Does this call center routine sound familiar? You place a call to your bank or airline, and the automaton asks you to key in your account number. Then, when you get to a human, they have no idea who you are, and, in most cases, ask for your account information. Again. Obviously, one system is not talking to the other.
Sadly, many business systems don’t share data. While IT already understands this is an issue, the customers who use the systems are usually more aware of the lack of data integration than the employees they speak with or even the company’s customer service managers.
A common complaint I get is that data has to be double entered by employees or customers. This leads to more work, more confusion, and more data quality issues. These issues cause a loss of productivity and credibility. Both can kill a business.
Don’t’ take my word for it. According to Loraine Lawson, Accenture recently took a look at how data integration affects 559 commercial insurance underwriters in the U.S.. 93 percent say technology, including data integration, is the best way to improve quality.
Moreover, two-thirds of respondents said technology has significantly improved underwriting performance. That’s expected. However, 54 percent said technology has increased their workload.
The reasons are pretty clear when you look at the rest of the data. 81 percent blame a lack of data integration across their company as the problem. Moreover, 67 percent cite a lack of process integration.
Why is it still so difficult to get IT to invest in data integration technology that’s systemic to the way they build and deploy business systems? Upfront integration is certainly a much better approach versus retrofitting ad-hoc data integration solutions well after deployment. Or perhaps you’ll end up with no data integration solutions at all, which is the default for most enterprises.
According to Gartner’s Magic Quadrant for Data Integration Tools, this seems to be a well-known best practice that is not well-followed. “Addressing requirements early with the business is crucial, because it is easier to architect than to retrofit characteristics that must be present in an architecture for a multimode, multipurpose data integration environment that flexibly operates beyond conventional bulk/batch movements, to include non-bulk approaches for replication, federation and message-based integration.”
The reasons enterprises avoid or ignore data integration best practices are easy to determine. We find them reflected in most surveys and analysis, as well as within my own experiences. They include:
- Perceptions that data integration is too expensive, and too invasive for most enterprises to leverage.
- Perceptions that data integration causes security issues, since the data is exposed.
- Current enterprise IT lacks both an understanding, and the skills to build and deploy a data integration solution.
- Enterprise architectures are too fragile to stand up to the required layering of a data integration solution into the enterprise.
The core issue with all of this is that the lack of a data integration strategy and enabling technology for core business systems means the enterprise doesn’t have the data it needs to optimize the value of those business systems. What drives me nuts is that IT is fully aware of this issue, and either chooses to ignore it, or they are not budgeted to solve the problem. They view things as working, and thus don’t want to improve or fix them due to the added cost and risk.
However, the internal and external customers who leverage the systems also know that data integration is lacking. What’s reflected in the Accenture survey above is is true about pretty much most of the Global 2000 enterprises out there, as well as most government agencies. We’ve met many of the automation requirements of the business, but the addition of technology does not always directly translate into value.
Missing is the easy sharing of data which would allow the data collection systems to function as a single, unified set of processes that truly automate the business. Moreover, they would operate to the delight of both customers and employees. Information placed in a single location is auto-magically replicated to other systems that should share that information. Customers are only entered in one time, transactions all match, accounting records all balance, it’s a wonderful world.
My guess is that, for most in enterprise IT, data integration is complex and scary, and difficult to consider in the context of the many projects that are currently in motion, including cloud migrations, security upgrades, new regulatory changes…you name it. I get it; there are distractions. There are also untapped opportunities.
Success in business automation means a complete transformation of all business processes to an automated and easy-to-orchestrate state. Without a sound data integration strategy, and technology, that goal is just not possible.