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There’s an avalanche of data management needs headed for IT that originates from the finance department. Building steadily over the past two to three years, finance has become the epicenter for cross-company data analytics and oversight of fiscal and non-fiscal information.

Data analytics is a natural extension of finance. What’s more, increasingly CFOs are functioning as the de facto chief data officer. A recent CFO IT study bolsters the argument, given 70 percent of CFOs and finance executives responding say they plan to devote substantial time to data and analytics in the next two years.

With all the hype around becoming a ‘data-driven company’ starting to feel a bit aspirational, one key rally point does hold true for all companies: the opportunity to gain competitive advantage from data is lost without a way to manage all the information in a meaningful way.

According to Ventana Research, 46 percent of a business analyst’s time is spent preparing data, while 52 percent is focused on checking it for quality and consistency. That’s a lot of manpower lost.

By now, IT should be hearing rumblings of the impending avalanche, and avoiding being crushed by it remains a serious challenge. Aside from the obvious questions around tooling, process, ownership, etc., there remain more critical issues to work through. Every company is different, yet IT is consistently stretched thin, creating an urge to just ‘buy something and get it over with’.

That’s a mistake – one I’ve seen first-hand play out over and over for decades. Forethought now will save months of labor, loads of money - and in some cases jobs. Three steps now will keep IT from having to dance around tough questions after a failed deployment.

Step 1: Take Stock of Your Data

With new data sources emerging daily and legacy data sources part of our business culture, figuring out what data your organization already has, what new data is on the horizon and what data might be hiding outside your organization is an important first step.

Consider a wide range of sources including enterprise applications, external cloud applications, legacy applications, machine sensor feeds, big data applications and even spreadsheets stored on desktops. Review the data as an IT team and with business stakeholders to determine which elements are needed to inform the business and which are noise.

When it comes to data, quality is more important than quantity, and gathering the right data is essential for competitive advantage. Once the relevant data has been identified, the team must then determine how it can be accessed in a timely and automated way.

Step 2: Ensure the Data is Trustworthy

While all steps are important, this one is critical. Without this step, business users waste valuable time debating whose numbers are accurate rather than making important business decisions based on good data.

As the variety of relevant data sources expands, it creates a complex data environment with non-standard, incomplete, outdated and duplicated data. Making this data “trustworthy” becomes more daunting the more data an organization creates.

Harmonizing the data will make a real difference. Data harmonization done right creates a “golden” record that all applications call to when they need that data, avoiding replication errors. Storing those golden records in one, integrated central repository enables vastly streamlined updating processes – a ‘one change affects all’ strategy.

As part of that harmonization process, data quality and governance programs must be implemented to preserve the long-term integrity of the data in the repository. This golden copy becomes the foundation for all analytics and reporting across the business and will keep the focus on the business rather than the process.

Step 3: Streamline Reporting

Once the data is available and trustworthy, it needs to be useful and usable. This is where reporting comes on the scene. Empowering teams with the right reporting tools allows them to make better decisions faster, while freeing up the IT team to concentrate on more strategic initiatives.

Again, this is a situation in which quality trumps quantity and having the right reports will be more valuable to the business than having many reports.

Start by working with business stakeholders to define the content that would best inform the business and provide consistent views of performance. Choose agile reporting tools and infrastructure that will allow your business to adapt reports as needed over time. Ensure that reporting solutions will allow business users to self-serve so IT doesn’t need to get involved with every report modification.

Also consider how to keep the data fresh, as near-real-time data is essential to good decision making and customer satisfaction. Strive to give a diverse set of user groups access to the data with ease and governance. Transparency, consistency and accessibility should be the hallmarks of any reporting solution.

If you’re in IT and your employer is aspiring to be a ‘data-driven’ company, it’s only a matter of time before finance sends an avalanche of data management requests your way. Get ahead of it now and start collaborating with finance on data access, management, reporting and analytics.

If it’s not happening already, you can bet the CFO will start driving hard toward systems that enable the department to glean trusted insights for driving corporate performance management. Don’t risk not supporting such an important business need.

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