Data capture
Once an efficient means of storage is available, the capture can be relatively simple. Current dependence on IT has resulted in multiple opportunities to capture data. A simple example illustrates this...
In most business environments, data and interactions are increasingly becoming electronic. Even when people have face to face meetings, agendas, minutes and summaries will be distributed electronically. By monitoring interactions and gathering data, organisations are able to maximise their productivity. This was achieved by Sandy Pentland, a professor of computer science, who monitored interactions between workers at a call centre. Pentland used the data gathered to restructure coffee breaks and enhanced the flow of ideas, varying who interacts with who and changing conversations.
Equally, data can be collected from existing programs and software. For example in healthcare, data is being developed to be used to provide treatment tailored to genes. When samples are taken, typically results are returned in a digital format. The most innovative healthcare companies will feed this information into machine learning systems which will be able to suggest or eventually prescribe treatment.
The opportunities for collecting data are almost endless, especially because of our growing dependence on IT. In order to gain real insight, however, this data needs to be processed into a format which can be easily understood and used to drive results. To gain more insight across the organisation, it also needs to be accessible to the data analyst within the company, so there isn't a need to rely solely on IT to handle these projects and produce results.
How is it processed?
There are a number of tools available to process data, dependent on business requirements. Traditional tools for analysis of data have their issues, and are left unable to process the size of the modern day data environment. For line-of-business analysts, manually inputting or processing data is too time consuming and will result in data being out of date by the time it is acted upon. Then organisations will fall behind their competitors in their ability to make data-driven decisions.
For many businesses, the major benefit of data is that it can be blended. As data is often captured from so many sources, and often saved in different formats, it is important for businesses to be able to effectively blend the right data, organise and place insight at their fingertips.
Many data sets will come from multiple sources. For example, customer information for a retailer might be made up of data taken from in-store and online purchases, social media likes/dislikes, call centre information and many more. All of this data needs to be united in one place for analysis to provide a deep understanding of shopping behaviour.
Data blending is therefore a critical tool, enabling multiple data sources to be joined in one place. For example Database USA, a provider of business mailing lists, blends data from hundreds of data sources in order to ensure their lists are up to date and accurate.
What do businesses get from data?
There are an endless number of specific industry uses for data, as well as some key means by which almost any business can benefit, from increasing productivity, to intelligent decision making and personalised customer relationships.
The most traditional use of data is marketing. Data-driven marketing has been around for a little while, but it is growing in its use across verticals. Gartner predicted that by 2017 the average CMO will be spending more than CIOs on IT services. This has sparked much more of a link-up between marketing and IT departments, who are also helping to combine marketing and CRM databases.
Data allows marketers to make their contact with customers and potential customers more personal. Knowing that your core customers are made up of specific demographics and having an understanding of individual customer preferences makes personalised marketing achievable.
