*** The 3 Things Series aims to simplify – sometimes even oversimplify – technology concepts so that you learn 3 things about a topic ***. Opinions are my own.
Organizations embark in Big Data projects typically with 3 goals in mind: cost reductions, improved decision making and the ability to create new products and services.
1- Cost Reduction
As the quantities and complexity of data in organizations increase, so does the cost of storing and processing this data. Decisions about how much data to keep available for analysis, and how much “historic” data to move to tape or other less expensive resources, are then made. The problem with this strategy is that by limiting the data that can be analyzed, the insight that can be derived from this data is also limited.
In recent years, technology developments especially in Open Source, have made cost reduction a reality through the use of inexpensive technology such as Hadoop clusters (Hadoop is a unified storage and processing environment that allows for data and data processing to be distributed across multiple computers). Hadoop clusters give organizations the ability to keep more data available for analysis at a lower cost, and to easily add complex data types (images, sound, etc) to the pool of data to be analyzed
2- Improved Decision Making
Data analysis can be significantly improved by adding new data sources and new data types to traditional data. For example a data-driven retailer may see significant benefits in their inventory planning processes, if a new data source like weather data is added to the model to better predict sales and inventory requirements. An enriched model may be able to predict shortages of winter clothing by incorporating temperature into the existing models. Additional benefits can also be achieved, if more complex data is analyzed. For example, this same retailer may better target their ads in social media, if they evaluate not only their clients purchasing history, but also the actions they take in social media to interact with their brands and those of their competitors.
3- Development of New Products and Services
The most strategic and innovative business benefits will probably be achieved by the ability to use new data or new sources of data to create new products and services. Let’s think for a minute about the data our cars generate (yes, we don’t necessarily see it, but more and more cars are equipped with sensors that collect a lot of data about our driving history). Using this data, insurance companies can offer policies that are dynamically priced based on an individual’s driving history (which is good news to you only if you are a safe driver of course). Integrating weather data can also bring tremendous savings to an insurance company. Some insurance companies have been able to achieve significant savings per claim by letting their clients know that a storm is coming and recommending they don’t leave their cars exposed to the elements. (Again, assuming that as a client you listen to your insurance company recommendations).
In summary, when thinking of the business value of Big Data, think of three areas of value:
- Cost reductions
- Improved decision making
- Ability to create new products and services