Optimizing Processes for Innovation and Agility

Innovation and agility are lofty goals that sound so good in annual reports but so often fail to materialize in the real world. That is because they must be pursued in the dirty and hazardous work of process optimization. And that’s a scary thought for many.

Before the dot.com period of “technology for technology’s sake,” there was an equally manic time when corporations tackled “process for process’s sake.” This phase, known as the business process reengineering, or BPR, era, called for the radical reinvention of all processes across the enterprise.

BPR promised quantum gains in operational efficiency and competitive advantage. However, it often wreaked havoc on organizations, leaving them to wonder what value they had received in return for the millions they spent. It’s no wonder that when you even utter the phrase “process model” now, some executives and managers go weak in the knees, envisioning a return to the bad old days. So, I want to be clear that when I say process optimization I do not mean revisiting BPR.

What I do mean is the analysis and design of processes to show the link between business objectives and the supporting technology for a given initiative. It does not entail the wholesale revamping of processes. Instead, process optimization focuses on improving the specific processes that support each proposed business scenario model. It is here that the organization can be viewed through the lenses of innovation and agility.

More Bang

Processes can be examined in light of the three types of innovation: business model, business process, and product. Studies show that more bang for the buck can be had in model innovation than in process innovation, and more in process innovation than product. To what extent do existing processes support a new business model? How can processes themselves be revamped to offer some new advantage? Do existing processes facilitate new product development?

As for agility, are processes modified when new information about customers and markets becomes available? Do internal boundaries and power centers block such change? Is the enabling technology inflexible and acting as a dead weight on attempts to change?

Working from current process models, process analysts and domain experts collaborate to generate to-be models that can satisfy the aims of business model scenarios. Next, they perform a gap analysis between the current process model and each to-be model to determine which processes need to be eliminated, streamlined, automated, or outsourced and to anticipate the potential impact of these changes on supporting applications and systems.

Drilling down from this high-level view of process optimization, there are four key steps: translate business model requirements, assess the value of existing processes, analyze process gaps, and develop functional requirements.

Here’s an example: A team of process analysts is working on a project for which they need to diagram the approval process for purchasing non-production goods. Using conventional methods, their actions would be informed by an in-depth analysis of the decision at-hand. They would start by gathering as much data as possible:

The current approval process

The complete list of approved suppliers, products, and contract types

The organizational hierarchy and current purchasing limits for each employee

The existing technology assets that automate this process and

The supporting systems such as hardware and networks.

After pulling all this together, they would weigh the data, diagram a process flow that seemed to fit best given the constraints, and sign off on the decision.