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Challenges organisations face in becoming data-driven

Despite increasing investment, many companies are struggling to maintain momentum in their data strategies. A recent survey from TechCrunch states that 72% of large companies haven’t been able to create a data-driven culture. 

With many organisations devoting more and more resources to their data strategy, this isn’t due to a lack of trying, however the sheer scale, complexity and number of employees at large organisations can often disrupt successful strategy implementation. 

Here are some of the common challenges companies encounter on the journey to becoming a data-driven organisation. 

Accessibility & Autonomy

There’s a big difference between making technology available to employees and having them embrace it. One of the first challenges companies address is how to make data available in a secure way for staff to use, as demonstrated in a recent study cited by  Harvard Business Review that saw 77% of executives report business adoption of data analytics initiatives is a major challenge.

To increase analytics adoption, it’s critical to ensure that data and analytics are available in a format that is tangible and understandable to employees, and can directly correlate with processes they run and decisions they make. 

Often to be most successful, teams should give some autonomy to the end user, by ensuring that the right tools are in place to facilitate self-service analytics to support the complexities on the ground. 

Trust in Data

Many companies struggle with establishing trust in their data, despite a significant investment of time and resources into quality assuring data to ensure it meets requirements. Data can be sourced from multiple platforms, departments or external suppliers, and is often received in different formats. This results in effort being expended to reformat, validate and consolidate data to support analytical needs, work which is often manual and unregulated. 

Aside from the significant effort to correct and prepare this data, there are also impacts of data sourcing downstream. Employees utilising data that has been sourced from colleagues or shared access points can often be unsure of when the data was created and where it came from, leading to a lack of trust in that data to power analytics, and decreased adoption of data tools, or duplication of effort where employees are running multiple manual quality assurance processes for different use cases. 

Organisations looking to resolve this issue are investing in data supply management tools, to automate the collection of data from multiple sources and platforms in a transparent, regulated way. Platforms like gather360 complete quality assurance, transformation and consolidation activities in an automated environment with an Audit ID. This empowers employees to look up information on where the data came from and how it has been processed, which builds an implicit trust in the correctness and completeness of data. 

Data Overload

Many large, data intensive industries are facing the challenge of data overload, where valuable data is not being utilised to drive insights as there is simply too much information available within the business.

To ensure that these opportunities are utilised is essential to utilise new technologies such as automation to sort and prepare data, and advanced analytics like Forecasting, Artificial Intelligence and Machine Learning to uncover insights lurking within millions of stored data sets. The more valuable insights an organization is able to extract from data, the more data-driven their decision making can become. 

Becoming a data-driven organization does not happen overnight. There is a lot of elements to be considered, from access and availability to culture and technology, and these efforts unfold over time. However, ensuring that your data strategy considers all elements including access, trustworthiness, education and technology will set up your organisation for success. 

Build a future-focused data strategy

At Think Evolve Solve, we support companies across multiple industries to create a data strategy that works for their organisation. We’ve made it our mission to create a simple, fast, and effective way to plan data strategies that work. Find out more about how we do that here. 

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