In many organizations, the IT department is becoming more and more focused on serving one large client — the company’s marketing wing. Chief marketing officers have woken up to the power of big data and how the information that their company gets from their customers and prospects can influence how they sell products, growing revenues. Unfortunately, many marketers approach big data from a very different perspective than traditional IT leaders, and this causes friction.
To marketers, IT departments fail to understand how to use big data in three key ways:
- IT has a data-first approach. Most IT departments start by building up big databases of data. Only once the data infrastructure is built do many IT teams start to use it to try to glean additional business intelligence. Marketers need something now and are used to making best-guess decisions off of incomplete data — they don’t need a perfect base of data.
- IT pulls the wrong data. Most IT systems are set up to vacuum readily available data into a database. The problem with this is that the right data might not be in an easy to grab format. For example, data in cloud-based applications with application programming interfaces and metadata from emails are very easy to grab, since there are direct pipelines to the database. When important data is located in individual documents or in scans of old paper documents, it’s much harder to acquire and put into a database-friendly format. IT usually delays capturing this information, but it might be the information that marketers actually need.
- IT focuses on infrastructure rather than access. Most IT departments want to set up a system that will meet all of their needs, then import data, then start to use it. However, the time that system configuration requires could leave the organization behind its competitors.
IT departments that operate in this way are getting bypassed by marketers who care about one thing — answers to their business questions. IT departments can help marketers by getting involved in business processes to make it easier for them to tag, store, access and query the data they collect.