How Data-Driven Enterprises Foster Innovation
Data drives simply everything. A business now finds it unimaginable to sustain and grow without relying on Big Data. Data is helping companies save costs, identify new opportunities, improve efficiencies, tell stories, and get a better understanding of the past to define a better future.
While these are some of the obvious benefits, big data is also helping companies innovate better. Data-driven companies are able to encourage innovation thanks to the effective use of large amount of information available at hand. How? Let’s see. By definition, innovation is a process of creating new products, services, or processes by using new or existing knowledge. Big Data facilitates exploitation of a large amount of data to facilitate the innovation process and create value.
Innovation is one of the biggest advantages which motivates a data-driven enterprise. Let us see how this exactly happens.
Data provides insights necessary for innovation
The data which is gathered has the power to provide insights for restructuring an existing business model. In other words, a business can make required changes to suit the prevailing market conditions and stay ahead of the game. Innovation does not always imply coming up with a new product or service. But at times, it can also mean new inter-departmental ideas to better the overall functioning of the company. For example, based on the data received, a marketing team can frame novel ideas for business growth in tandem with inputs from the finance department which can see if the plans are monetarily feasible. Then there is also the automobile industry which designs new innovative features in a car model to suit the next generation requirements. This can happen only when the company has access to data which shows what the younger generation wishes for.
Data helps in analysis
A data-driven enterprise can analyze a market picture in its entirety. It greatly helps in predicting future market trends, so that a business can plan or strategize accordingly. This also means that the business can work towards coming up with innovative solutions to counter the competition. Put it simply, this is a circle – Innovation also comes into the picture to forge new business models, for which again, one needs to heavily rely on data. Aspects such as sales demographics, consumer behaviour, etc. are important while analysing the market situations and accordingly forming a fresh-out-of-the-box strategy.
Need for structured and unstructured digital data
The structured data is more organised and is far easily understood. Innovating becomes simpler with such kind of information. On the other hand, unstructured data, as the name goes, has various bits and pieces of information and requires data mining tools to make sense of it. For instance, social media posts fall in this category. I mention these two types of data because a data-driven enterprise makes use of both these kinds to bring newness in their system, and not just always relies on the structured form. In fact, it is the unstructured category which is at times more preferred for the variations it allows required for innovation.
How this has helped some companies
Two biggest examples I can think of data-driven enterprises and innovation are Nike and Flipkart.
Nike, using data and analytics for innovation, redesigned some of its products through a Nike+ data-driven platform. They came up with a Nike+ sensor which is fitted onto a consumer’s running shoes or to their FuelBand (something which is more or less like the Fitbit). This sensor then collects data related to daily activities, measures calories burned, and so on. Nike has also devised an API (Application Programming Interface) so that others can develop mobile apps based on the Nike+ platform.
At Flipkart, the management decided to focus on improving customer experience using data. The data received gave them insights into selection preferences of their consumers. The company consequently made innovations in machine learning to match their product assortment/ selection. Going further, Flipkart has also come up with models to understand customer behaviour with statistical modelling. For instance, they can now evaluate products and list quality in real time. The search algorithms use the inputs to list the best quality products when a consumer searches for the same.
Thus, various competitive ideas can be implemented to improve on a company’s business growth while being data-driven.
To conclude, I would like to reemphasise my belief that becoming a data-driven enterprise is the way to come up with the right solutions for tackling the future business concerns. Innovation is the key to sustain and what else but Big Data to pave the way!