes with its own language that can be a barrier to entry, so it is pivotal that data leaders find a way to make a common data language. This can be achieved by working closely with the leaders of other departments to find common ground examples which highlight data processes and terminology.  

DataIQ members have mentioned that middle management is often the most resistant towards adopting data and analytics – particularly if they have a long tenure. The language of enablement, privilege and benefit will land better than anything that sounds like a threat to their status and job.  

As AI tools continue to develop rapidly, there are concerns that people will lose their roles to machines; this is a prime opportunity to create a common language that puts these fears to rest and demonstrates the colossal benefits of data-driven tools to every department.  

 

Showcase data success stories 

This can tie-in nicely with the first point about internal messaging, particularly once business leaders and the executive board are aware of data success stories. By having non-data professionals showcasing the power of data, it can have a catalytic effect on the development of data culture within an organisation.  

For example, if the CEO names data as a key enabler of their vision because data has been shown to provide success, it is hard for teams across the business to resist the change. If business leaders tell investors about their big plans – even if this is ahead of the culture change – it is more likely to happen.  

The caveat is that this does require getting buy-in from the top level of the business, which can take time, particularly if there are members that simple do not understand data.  

 

Measure the progress of data culture 

Managing the progress of something intangible such as data culture can be difficult, but it is not impossible. Leaders need to carefully select what to measure, and the metrics teams should use to monitor the success.   

For example, businesses can profit by anticipating competitor price moves and this can be monitored by predictive accuracy through time. The better the data, the stronger the accuracy.  

Start off by noting how many people outside of the data team are actively engaged with data, and see that number grow over a period of time. The more people that utilise data, talk about it, and demonstrate how data has impacted achieving their objectives. This can easily be tracked through short questionnaires conducted quarterly, as well as giving the opportunity to ask more specific questions about data that are relevant to your specific business niche.  

 

 

DataIQ provide a measuring assessment that surveys the maturity of data culture across the organisation and provides benchmarked scores highlighting areas of strength and weaknesses. 

Download the latest report to see how DataIQ measures the ten dimensions of data culture. Access tips, tricks and stats explaining how to improve in each area. 

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