How businesses are using data to evolve

DECISION-MAKING is key for any business: how the leadership of the business governs its management, how managers strategise and how the team performs overall depends on the decisions made.

The right decisions could lead to exponential growth; the wrong ones, to a failed business.

The most important tool for any business to make the right decision is data. This is why more businesses, from well-established companies to start-ups, are using more tools for gathering data in order to make the right decisions.

At the ICATT Annual International Finance and Accounting Conference at the Hyatt last week, panellists discussed data-driven financial management and how it benefits businesses.

Moderator Anthony Pierre, the managing director of Moore TT, said data analytics is evolving rapidly and being influenced by technological advancements.

“Big organisations are increasingly relying on the localisation of data and data analytics. To take strategic financial decisions, optimise resource allocations and enhanced overall operational efficiency.

“The ability to harness data does not only enhances decision-making, but also provides a competitive edge in a dynamic marketplace.”

Panellists included Michael Oderson, chief product officer of Enginuitty, which specialises in digital transformation; Kerri Maharaj, chief financial officer at the Unit Trust Corporation (UTC); and Nigel Newallo-Singh, acting head of security assurance and operations at IGovTT.

They all agreed data-driven management was not just about efficiently running numbers but about optimising business performance by taking a deeper look at operations, insightful analysis and making decisions based on the facts.

Getting the facts on your business

In the past, people made decisions based on market facts, financial statements and good old-fashioned intuition and experience.

Maharaj, in his presentation before the discussion, said the problem with this approach is there are often a lot of statements and beliefs in an organisation that become almost canon.

“People believe it and it becomes part of the decisions they make.”

He gave the audience at ICATT an example from Unit Trust, where it was always believed that its best investor was young and female.

“When we delved into the data, we saw there is a split of male-female.

"Then we looked at the amount of money invested by different age groups. It didn’t necessarily say they were younger.

“When we looked at the amount of money that the respective genders were investing, it was actually opposite to the first pie chart.”

The data, Maharaj said, brought the company to conclude male and female investors at UTC were relatively similar.

In another example, Maharaj spoke about a particular product that the company felt was essential, but the data showed something different.

“When we looked at our customer base, we realised the number of people with this product was ten per cent. The number of people that actually used the product was two per cent,” he said.

It raised the question of whether or not UTC should be investing in the product.

“It doesn’t mean that there was anything wrong with the product – it could mean that the awareness of the product was insufficient. But then it does then give us two different approaches: whether we invest in the product or we improve awareness of the product.”

Maharaj made the point that looking at the data could give new insight into a business and where it is having the most effect, what products have the most penetration and what the market really looks like.

“We are taking a different approach as we move forward,” he said. “We are looking at what happened, why did it happen, what could happen in the future and what we should do next.”

Big data, big benefits

Oderson said for international companies, data has become an integral asset.

“It is really what is driving the growth of a lot of companies. They are shifting and using the data as an integral resource in their organisations,”

Oderson said businesses that use resources to gather and analyse data get real-time insights and are able to make informed decisions and obtain predictive and prescriptive analyses.

With data-driven support, Oderson said, businesses now have transparency and accountability in how they make decisions.

Maharaj said using data-driven resources gave fast analysis, cost-reduction and improved decision-making.

“Most of the people in the audience have had an experience with a spreadsheet. When you send a report like this to someone they don’t use it, and most of the time you use some sort of parallel reporting to make sure they understand it.

“If you could switch that to something more like (a dashboard), where we work with them and design this report to what they would like to see, suddenly, they get actionable data really quickly.”

But both Oderson and Maharaj said in the region, businesses still have legacy systems that make it hard to access the wealth of data a company may possess for better decision-making decision-making. a

“If we look at companies today, we use Excel as the main tool,” Oderson said. “A lot of companies talk about big data, but if you are talking about big data it would be gathering data in the exabytes." (An Exabyte is a billion gigabytes.)

He said many companies have the problem that information is gathered, but not centrally stored. In order to get the data, technicians would have to perform separate analyses and pull the data together.

Maharaj said UTC had this problem.

“The data was there – it was 40 years of data on hundreds of thousands of customers and millions of transactions – but we couldn’t get it.

“We have a super-smart team member who figured out how to get this data from our systems, and we are starting to leverage it.”

Tools of the trade

Oderson said while the region still uses very traditional tools with some systems that can only be described as archaic, the tools that are driving data-gathering are becoming more accessible.

“Artificial intelligence has grown in popularity, because it is now consumer-facing.

"But that is just the tip of the spear. There are a lot of tools that can now integrate with your internal technology and give you that competitive advantage.”

He added that resourcing analytic tools has become less of a problem, especially in the online and financial services space. They include:

Tableau

Tableau is a visual analytics platform that includes AI and machine-learning capabilities. It is a leading business intelligence tool that helps use data for real-time analytics, data management and visual storytelling tools such as dashboards and graph generation.

It can be used with Microsoft Azure, which uses cloud services for building, deploying and managing intelligent applications.

Businesses such as global communications company Verizon, Mexican-style restaurant chain Chipotle and meal-planning and food-delivery company Hello Fresh use this tool.

Apache Spark

Apache Spark is an open-source analytics engine that processes large amounts of data.

Companies such as Uber and Shopify use it to manage big data workloads. Apache Spark generates structured query languages, which systems use as a standard language for database creation and manipulation, batch processing, graph process and real-time analytics.

Google Cloud AI

Google Cloud AI is popular among start-ups and new companies. It is a collection of tools and services used to create, deploy and manage AI applications and machine-learning models.

Its suite of tools includes an AI platform which makes predictions for new data; pre-trained models, API (application programming interfaces) that teach programs to communicate with each other and tools for tasks such as image and speech recognition.

It also has products that help extract, classify and split data from documents and conversational AI platforms.

Google Cloud AI also provides a two-three-week engagement programme and hardware for AI workloads.