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Many businesses will agree that data offers huge potential business value. Research from MIT and UPenn has found organisations that make decisions based on data and business analytics outperform those that do not. This holds true across critical business areas such as output, productivity, return on equity and market value. However, investment often comes at a high price. From data collection to cleaning, hosting to maintenance and analytics to security, the shift towards becoming a data-driven organisation can not only feel like more work but it can be compromised if the human and organisational factors are ignored.
Businesses must recognise the transformation that needs to take place from within. To fully capitalise on their data, organisations need employees at all levels to understand how data can be used to drive new and existing business – not simply operational efficiency. This requires a strong data culture that encompasses various aspects: wide access to trusted, high-quality data, data literacy, value and belief systems, and leadership. Without this foundation, organisations will not be able to maximise the impact of their investments in data infrastructures and turn insights into action.
Starting from the top
To set and execute on a business strategy driven by data and analytics, businesses need a senior sponsor to champion the value of data and work closely with employees at all levels to communicate this message. By sharing a clear vision of how data will enable the business to grow and empower staff to drive real change, these leaders will inspire employees and reshape their attitudes towards data; motivating staff to use data in their decision-making and rise up as data citizens. This is also an important step in promoting the idea of data as an asset; educating employees on how the data they come across on a daily basis ripples through other parts of the business. In other words, employees must be aware of the bigger picture.
Similar to any business proposal, encouraging a data culture requires both salesmanship and a value proposition. The aim is to get employees excited about the potential data can have, not just for their organisation, but for their business function. A way of doing this is by giving a practical demonstration of how various types and combinations of data can be used to discover insights. For example, any individual customer is likely to have their data held in multiple systems and by different teams; from finance, to customer relationship management, to customer support. Each system will offer different insights into the customer’s behaviour and by connecting these data sources, businesses benefit from a more holistic view of the customer’s life cycle. This takes customer intimacy to the highest level.
With a recognisable figure at the top lending their authority and influence to the data cause, leaders can also not only rally support for a data transformation across the organisation, but also use this support as a springboard to justify further investments into data infrastructure.
Auditing for progress
Another critical step in igniting a data-driven transformation is conducting a thorough audit of various business units and departments. By analysing team structures and processes, organisations can find out how data is being used at every level. It also enables them to determine the areas where data is being used effectively, allowing the executive data leaders to identify and work with the main agents of change within these units to catalyse a wider data transformation across the board. Similarly, it allows businesses to identify potential risks, diagnose areas of improvement and assess how these problems can be solved.
These audits can lead to the discovery of other deep-rooted problems – for instance, a lack of understanding on how to actually integrate data into daily tasks, or having insufficient technology and tools in place. Such information is vital in any data transformation, as without identifying a starting point, organisations will not know how to improve or identify the steps they need to prioritise moving forward.
While this approach gives businesses a micro-level view of their data structure, it is also important to have a high-level macro view. Mapping the data supply chain (tracking the path of every data set, allowing leaders to answer questions like who owns the data, who consumes it, what decisions they make with it) helps businesses paint the bigger picture and provide context on how individual data use fits in with the wider organisation.
Building data literacy
Offering training and other support resources is key to building data literacy in an organisation and for integrating data into existing business processes. Visibility and education must be provided across all vital areas such as data cleaning, management, visualisation, business intelligence, catalogues and data governance. Without this, employees will not only fail to understand how to use data, but also lose the curiosity and drive to learn how data could benefit them in the future.
Understanding employees’ backgrounds and explaining data to them in relevant terms can help leaders overcome this obstacle. Psychology shows that people learn by assimilation and accommodation (proven by decades of research in cognitive development), therefore understanding existing mindsets will be key to making education effective and introducing new information. It may be helpful to avoid complicated technical jargon, as this may alienate the average data consumer – rather, leaders can reframe data terms in the business language employees are familiar with. While this may require a tailored approach, it will help to demystify data and build a more inclusive environment.
Not all employees need to transform into experienced data scientists overnight – data culture simply means that people can understand how to leverage data and glean new opportunities and knowledge from it. This is becoming crucial as customers’ data provides a wealth of knowledge into their wants and needs. Businesses must have the right processes in place to transform those data insights into action, as data culture and data success go hand-in-hand. No matter how well-crafted or advanced a data strategy is, it will block its own success without a data culture and data citizens to execute it.