Data is the new fuel of business. Having that clear is easy to understand why most executives should be concerned about the quality of data on which their insights and decisions depend. But many companies fail to understand what constitutes quality data and consider that they already have the data they need to grow their business when this is not the reality.
Our clients are usually surprised when we show them how they are losing sales opportunities, having a wrong understanding of their customers’ aspirations or building a biased picture of their operational efficiency.
According to the "Databerg report" published by Veritas, companies are leveraging less than the 20% of their collected data. They are sticking to the closed analytics solution a third-party is providing them, in the best of the cases, instead of empowering such a vital asset their owned and collected data is.
During the last years, we’ve been working, for example, with Tour Operators and their complex architecture where their sales requests can come from many channels (web, web services, apps), and the response depends on their suppliers (airlines, hotels, car rentals). Well, for them, having a narrow picture of the demand, uniquely based on their actual sales, makes them miss critical pieces of information such as what their customers' intention to purchase was, or which requests became lost sales due to lack of availability. With Datumize Real Demand we are opening them a world of opportunities to make their business grow. To give you one clear example; one of our clients, Globalia, increased by a 5% the annual revenue in just one year thanks to the better understanding of their real demand that leveraging the hidden data with Datumize solution provides them.
If we can select one “leitmotif” we should follow on in this transformation era is: think unlimited. We will be able to accelerate our business indeed and to gain competitive advantage only if we have clear that there is always more way to go.
So, are you up to discover how to leverage your hidden data in decision making?
