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Harnessing information so that your organization can become data-driven is no simple task. You need to be able to rapidly assimilate, integrate and analyze your data 鈥� existing internal data and the growing stream of big data from new internal and external sources 鈥� and turn it into insights that you can act upon at the point of action.

Jeff Hunter, vice president of the NA Insights & Data practice at Capgemini, says a of 1,000 C-level executives and senior decision makers reveals seven principles CIOs should follow to help their organizations successfully transform into data-driven enterprises.

Data-driven transformation must begin with your business objectives. Once you understand your objectives, you can design a roadmap for leveraging new data sources to help you achieve those objectives. Where you start in terms of both data maturity and technology will dictate the course of your journey.

鈥淏y proper alignment of business and technology, firms can start to systematically go through business process and business models and start to ascertain whether a process contains qualitative elements that could be replaced by quantitative elements,鈥� Hunter says.

The Internet of Things is here and it has brought (and will continue to bring) unprecedented volumes of data with it.

鈥淐ompanies over the last 20 years have been talking about enterprise data strategies because they have data marts and data silos sitting all around the company,鈥� Hunter says.

While organizations have worked hard to break down these silos, the coming flood of data will create them all over again unless your environment is prepared to cope with it.

鈥淭he amount of data that鈥檚 being generated on a daily basis has far outstripped what we were used to in the last two decades,鈥� Hunter says. 鈥淵ou have to be prepared to manage the new velocity of data.鈥�

Hunter says that many new technologies equip organizations to capture and manage data. Your data landscape needs to incorporate a mix of these technologies to suit the specific data sets necessary for your business needs.

Technology is not enough to transform your organization into a data-driven powerhouse. Creating a culture that understands data and how to use it is just as important, if not more so.

鈥淔or us, that really means understanding data is no longer a by-product,鈥� Hunter says. 鈥淚t鈥檚 an asset. You need to go into the mindset that it is an asset. You need to understand that your data could potentially help you reengineer an existing business process or help you find a new revenue stream.鈥�

To get there, you need to embed data science throughout the enterprise and systematically make all decisions better informed.

You can expect demand for information and data-driven insights by business users to increase continually in virtually all organizations. That means business users must feel that they can rapidly access the information they need, any time, any place.

That鈥檚 no mean feat. The trick is to start small with a single business goal that can benefit from analytics. Then iterate, allowing your team to gain experience and become a center of excellence that can 鈥渋ndustrialize鈥� the process of bringing data-driven insights to business problems.

鈥淭his process should be able to be replicated and continuously consumed,鈥� Hunter says. 鈥淵ou want to make an investment in technology, people and analytics that allow you to industrialize sideways business unit by business unit.

Hunter notes that a large portion of Capgemini鈥檚 own investments in big data are reusable across clients.

A key element to making your data initiatives succeed is to apply data science to your data science. No, that鈥檚 not another crack at the Xzibit meme. With increasing amounts of revenue driven by data activities and insights, you need to be able to determine whether your data initiatives are moving the needle so you can measure success and failure.

鈥淗ow do we measure success? We want to make sure we are focusing on insights as a crucial KPI,鈥� Hunter says.

Basing decisions on insights gleaned from bad or unreliable data can be much worse than acting on intuition. Worse you can expose your business to all manner of bad things if you don鈥檛 handle data securely and with utmost respect for privacy issues.

鈥淭he security and privacy of your data assets is essential,鈥� Hunter says. 鈥淲e will always stand very strong on proper governance of data. Contractual, compliance and regulatory issues have to be adhered to regardless of how fast the data is generated.鈥�

Ultimately, data-driven insights are valuable only when the insights are provided to people in your organization who can act upon those insights in a timely fashion. The insight needs to make a difference at the 鈥減oint of action.鈥�

For instance, if you鈥檙e focused on shopping cart optimization, you need to provide recommendations to the customer before the transaction is completed.

鈥淭hose same types of things are being done elsewhere as well,鈥� Hunter says. 鈥淐an you provide insight to the point of action for a machine operator so that he or she is getting information that the drill bit is going to break within the next seven cycles?鈥�