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How Come We Don’t Talk Anymore? Getting Your Systems Connected

Aug 23, 2017

So what if your systems could magically talk to each other? How much better reporting could you get? How much more time would you have to do actual analysis of the data and be a business advisor? How much more time would you have to think about innovation and increasing value in your organization? Let’s discuss how you can make steps toward making this dream become a reality.

Organizations often find themselves with disparate systems that don’t communicate with each other. Shorter-term priorities and business objectives often take priority over finding synergy between the systems that support business processes and the value delivered to customers and stakeholders. Over time, this results in growing process inefficiencies and prevents holistic analysis of data so faster, more informed decisions can be made about the organization. The challenges that develop by having siloed data—misused employee productivity, lack of real-time visibility, and (albeit often downstream) greater customer churn—are real. Conversely, if you make system integration a strategic priority, your organization will reap long-term benefits: process efficiencies, improved visibility, cost and time savings in IT, accelerated growth, and employee-driven innovation. Of all of these benefits, I believe the latter is of the utmost importance.

Technology is actively reshaping business as we speak. Employees who are freed from the mundane can spend more time innovating. Those organizations which don’t free their employees to innovate will quickly fall behind the competition.

Better Data Helps You Make Better Decisions

The truth is that if you had better data at your fingertips, you could make better decisions. The problem is that you often get caught spending much of your time looking at data in independent systems and having to make data correlations in your head (I call this assumptive analytics), building reports across multiple data sources, or even manually compiling import/export data files between systems. Are these tasks really the best use of your time? I think we can agree that answer is no. You know that if you could spend more time analyzing data and less time compiling data, you’d be a better advisor to the business, providing more value and probably being happier with the work you are doing. So how do you actually make this happen?

Get Organized Early and Often

As with any important project, getting your integration strategy organized early and staying organized throughout the execution are very important. In addition, you must continue to focus on the quality of your data to ensure that when your systems are integrated, it’s with quality data—remember, garbage in, garbage out. Part of being organized is understanding your budget, not just your financial budget, but your time budget. Set some boundaries around these items early and continue to drive your strategy with these elements in mind.

In addition, you need to pull together a catalog of all of your systems, types of data objects (structured or unstructured), and corresponding integration capabilities (extensible API, Web services, platforms, or merely flat file uploads). Spending time upfront pulling together this information, often referred to as an enterprise system landscape, will pay dividends in the end.

Set Priorities Based on Value to the Organization

Then, with functional representation from within the business units, set a ranking or prioritization for each system and/or integration point that consumes the most manual effort. Build another ranking on the importance of that system to the organization. Finally, place a ranking on the technical capabilities available, based on your previous research. These three rankings will help you build a solid return on investment and empower you to focus on those integration points which will deliver the most overall value to the organization. The value of the integrations must be a continued focus throughout your overall system integration execution. That is, it’s not enough to build slick integrations and automation; they must focus on those areas which deliver value: freeing FTEs to focus on higher-value tasks, reducing errors, or enabling better analytics for business decisions.

Custom Integrations vs. Platforms

As you pull together your enterprise system landscape and complete your ranking exercises, the priority areas should begin to surface. You will start to see the scope of each integration (including data structure), the overall number of interfaces, and available technology surrounding each system. As this all comes together, your next important decision will be the technology used to make the systems talk to each other. Will you use a platform (e.g., another system) to manage all of the integration points, or will you develop each one in a custom fashion? Do a little research on iPaaS (Integration Platform as a Service), and you will see it’s currently all the rage. It’s true that some of the available platforms are very powerful, but you must evaluate the cost and overall value to the organization before jumping in. Often, more traditional custom interfaces are more appropriate and affordable for a smaller scope and number of interfaces required.

Don’t Bite off More Than You Can Chew

While you evaluate and plan your strategy, priorities, and technical approach, it’s imperative that a focus on smaller successes driving toward the overall strategy be more important than a focus on larger leaps. Success breeds success in system integration efforts, so plan broadly but execute incrementally. Using tactical, well-tested enhancements that progress the strategy is much more valuable than rushing against arbitrary deadlines. Along the way, the key stakeholders must challenge the outcomes against the initial business values defined at the onset. This consistent review and accountability will ensure that your efforts produce tangible business benefits, that the organizational investment (time and money) is producing fruitful results which provide the rich data analytics we all desire from connected systems, and that data quality is still of the utmost importance.


Matt Rowley
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