You have read it before – data is the new oil, and the new oil resides in a data platform. If your business operates in the 21st century it must have a data platform. But why is this so important? What drives this trend? To start with here are four reasons.
Big data is just a lot of data – Aggregation turns it to insights
By 2025, the volume of all data by an IDC estimate will top175ZB (zettabytes). Enterprises will be managing 50-fold more data than today by then. The Big Data trend started about six, seven years ago. It was initially technology driven, a capability to store vast amount of data had become possible. During the past decade a large number of enterprises have jumped on the data wagon and implemented data collection into business systems and data warehouses. However, the business impact is lost, the problem is getting value out from all the data.
To create business value it is not enough to store the data, but we need to understand what the data tells us. This means aggregating and modifying the data collected from a myriad of sources into meaningful, actionable insights and using those insights for solving business problems and optimizing processes. These insights give business the correlations between the existing data and digital strategies. The ability to create insights is the biggest benefit for creating a data platform capitalizing on aggregation and analytics.
Corporate agility – how data helps getting there.
The speed of business is moving at ever faster clock-speeds. Digitalization of the world has created rapidly moving ecosystems and customers that have changing demands for products and services. Corporations have reacted to the need of speed with agile and lean methodologies that focus on rapid development and experimentation cycles.
In a startup, where agile/lean methods were originally designed for, experimentation is straightforward. You know who your top five prospects are, you know their history and you are likely to have a good understanding about their business.
In an enterprise this not so obvious. The list of the top five customers depend on who you ask, the time of the fiscal year and which product offering you mean. Once the criteria for selecting the top 5 customers is ready, a SWAT team is created that goes through data in business systems to find answers. First the list of answers is reviewed, then more detailed criteria is created, and another selection is done etc.
In most cases a startup uses less time to execute the full experiment than it takes to fetch the data using this iterative process. To become agile, you need to have the business relevant data stored and accessable in one place, enabling business managers to make data-driven decisions efficiently.
There are always more development projects in planning that can be executed as resources are not infinite. To match the available resources to projects prioritization is needed. Prioritization is too often done with incomplete or random human observations or even mere assumptions, as data for doing more precise analysis of the cost and benefits is not available or would be too cumbersome to collect.
Having reliable and consistent data and analytical tools available, enables making analysis for decision making purposes efficiently. A data platform therefore makes for precise and efficient decision making toolh.
The rewind button
All businesses suffer from unexpected incidents or failures in operations. In practice these can be for example suddenly dropping in e-commerce sales, bottlenecks in production or substandard quality.
While the problems and business areas differ, one thing is common with all of them – having data helps grandly in solving the issues. To be more precise you need to have data from the moment the incidents started to happen, so you can analyse what has changed, and identify the broken customer path or faulty parameter in production.
Having a data platform containing historical data empowers you to press a rewind button when needed and go back in time to locate and fix the issues. Without the data platform, the data needs to be collected after the incident occurred, which causes additional loss of sales or downtime.