Taming Big Data Analytics

Data can be compared to the missing piece of a puzzle. Used correctly, it can have numerous benefits for a company, including better customer retention, cost-savings, improved customer engagement, and a clear direction of how you can expand your services and offering.

Varsha Ramesar is the Cluster Executive for Data and Analytics at iOCO. Her role entails collating data competencies across the company into a single value proposition for clients.

“I come from a computer science background and have always been fascinated by data. It’s incredible how this technical information can translate into something that benefits a business,” Ramesar says. “The skill lies in correctly harnessing it for an outcome that has measurable results. iOCO’s value proposition is that we can consult and advise from a strategic perspective, including analysis, interpretation and execution of the data.”

With data analytics, it can be difficult to know what to do and where to start. Companies need to be able to assess their data, and understand milestones, and that is where iOCO’s specialist skills come in.

The four Vs of big data used in analysis include volume – the scale of the data; variety – its different forms; veracity – the quality of the data; and velocity – the speed at which data is processed and analysed.

The companies that obtain the best quality data can do the most with it. To create the best value proposition, you need to understand your customers, and then have the data handled by the right people, aka domain experts, who can add meaning to it.

Velocity is another challenge. Data needs to be processed at speed and analysed quickly to be useful in turning insights into action. For example, Elon Musk’s self-driving car must make a nano-second decision on whether the object on the road is a leaf or a living animal.

Two of the most successful companies in terms of data analytics are Netflix and Uber. These IT companies built their world around data and have been able to swiftly customise their offerings to create new value propositions. For example, Uber Eats has grown beyond the servicing of the traditional restaurant and there are now companies that are making custom cuisine, direct from a kitchen warehouse to the Uber Eats client.

Other companies had to swiftly adapt during lockdown. Big supermarkets faced the challenge to come up with alternative business models in the new, post-Covid landscape. “They had to use their available data to create an online platform, and the data had to enable them to make decisions like: Will our customers use an app? What locations make sense to include? Can we work it logistically? What times of day should it run? How many services should it include? What products can we cater for in this service?” Ramesar says.

Checkers Sixty60 quickly accelerated into this market, while other stores proceeded more cautiously. Meanwhile, small companies like Zulzi – an online shopping app that includes groceries, liquor, pharmaceuticals and food – had the data and agility to expand fast. Zulzi obtained additional investment and grew substantially during lockdown.

Ramesar says data analysis is a continuous process. Understanding patterns allows you to predict what the uptake and profitability of a new product or service will be.

“iOCO’s strength lies in being able to ‘democratise’ data – taking it from a technical place into the customer’s hands, where it can be used to define a customised solution. There is no copy-paste recipe. We have worked in many different industries and can create the right fit for each business that will give maximum value,” Ramesar says.

The original article was published in Brainstorm Magazine on the 9th of June 2021