How to Sell the Invisible in the World of Data and Digitization By monitoring following things leading technology companies have identified the most basic demand of the customers

Data is the new gold – as hackneyed as this popular catchphrase may sound, its relevance only grows by the day. The fact that Data is everywhere and is waiting to be harnessed in a variety of ways and for a vast suite of purposes exemplifies the power that it holds for businesses. Yet, whether a business is able to ask the right questions of this data and find the appropriate answers, is what determines its success and relevance in the highly competitive business landscape that we inhabit today.

The Background

Manufacturing companies, over the last few years, have been collecting data and leveraging the insights it offers for a variety of functions – improving operational efficiencies, refining their business models, reducing manufacturing costs etc. However, in a world where the customer is aptly known as king and where manufacturing is ultimately targeted to build products for the end-user, organizations need to actively start tapping the power of data to give their customers exactly what they want. Digitization is a great disruptor, so business leaders can either use it to power their next big move or let their venture concede to the disruptive entrants.

The Functioning

While data and the insights it offers to map customer behaviour are regularly being leveraged by consumer internet companies, the relevance of this practice for a traditional manufacturing firm cannot be overstated either. A large number of forward-thinking companies are already putting data analytics to use to fine-tune their products, forecast demand on actionable insights and optimise their production lines. An IDC survey suggests that by 2021, 20per cent of all global manufacturing firms will rely on IoT and data analytics based infrastructure to speed up execution timelines by 25Per cent. Eventually, the use cases of data will also expand to help businesses understand customer preferences and adoption such that the process becomes an integral part of the manufacturing industry.

To be competitive, manufacturers need to utilize the many data points spread across their value chain – from channel partners, suppliers and smart products to customers – to truly understand what they need to be doing to make their customer happy. By using the many insights that digitization offers, a lot of businesses are not just streamlining existing products, they are coming up with a whole new category of offerings and business models that really plug the gaps in the market.

The Result of Monitoring

It is on the basis of such on-going monitoring of consumer behaviour and market demand, that some leading technology companies have identified the most basic demand of customers - that of clean air - and commoditized the same. By understanding customer needs and gauging their preferences regarding how these needs can be met, tech innovations have been created to offer a practical and impactful solution to an almost intangible and invisible problem that has been plaguing a vast number of Indians for many years now. By understanding the importance of analyzing various disparate data sets and coming up with a business model that truly appeals to target customers, such players are not just ensuring deep consumer satisfaction but are also disrupting the industry as a whole and making clean air, a vital necessity, more accessible.

An obsession with customer engagement has also led many top players in this domain to apply digitization in another aspect – that of using maintenance and performance assurance systems to create a complete and evolved customer experience. In the manufacturing space, it is important to marry the digital with physical experiences to ensure overall and sustained customer satisfaction. The way to best achieve it can only be gauged through substantial use of data insights.

The success of such a model of experimentation and validation is also encapsulated in the popular "Lean Startup' methodology that has been widely advocated by entrepreneur Eric Ries. The idea is that a startup must be agile while building and fine-tuning a prototype. It should be ready to launch an iterative product, much like a proof of concept, and continuously measure its impact against the market response to improve on it.

How Can The Impact be Measured Best?

The answer naturally is through the use of data tools and digital technologies that allow startups to scale rapidly without investing too much in an expensive product launch at the onset itself. Such tools allow companies to supplement human decision-making with accurate proof of whether a product is working and what exactly can be done to make it better so that it receives a better customer reception each time.

With the relevant, data-driven insights that have been extracted across massive volumes of data that is collected each day, the decision maker in each business can take highly contextual decisions regarding what the customer seeks and what they can deliver. It is through this iterative, data-driven approach that even traditional businesses can be geared to deliver the most delightful experiences to their customers that not only propel the business forward but also add meaningful value to the world around us.

Technology giant, Amazon, has been popular for a variety of reasons, top amongst which is its culture of customer obsession. Known to invest tremendously in its data backbone, Amazon has always attempted to figure out exactly what its customers want and work backwards from there, be it in terms of products or services. This practice of putting the customer first and using every available technology tool to understand what they really want and need is something manufacturing firms need to embrace with greater agility today. It is only through such an espousal of manufacturing capabilities, a flexible approach to product and a willingness to get the best out of available data that manufacturing companies can ensure their customers get the best value proposition possible.