The Various Types of (Data-Driven) Business Innovations

Henry Ford had once famously stated that if he had gone around and asked what the customers wanted they would have said faster horses. But that era is long gone. In the current scenario where more than 40% of the product launches fail, it is imperative for the organisations to exactly know what the customers are looking for, anticipate their needs, and then innovate accordingly. Data, the new soil, is playing a crucial role in helping organisations go beyond gut feeling and exactly know what their customers are looking for.

Talking about innovation, while I quoted the example of Henry Ford, I believe that innovation goes much beyond just the product innovation. Let’s talk about three categories of innovations – product, process and Business Model.

Product Innovation

A majority of the times, when people think of innovation, it is product innovation they are referring to. It involves either of the following three cases – enhancing an already existing product (The recent example being, Apple coming up with a dual sim phone, which is a first for them). Develop a new product like Fitbit or optimise the already existing features, like an OS update.

Technological advancements, changing customer requirements & industry landscape are generally the key drivers behind product innovations. Behind the scenes, there is a lot of structured and unstructured data flowing into the system. Market researches, competitor behaviours, audience reaction from A/B testing, etc. form the basis of data analysis – insights from this data helps in preparing product metrics and product KPIs which assist the product team to innovate.

One of the most popular examples of product innovation in our day to day lives is that of beauty product brands which leverage big data to come up with innovative products. These giants collect vast amounts of data regarding the kind of products being brought, what composition, and what type of customers (skin type, area) are buying those. With better insights into those parameters, these brands expand their product lines. Over and above that, they also use the data collected to make recommendations to the customer regarding the type of product they should choose.

Most of the premium automobile companies are running simulated test drives to innovate and better their products by gauging customer reaction and also by sensing which features are mostly used and which are not.

Process Innovation

Process innovation is the least appealing of all the innovations, as the results of process innovation are not obviously evident to the customer. However, these can lead to various long-term benefits in terms of faster time to market, reduced costs, minimal wastage, and enhanced productivity and efficiency. A process is a combination of resources, technologies, and skills being consumed by an organisation to generate a product or service of value. Data-driven process innovations have already become a part of the mainstream logistics and operations ecosystem of organisations. Enterprises worldwide are leveraging Robotic Process Automation and IoT-based sensor data to optimise their internal processes. Many heavy equipment manufacturers are capitalising on the IOT data being fed into their system to provide predictive maintenance. This goes a long way in reducing time to market and enhancing customer experience. Nowhere else is the effect of data-driven process innovation is more pronounced than the fulfilment centers of Amazon – The real-time tracking of delivery fleet helps the company in giving visibility to logistics and subsequently optimise the whole process.

Business Model Innovation

The advent of the digital era has unlocked new potentials to come up with newer business models. Uber has become the largest taxi service and Airbnb is the largest supplier of rooms worldwide – it is interesting to note that both these companies are technology companies leveraging the power of data and neither of them owns any physical assets.

Retail giants are analysing vast amounts of customer data available to them to get a 360-degree view of their clientele, which allows them in more accurate target marketing. Insurance providers are analysing external and internal data to automate underwriting and for calculating the premiums with lesser effort and increased accuracy. Differential pricing on the basis of the seasonality of demand has become more of a norm rather than an exception in the airlines’ eCommerce and other digital business. The customer loyalty score and index are also used to show different prices to different customers. eCommerce and OTT content providers are leveraging analytics to customise the landing page for every individual on the basis of the products and items that interests them. One of the most recent and celebrated examples of business model innovation is that of the Rolls Royce aircrafts turbine manufacturing segment. Rolls Royce leveraged the data available to them and decided to drastically change their business from selling turbines to leasing the turbines out to the clients. The whole new business model is based on performance-based contracting. Data points like performance, operations, maintenance are crunched to derive at the contract value.

It won’t be an exaggeration to say that the convergence of data points about operations, productivity, socio-economic factors etc. will serve as important inputs for streamlining and for bringing in data-driven innovations.

That’s why I believe that data is not only the new oil but data is the new soil – the soil which helps organisations create new opportunities, new services and products, and fosters innovations. Just like the soil, it needs to be appropriately ploughed, right seeds need to be sowed, and it needs to be cultivated.