While the press and many companies continue to marvel at the sheer volume of data being generated and captured in the internet era, forward-leaning corporations have already recognized that big data's transformative potential to generate value in both the digital and physical realms will go largely unrealized unless it's complemented by speed. Fast data can unlock the value-creating power of big (and small) data.

Technology has empowered customers in such a way that they are now in charge of the business relationship - a fact that's left many businesses playing catch-up. Companies and supply chains that fail to realize this risk losing customers if they don't respond to their needs.

There will be a surge in next-generation advanced data collection devices, which will intelligently edit and communicate data and play a critical role in providing improved business analytics, or Big Data, according to a Datalogic survey.

Over the past 30 years, most companies have added new C-level roles in response to changing business environments. The chief financial officer role, which didn't exist at a majority of companies in the mid-1980s, rose to prominence as pressures for value management and more transparent investor relations gained traction. Adding a chief marketing officer became crucial as new channels and media raised the complexity of brand building and customer engagement. Chief strategy officers joined top teams to help companies address increasingly complex and fast-changing global markets. Today, the power of data and analytics is profoundly altering the business landscape, and once again companies may need more top-management muscle.

The RFID market will increase from $6.98bn in 2012 to $7.88bn, and will reach $23.4bn in 2020, according to a RFID sector survey by IDTechEx Research.

ABI Research forecasts that the M2M analytics industry will grow a robust 53.1% over the next 5 years from $1.9bn in 2013 to $14.3bn in 2018. The forecast includes revenue segmentation for the five components that together enable analytics to be used in M2M services: data integration, data storage, core analytics, data presentation, and associated professional services.