By Raj Vattikuti, CEO, Altimetrik
Data is fundamental for any business to see real transformation. Relevant data can help in transforming businesses and achieving real outcomes. With data, we are able to understand customer behavior and personas in a much better and clearer way. Build services and various opportunities to serve different segments of customers by analyzing their behavior and personas. The right perspective towards data is that it has to be relevant, and technology has to be simplified to derive outcomes.
The other aspect is to connect different business entities to make them more operationally efficient. Today, the most important factor is the collaboration of business and technology. Business needs to take ownership of making sure that the data is aligned to specified business outcomes. Only then you can apply AI algorithms or any other technology to be more effective.
Data is driving product opportunities by connecting the consumers and evolving new business models. However, today, many companies are trying a big-bang approach to make sense out of it. In the pursuit, business is of very little relevance to actual outcomes.
We are helping our customers take an incremental approach based on the priority of their business outcomes. This takes data in a sequential and streamlined manner to the relevant data lake and provides actionable insights aligned to the business objectives and outcomes.
It could mean co-creating new products by listening to customers in real time, which we are presently working on with one of the largest global apparel makers. It could also mean increasing marketing effectiveness and fast decisions, connecting marketing, sales, and the supply chain. We have had recent success in doing this with a P2P lending platform in the European market. Risk management and compliance is another outcome that can be handled with data, which is a rising problem in the banking sector, and we are helping our BFSI customers in this area.
When you take the incremental approach, the business is able to map the entire process of data handling to actual objectives.