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 thats 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.
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.
Heres 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.
This sounds reasonable at first, but it fails to take into account any ripple effects that might spread from this individual decision. Let's say, for instance, that one supplier relied on a legacy order processing system to interface with the company's procurement system. Let's also say that when the team reengineered the approval process they did so in a way that made it incompatible with this legacy application. And finally, let's say that this particular supplier accounted for 40% of all purchases of non-production goods last year.
Clearly, this should compel the process analysts to revisit their decision. But without an impact analysis they wouldn't find out about the ripple effects until too late.
The primary responsibility for process optimization falls upon process analysts and domain experts who possess detailed and accurate knowledge of how processes work. In some cases, companies will appoint process owners that have overall responsibility for improving particular processes. The discretion of these process owners spans multiple business functions, freeing them from the political and process restrictions generally imposed by organizational silos. Together, they model as-is and to-be states of the company's process environment to discover the best way to make business goals reality.
The principal drivers of process optimization are the goals and objectives inherited from the business model. These keep teams focused on making changes that are in step with espoused management vision and concrete corporate needs. In turn, the results of process optimization drive the set of decisions made during technology automation.
By approaching process optimization in this way, companies avoid the costly disconnects that can occur when handoffs between business, process, and technology are not structured and managed effectively.
Faisal Hoque is the chairman and CEO of BTM Corporation. BTM innovates new business models and enhances financial performance by converging business and technology with its unique products and intellectual property (IP).