Last week, at the Nasscom India Leadership Forum 2017, Reliance Industries Ltd Chairman and Managing Director, Mukesh Ambani said: “Data is the new oil in the industry.” But image the possibilities if that data was shared. Speaking on the sidelines of Microsoft’s Future Decoded event in Mumbai this week,
Norm Judah, Chief Technology Officer,
Microsoft Services, gave different scenarios of data sharing and talked about the immense possibilities for business.
“This whole notion of digital transformation isn’t new. It started with the way companies deal with information – how they access it, store it, share it and (use it) to change the behavior of people. More recently, we started getting into it in a more structured way; there are four key pillars or dimensions: activities around employees, operations, customers and products. An organization could look at one or more of those dimensions,” suggested Judah.
He cited different ways in which organizations could leverage information based on one of these four dimensions. For instance, an organization could be thinking about how it gives its employees better information about its business and its products. This would be done with the objective of making its employees more productive.
“Suddenly you start to look at deeper and richer information,” said Judah.
Another scenario could be Operations, where an organization looks at operational efficiency and optimization of operations in different ways.
“For instance, an organization could use machine learning to look for patterns in the supply chain,” he said.
“The notion of customer information has also changed dramatically. In the generation of CRM systems it was everything that say, a bank or hospital, knew about its customers. But the boundaries that they drew were limited to the boundaries of the bank or hospital. But now, those boundaries have expanded,” said Judah.
Explaining this he said that the bank or hospital knows transactional details of their customer. But in many cases the organization looks for more information, beyond the transactional data. With this additional information, it can co-create products and services with its customers.
“There are key elements of data, information and information sharing. There are engines that look at all that information and operate on it in different ways. It could be a machine learning engine or a neural net engine, or some deep analytics,” said Judah.
The second aspect to this is the Data Economy – the economy of sharing and accessing data. For instance, banks can also get information about customer travels, through their credit card records. It can learn about the things a customer wants to do and where he/she is going next.
“That data economy actually becomes the new ecosystem. Every ecosystem is like a marketplace with buyers, sellers and liquidity. We are getting to the place of data sharing and creating environments where there is value in information. My information is useful to me, but it might also be useful to you too, so how do we exchange it? What’s the currency of the exchange? It could be three parties who share that information,” said Judah.
The information sharing could also be applied to consumers. Take retail for example. Consumers looking to buy a new TV set will search for a suitable brand and model on different websites before visiting a store. They would search based on various parameters such as screen size, resolution, price, features etc. And then, they would take this information and go to a store to see the models they have shortlisted. But the online and offline experience (in the store) are disconnected.
“Your context of information gathering is not connected to the context of action (buying a TV). But there is some way of making this connection. A bot could track your surfing and remember what you looked for, what you like and disliked. It could give a QR code (encapsulating your surfing experience) and you could take that and show it in the store – and they would immediately understand your preferences. Two things would happen: a quicker sale and an opportunity for the salesman to cross-sell and upsell.”
In this example the context of the experience is moved from an online channel to an offline one. While this is a consumer example, it could also be applied at the enterprise level. And Judah gave us an example.
Microsoft and its partners gave a live demonstration of this business model during the Future Decoded event in Mumbai, this week.
“We did some work with a company that manufactures large trucks used in road and building construction. When they give their sales reps a quota, it is based on what they did last year (historical quota). But the sales quota can also be forward looking based on the opportunity. The quota can be based on last year’s sales data (of construction trucks sold), combined with industry data on RFPs on construction projects,” said Judah.
Normally, these two sets of data are unrelated and in different contexts. But they can be correlated to create new possibilities and new opportunities to sell. This is only possible in the data sharing economy.
“If you go deeper, you can get some more insights about the usage of the truck. A truck manufacturer leasing trucks for the transportation of sugarcane can get information about next year’s sugar cane production, and will sell based on the ability to move a certain amount of sugarcane. So it is transportation as a service. The business model changes.”
The truck manufacturer could also get information that can be used for predictive maintenance of the truck – to minimize failure.
In this example, various dimensions of data can be used to benefit different parties: the truck manufacturer, the company leasing trucks and also the sugarcane manufacturer that needs transportation.
“Employees, customers, operations and service all have the notion of data, data sharing and data movement -- and the engines that run across the data,” said Judah.
