The three biggest obstacles when creating a data-driven culture
How organisations can shift to be more data-driven.
November 3, 2020 | By Ram Palaniappan
Organisations have always seen their data as an asset, and in the last five years, more and more have realised that data can be used as a competitive advantage. But the missing piece of the puzzle is understanding what type of data is needed for an organisation to drive change and act with agility—and how to collect it, process it and leverage it for competitive advantage.
The key to a strong data strategy is establishing a long-term business vision and then driving the strategy toward it. But constantly evolving market conditions and business models force us to consistently relook at our data strategies to address current impacts and future plans.
Every organisation should reevaluate their data strategy and realign themselves based on how the business performs outside of external influences. Companies often inspect metrics like customer demand, timing and revenue—but these are all inward-looking data points. There is a huge opportunity to look outward: what other data is influencing our views? What external factors are influencing customers to buy products?
The following are three of the biggest obstacles when creating a data-driven culture—and how to overcome them.
1. Defining your data platform and strategy
The first obstacle in creating a data-driven culture is clearly defining your data platform and collecting the right kind of data. Your data platform strategy and managing data across your business units needs to be synergised, or else you’ll find yourself trying to climb out of a chaotic data structure. If various business units within the organisation are each trying to collect and use their data to drive business strategies, but the organisation doesn’t have a common data platform or clear definition of the data that’s being collected, two things will happen: you’ll spend more money because teams across the business are trying to do the same work that could be consolidated, or you’ll incur more chaos because of the different ways data is being collected and processed. Ultimately, when looking at the organisation or strategic initiatives as a whole, you’ll have a difficult time getting an accurate picture without a single source of truth.
2. Understanding the right datasets for deeper analytics and insights
The second obstacle is fully understanding the right datasets to collect and process. It becomes harder if you don’t already have the proper technology in place to pivot. Having the right architecture for data analytics—from cloud-based platforms to open-source frameworks—is crucial to analyse high volumes of datasets and, in turn, provide deeper insights into your business. Understanding and prioritising the right kinds of data will help support the business through rapid changes, resulting in cost-efficient and effective decision-making.
3. Ensuring teams are data-literate
The third obstacle is folding in the right people; finding a good cultural fit can be the hardest part. Upskilling existing talent when possible can be an effective and valuable solution. For example, if you have an SQL programmer, you may need to upskill that person to be proficient in Python® and Spark® for the latest cloud technologies. If your people have developer fundamentals, the transition to picking up additional technologies through learning solutions courses shouldn’t be overwhelming.
Clarity will help you respond to disruption
When it comes to disruption, no one has a plan. But when companies need to respond to disruption, those that will be successful will respond quickly based on their data, numbers and feedback—in real time. In order to use data critically to influence agility and make sound business decisions, organisations must cultivate a data-driven culture through technology and people.
Senior leader, innovator and technologist Ram Palaniappan brings broad experience in big data, BI, mobility and cloud solutions. Ram has worked with Oracle and Deloitte and is a featured thought leader in the space, including contributing to articles in major IT publications, such as Information Week, and serving as a featured speaker at multiple forums and conferences.