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Most people can identify with a common issue within their own organizations: the attempt to solve a problem before really, truly understanding the problem. We are wired to think tactically, to seek the shortest route or path to our destination, to just "get it done." The problem with that "everything is a nail, and I have a hammer" perspective is that we often cause collateral damage -- whether to our team morale, our corporate culture, or even -- from an IT standpoint -- to secondary or tertiary systems that may not fall into our peripheral views as we attempt to solve only for what is directly in front of us.

Every decision we make in business includes both risks and opportunities. As is so often the case with collaboration technology, we seek after the quick win, the flashy new feature set, or the promises of ease and integration -- without fully understanding the risks, or, to be fair, the opportunities beyond what is front of us.

Begin and End with the Customer

When defining the problem of poor quality, lost revenue, or high costs, it is not uncommon for employees to blame the customers. They might say things like, “our customers are not sophisticated (i.e. “intelligent”) enough to use our product correctly” or “it’s another case of user error.” If the customer is internal, they might assert something like, “the department we hand off to doesn’t understand the way we work” or “it’s a training issue, not a functionality issue.” Such statements are counterproductive, and only serve to entrench companies in their inadequate ways, making real improvement and customer satisfaction that much more difficult to attain.

Sound decision-making begins and ends with the customer. That includes internal customers as well as the more obvious external customers. That’s because the customer ultimately defines quality -- and they are more keenly aware of what their business needs are, and whether the solutions being provided are meeting, or will meet those business needs. Granted, the voice of the customer can be emotional, contradictory and subjective. You must refine that voice of the customer into objective, measurable characteristics that are critical to success, and work closely with your customers to prioritize their asks -- and as you begin to define solutions, weigh out those risks and other potential opportunities beyond what they are asking for today.

Examine the Process

The quality of a product or service doesn’t just materialize out of nowhere. The process and the inputs that go into that process determine the results, and will help you to uncover the relationships between risks and benefits, helping you to build more scalable solutions. Compare this thinking to software modeling. Before you build, you need to understand your actors, your use cases, and the interactions and relationships between all objects within the system, allowing your development team to make improvement breakthroughs.

Our natural tendency is to focus on the results or outputs. A typical result of such thinking is to reward employees for achieving a desired goal without regard to how they reach that goal. Such improvements often turn out to be unsustainable and impractical in the long run. Over time, such programs seem to come and go and often end up being an exercise in futility. A better practice is to reward employees for achieving improvements to overall process, and those things that are repeatable and sustainable.

Many organizations have embraced the science of process, utilizing methodologies such as Six Sigma to help them, in a very measured way, to define what the important process outputs should be, and then understand the nature of the relationships between process inputs and outputs. The focus of Six Sigma improvement efforts rests on the process itself and on the process inputs, not the outputs. By manipulating, controlling and compensating for the process inputs, you ensure acceptable process results that meet the critical to quality requirements.

Capture the Data

Without data, your analysis and conclusions are just opinions. Many past quality initiatives based their analysis on subjective judgments and gut feelings. Not surprisingly, the resulting improvement efforts often fell short. While you cannot discount personal experience, the key to ongoing process improvement is to follow best practices, gathering and classifying information as you prioritize your tasks and develop a strategy, backing up your decisions with data.

You poll one hundred customers and find that seventy of them are “very satisfied”. You then go on to spend money, time, and other resources in order to improve that satisfaction level. Six months later, you poll another one hundred people and find that eighty are “very satisfied”. Did you really make an improvement, or is the difference within the margin of error? Expand on the kinds of data that you capture and synthesize into your decision-making processes. Use qualitative data gathering techniques, such as interviews, surveys, online polling, workshops, one-on-one interviews, and other team-based inputs, but also look into quantitative methods, such as descriptive statistics, hypothesis testing, regression, design of experiments (DOE) and statistical process control (SPC).

Move Forward

Every collaboration initiative begins as a business analysis activity. Building out a company culture that includes these kinds of deep qualitative and quantitative optimization changes requires a significant investment of time and resources. You’ll need to excuse the participants from their normal responsibilities so that they can concentrate on developing, extending, and applying the methodology. Although results begin to show in a few months, it may take several years before you see the return on investment you seek.

There is always room for improvement. You don't need to run out today and sign up everyone within IT for courseware on Six Sigma. But data shows that investments in process-centric decision-making can yield tangible financial results. In the end, these ideas affect the bottom line, and every business in the world understands that. Finding the right methodology, and finding a fit for it within your organization is a big decision in itself --one requiring both qualitative and quantitative analysis, as well as a bit of a gut-decision.