A new article in Wired opens with this provocative declaration: “The coming ‘Internet of Things’ spells impending disaster for CIOs everywhere. (Yes, I went there.) And it’s not because of the number of things joining networks — it’s because of the volume, variety and complexity of data generated by and about those things.”

According to writer Mahesh Kumar, IT departments are already struggling with data challenges. They spend enormous amounts of time, energy, and resources on “aggregating, sorting, tagging, manipulating and analyzing the data needed to support intelligent decisions about resource planning, cost reduction, technology investments, service quality, compliance, governance, and new IT initiatives…. Enterprises must innovate in order to remain relevant. But each new technology brings with it a flood of new data, increasing the volume and complexity of data required for IT decision support.”

The sharp spike in data generation in recent years, as well as continued escalation, has created a problem that extends beyond volume. IT teams struggle today with increasing data complexity and lack of context. It’s not just a problem of growing data volumes — IT organizations are also challenged by data complexity and lack of context. “To make good decisions, IT must integrate data from heterogeneous systems and put the data in the right context,” according to Kumar. “In any IT department, countless people spend most of their time wrangling data — not just the data created by information systems, but the data about those systems.”

Kumar cites IDC research that estimates the Internet-connected devices will reach 212 billion by the end of 2020. “What’s scary isn’t the raw number of things, but the corresponding amount and complexity of data that those things produce. There are no standards and consistency right now for how to report on and manage those things. IT decision support systems that are stretched to their limits today — relying on many different tools and manual effort — may come crashing down as the future arrives.

But Kumar still sees the possibility for organizations to take proactive steps in the face of the coming data tsunami. “A forward-looking enterprise should start by getting a better handle on the data about technology and other information assets already in house,” he advises. “Implement scalable, sustainable processes for managing and cleaning all that data, and use the clean data to support varied IT decisions.”