Making Data Usable

Without order, data is just a bunch of numbers floating in space. How can organisations make sense of the richness of information available to them and who are the professionals capable of helping them reach data nirvana?

It’s not how much you collect, it’s what you do with it that counts. For a long time, organisations have been aware that capturing information is just the first step on the journey to data nirvana, and that steps two and three – those of refining it and converting it into something tangible – are every bit as important.

How to Ensure Data Usability

Without structure, data just takes up virtual space, like an old file cabinet left in a dusty stock room with folders from 1987. It’s no use to anyone unless it’s moulded into the sort of human-friendly insights that people can really use.

This takes time, software, and, perhaps most importantly, people.

The importance of rationalising data is well summed up by Sherlock Holmes in the Arthur Conan Doyle short story The Adventure of the Copper Beeches: “Data! Data! Data!” cries an exasperated Holmes, “I can’t make bricks without clay”.

Meanwhile, the effort needed to order that data is well described by F. Scott Fitzgerald in his foreword to This Side of Paradise: “…to write it took three months; to conceive it – three minutes; to collect the data in it – all my life.”

Who Can Help Make the Most of Data?

We know businesses come in all shapes and sizes, so there’s no universal adapter they can all plug into. Large organisations might want to recruit an oven-ready division of data experts, including architects, analysts, and engineers, all the way up to heads of department or Data Product Owners who sculpt the helicopter strategy before kicking it up even higher to the executive suite.

Small and medium-sized enterprises rarely enjoy the luxury of splashing out on a new team of pre-trained professionals, so hiring consultants or investing in skills within the existing headcount might be better options.

Consultants, for example, can parachute in for a defined period of time, righting the ship and providing a blueprint for the future of your organisation before leaving you to get on with it.

They can provide a quick no-nonsense solution, with expertise ranging from researchers to project managers, many equipped with advanced skills in areas like AI-driven project management, predictive analytics, and automation.

They are also flexible, able to work to a single objective or a handful of goals, without distracting the core team from everyday operations.

Even better news is that the availability of contractors is increasing and their skills are improving, with now more than 100 universities offering courses in data science, analytics, and machine learning in the UK alone.

This is just one of the factors driving the data industry globally. Another is profits. According to Markets & Markets, the industry for artificial intelligence applications will surpass $400 billion in value by 2027.

By 2030, AI will have boosted US GDP by more than 20%, says Statistica, and more than six in ten business owners agree it will increase productivity, according to Forbes Advisor.

So if you haven’t got your house in order, now’s the time to do it.

How to Make Data Useful

While the explosion of data provides enormous opportunities for businesses, its sheer volume and complexity can make deriving actionable insights challenging. Back in 2016, Forrester reported that 74% of firms claimed to want to be data-driven, but only 29% are actually successful at connecting analytics to action.

Fast forward to 2024 and actionable insights are still the missing link for many businesses needing to drive business outcomes from their data.

Data usability happens when organisations convert raw data into easily digestible formats through visualisations, dashboards, and written reports that allow decision-makers to grasp critical insights quickly.

Companies that excel in making data usable typically have a few elements in place:

Centralised data platforms: Many businesses are moving towards centralised data lakes or warehouses where data from various departments is aggregated, allowing for a more comprehensive analysis across different functions.
Data governance and quality: It goes without saying that ensuring that the data is accurate, clean, and trustworthy is essential. Data governance frameworks help monitor the quality and consistency of the data, which directly influences the reliability of the decisions derived from it.
Democratising data access: Making data usable requires that it's accessible to the right people, including non-technical stakeholders who nevertheless must engage with data. Self-service business intelligence (BI) platforms like Power BI, Tableau, and Looker allow users across departments to generate their own insights without needing data science expertise.

From Data to Decisions: A Strategic Approach

To transform data into decisions, organisations must create a data-driven culture, one in which data is a touchstone resource from the grassroots to the top table.

Fostering an environment where data is valued at every level is a complicated and somewhat arduous strategy play; one with the following ingredients:

Integrating Data into Decision-Making: Organisations that thrive on data-driven decisions typically use predictive analytics and machine learning to forecast trends and inform their strategies.
Real-Time Decision-Making: With the help of AI and machine learning, companies can analyse data as it’s generated and make timely adjustments to strategies.
Actionable Dashboards and Data Visualisations: Making data usable means turning it into formats that support swift decision-making. Dashboards that visualise KPIs and other key metrics in real-time are becoming indispensable for business leaders.

José Esteves, data expert and head of the Porto Business School, argues that the introduction of structured information, powered by AI and presented to the C-Suite in the right way, can make a huge difference.

“Very few organisations can provide sufficient levels of analytical information to top leaders, so ‘gut instinct’ was created as a way of surviving,” he said in an interview with Raconteur. “But AI can help to create scenarios, assist with planning and enable better foresight than before.”

So whether it’s upskilling, hiring expert consultants, or drafting an entirely new team of permanent professionals, every kind of business has the chance to become turbocharged with the help of refined data.

What are you waiting for?

To read other articles in our Data series, please visit our Insights page.