As with so many new technologies, the era of big data has been more hype than reality, with many organizations struggling to get high quality data out of internal silos in order to derive timely and actionable insights from it. According to a recent survey from PwC, however, now is the time that will all change. Their latest pulse survey reveals that 86% of companies believe that 2019 will be the year they finally extract value from data.

This priority was emphasized by the 94% of executives who thought customer data was critical, although the size of the challenge was underlined by the fact that just 15% thought they had sufficient data in this area. When asked to explain some of the barriers they faced, the responses were those we've heard many times before, including the quality and standardization of data, the security of it, and the regulatory uncertainties surrounding the collection, storage, and use of data.

The survey revealed six core obstacles towards achieving this:

1. Unreliable data that was accumulated over a long timeframe and lacks the accuracy and robustness required to make meaningful decisions.
2. Regulatory issues with compliance challenges changing at a rapid pace, especially in areas such as privacy.
3. Security issues continue, with concern all along the value chain, from capture all the way to archiving and purging.
4. Silos continue to hobble data-driven transformation, especially when different standards and rules exist in each silo.
5. Talent remains an ongoing concern, but many executives believe AI and automation will enable them to do more with less.
6. Technology is the final obstacle, and executives reported feeling less than confident in their technical capabilities, especially in an age of AI and high-powered computing.

Trusted Data Optimization

So what's the answer? PwC believes it's something they refer to as 'trusted data optimization,' which aims to build trust in data within the organization so that rapid, data-driven decisions can be made. They propose three steps towards making better use of data within the business:

1. Audit and assess your data so you understand what you have, who can access it, how accurate it is, and what obligations it carries. From here you can begin to standardize formats, labels, and processes across the business.
2. Build a strategy framework to assess the risks of each data use case you can think of. This should include any compliance issues and the impact on market expectations, and will allow you to perform cost/benefit analysis for each use case.
3. Operationalize data by establishing robust security and privacy protections. At the same time, update technology so it can be relied upon.

"The result will be a head start toward maximizing data's power and trustworthiness, while enabling risk officers and business leads to accurately and quickly balance each use case's benefits and risks," PwC says. "They can then advance with confidence in the race to turn data into value."

All of which makes the process sound so easy that 2019 is inevitably going to be the year where all of the problems raised are addressed and data-driven transformation occurs. Or perhaps not. Time will tell, I suppose.