Reactive.

Too often, organizations react to data.

A request comes in. A team is formed. The team tackles that single request. [Rinse and repeat]

But what is the overall data strategy?

In Part 1 of this blog series, “Why Does Banking IT Need to Prioritize Data Strategy?,” Asad Mahmood, Vice President and Industry Director for Data & AI at HSO, discussed the need for senior technology executives to develop a strategic approach to data collection and analytics.

In this installment, Asad explains the advantages of changing data behaviors with a unified data strategy to maintain data security while simultaneously breaking down data silos.

For many organizations, data is traditionally handled in a reactive manner – when a request comes in, a team is formed to tackle that specific request. They end up fighting individual battles without an overall strategy for winning the war.

The IT department is forced into a position where they are very reactive to requests for data. The business side generates the budget, then requests a business requirement from IT, and IT helps them execute it. But the IT department rarely oversees the organization’s overall data management strategy.

In the finance world, business users don’t always trust data that has already been manipulated by IT, but they trust the raw data and love Excel. They love the flexibility Excel provides, are used to it, and trust themselves to create the formulas and pivots to extract whatever they need from that data.

Unfortunately, once you allow individuals and departments to start data behaviors of working on Excel spreadsheets independently of each other, the data and the analysis gets trapped into those silos of business users doing it themselves.

Spreadsheets are copied and manipulated and sent between departments. Not only does the data quickly become outdated, but you also lose control over who has access to that data. At the same time, it takes those business users weeks to bring in new data, update the pivot tables and anything else, and then make sense of it all.

I have been to organizations where I encountered more than 100 Excel spreadsheets and databases being utilized to run the whole business rather than using the business applications specifically designed for that purpose.

Excel is being used for their financial plan, their forecasts, their execution plan, and their operational plans. Everything is running out of Excel, and that becomes a tremendous risk.

In the financial sector, it’s even more critical to have control of your data because of regulatory oversight and how you handle PII.

A better approach is to include the CTOs and CIOs in the data strategy and centralized enterprise data management. They see the type of requests that are coming in, they can see the type of requests that will be asked for in the future, and they know the data insights their enterprise systems can create.

For that reason, the CTOs and CIOs can bring data accessibility and usability to the forefront and provide a better view of the business to these users. Showing business users the data capabilities available to them will help tame the multiple spreadsheets and data silos and eliminate compliance risks to the organization.

The successful organizations I have seen made an investment in enterprise data management initiatives in parallel to the business requirements, so everyone benefits from the greater visibility.

This is why data strategy is so important. Once the data strategy is in place, business users can see the potential for greater insights, and IT can provide these solutions more quickly. And it will not take months of development time when they ask for a new requirement.

This is where businesses can really start innovating and providing that edge against their competitors.

This makes the business truly agile and allows the executive leadership team to make more and more data-driven decisions in real-time.