Data analytics, sometimes size matters

In the new world of business powered by the Internet, one thing remains certain; any product or service interaction that could be transformed into a digital form will be done so, if not already being on its way to be digitally shaped. With this in mind, anyone in business needs to ask what will be the place of their offering in the new interconnected world. Are they already moving towards it, or resisting the change while they can? What are the opportunities that arise, beyond selling online and/or automating a supply chain internationally?

For the ones initiating into the premises that are key in this new way of doing commerce, paying attention to their current flow of information unveils the most likely aspects that will be transformed to a digital form. From conversation with suppliers, new product designs, sales networking, and ultimately the word of mouth dialogue between customers, information is being captured, enriched and transformed in a structured way, that ease interactions, make them more accurate, and destroy barriers of geography and time for a message to reach its destination whatever that may be. And yes, it was easy before for the small business owner or even for the traditional mid-size company to pretty much have all the important aspect of the business on their heads, and while in environments where everybody else was pretty much doing the same, only the smarter individual had a competitive advantage as aggregator to many sources of data. However, with the help of a few tools, a not so smart new business owner can completely overpower the old establishment, by just paying attention to aspects that are difficult to uncover even by the best trained eye, and that sit in the realm of having access to enormous amount of data and some computational horsepower.

For data to exists and get to become a large repository, first it needs to be captured from an information flow. If someone is trying to understand how a competitor might win their business in these days, the first thing they need to look for is the most essential knowledge they possess. That if augmented and enriched can lead to a better offering from a new challenger. The knowledge-information-data transformation allows, for a once not too digital business to become a source of information, rather than a dead-end where the dialogue between suppliers, channels and customers, stops. Allowing for this dialogue to flow endlessly in any company interaction will produce enormous amounts of data, and opportunities to learn from it the new ways of doing business; while narrowing the path of somebody else trying to learn much more and way faster to eventually become a threat. At a certain point, all business will allow for the dialogue to keep flowing, but what about the dialogue that you need to have with your competitors? What about the information that goes beyond just a product or service, and need to form an integral profile of a customer and its needs?

Certainly, every company will like to be the sole supplier of all their customers, but this is neither desirable to the customer nor possible in the open model of economy. Then, the flow of a company information (even though huge) is still just one aspect of a myriad of relationships a customer might have, and that all the players in an industry might be missing from their efforts to produce better product and services. In some areas cooperation around information is critical to the survival of the whole ecosystem, like in credit markets where a Bank needs to know whether a prospective borrower has a good enough record before lending to an unknown customer, or the pharmaceutical that tries to understand the toxicity or side effects of a new drug when combined with established ones. From these natural opportunities of cooperation, the digitization of information will open many more, particularly the one where a whole company is just dedicated to aggregate and analyze information about business in a line of trade, and fill the information gap for companies interested in knowing more about their customers, beyond just the interactions they directly have with their products.

Usually in a platform mode, a provider creates a service that is used by both customers and businesses serving those customers, retaining the intelligence of all transactions and having a real-time pulse in the drivers of demand and customer satisfaction (e.g. Ebay, Amazon). Another way is for a provider to organize the industry player’s information, and offer a business model where it makes sense for them to contribute its data and have access to reporting and intelligence about customers significantly expanding their view about them.

Either way of the equation, in the new world of business; companies will be separated between data generators, and data aggregators. For anyone in the latter group there is a significant advantage to have access to a bigger torrent of data if utilized correctly. They can be the first to uncover trends, and needs, as well as, benchmarking players in an industry, which could be beneficial to commerce in general. However if they don’t have a service themselves, and they view their customers as the businesses providing data, is very little what they can do with that enriched knowledge for their own benefit, and ultimately the betterment of the end-consumer; the customer they really should be aiming at.

The other issue is just having too much information. Big data is sold as the next critical business trend, but there is a pitfall lurking in the background. With more data, there are more possibilities of constructing any reality a business, or its consultants, wants to portray, since there will be more points to generate correlation that still would not mean any causation. So, for the managers of the big data repositories the hunt for the right insight becomes exponentially more difficult instead of less, while computational infrastructure and expertise to maintain ‘the hunt’ could be a big-ticket item.

Data is a key resource in the new business world, but as with anything good, there are limits of how much a business should be involved in a data analytics and extraction operation. Choosing its role (generator or aggregator), and the appropriate intensity of their information gathering efforts, would define the winners and losers in the battle to distinguish a true signal from just noise.

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