Change : Sustaining Organizational Change

Raj Phalpher worked for Northern Telecom ( Nortel ) for fifteen years managing various facets of Quality. After Nortel, he joined Juran Institute Canada Limited as Vice President. Here, for three years, he was responsible for marketing and delivering, business performance improvement and change management related consulting services. He is currently Senior Vice President of Resultel Technologies Inc., a management consulting company that helps organizations achieve desired business outcomes and self-sustaining change.

 

Contact Raj Phalpher by e-mail: phalpher@resultel.com.


Magnitude of organizational change ranges from minimal change or maintaining status quo to revolutionary enterprise-wide re-engineering. This magnitude of change is a function of the vehicle used to drive the change. It is important to understand the capabilities of various vehicles and use the most appropriate one for the desired level of change, as killing a fly with a sledge-hammer is as inappropriate as attempting to kill an elephant with a toy-gun.

Our research indicates that maintaining status quo or seeking revolutionary enterprise-wide re-engineering are not healthy options for an organization. We find that organizations that embrace evolutionary change through process improvement and process (re)design achieve sustainable change. The most common vehicles for driving this sustainable change in ascending order of magnitude of change are Data Analysis, Process analysis, System Assessment and Customer Feedback.

Change is ‘making or becoming different’. When we talk about affecting change, it is assumed to be a positive one, or change for the better. For organization better is either increase in revenues or reduction in costs, or a combination of the two. Every organization strives to be better or seeks improvement over time.

On behalf of the various stakeholders, management drives continuous improvement over time. The magnitude of improvement sought depends upon a number of external and internal factors: the nature and the maturity level of the industry, organization’s current profitability level, the threats facing the organization or opportunities available to it, etc. The magnitude of this improvement ranges from minimal change or maintaining status quo to revolutionary enterprise-wide re-engineering. Sandwiched between these two extremes are varying degrees of evolutionary change through process improvement and process (re)design.

The magnitude of improvement or change increases almost exponentially as we move from minimal change ( or process control ) through process improvement and (re)design to enterprise-wide re-engineering. If the relative magnitude of change through process control is 1 and process improvement is X (X>1), then the magnitude of change through process (re)design is X2 and through re-engineering is Xn. 

Our experience indicates that the two extremes, process control and re-engineering, are of limited use. Maintaining status quo through process control implies little improvement over time. There is no significant increase in organizational effectiveness and it does not help the organization move forward. In light of nimble global competition, this is not acceptable. Enterprise-wide re-engineering, on the other hand, is just too radical. It is exhausting for management team driving it and has a low success rate. We find organizations that embrace evolutionary change through process improvement and process redesign achieve sustainable change. The most effective drivers are contained in the arc of sustainable change shown above.


The rest of this article defines these magnitudes of change, illustrates their differences and describes the vehicles used to drive these different magnitudes of improvement. 

 

Process control is maintaining status quo. It is maintaining the desired or specified quality level over time. If the quality level worsens from the specified or desired level, intervention takes place to bring it back to the original level. 

 

Process improvement is incremental improvement over time. It is removal of known defects or process deficiencies. In process control, troubleshooting takes place only if the actual measurement is different from the standard, whereas in process improvement, deficiency is known and the task is to investigate the root cause and implement corrective action. 

 

Process design or re-design is performed to satisfy the needs of the stakeholders. Design of a process requires systematic translation of needs into process features. Process improvement focuses on alleviating specific weaknesses of the process, whereas process design focuses on designing the process from ground up to satisfy the needs of varied stakeholders. Process improvement leads to reduction in dissatisfaction with the process, whereas design leads to increase in satisfaction level. 

 

Re-engineering is identification of the organization’s key processes and examination of each process from the design perspective. Process design examines and builds one specific process at a time, e.g. the billing process, whereas re-engineering is enterprise-wide examination of all processes and all resources: people, materials, machinery and power. 

 

A number of vehicles are available to drive the desired level of improvement or magnitude of organizational change. This magnitude of change is a function of the vehicle selected. Use of appropriate vehicles is critical for achieving the desired magnitude of change.


For example, implementing simple metrics such as product quality (defect rates, customer returns, etc.) or process metrics (orders shipped on time, service response level, etc.) help control current processes, and nothing more. No effort is spent improving product quality or productivity level over time. These metrics cannot be used to drive process redesign or re-engineering effort.


On the other hand, re-engineering is top-down, organization-wide and driven by the organization’s strategic vision, mission and goals, etc. It requires identification of key business processes, benchmarking organizational effectiveness metrics, such as customer satisfaction level or time to market, against other organizations, and redefining these processes. These efforts will impact everyone in the organization and it is anything but maintaining status quo.


Use of appropriate vehicles is necessary to achieve the desired magnitude of change. Equally important is understanding the capabilities of various vehicles and using the appropriate one for the desired level of change is necessary, as killing a fly with a sledge-hammer is as inappropriate as attempting to kill an elephant with a toy-gun.


Our experience indicates that the two extremes, process control and re-engineering, are of limited use. Several lists have been compiled on reasons why re-engineering efforts are not always successful. The most comprehensive list is the one by John Kotter .

  • Allowing too much complacency
  • Failing to create a sufficiently powerful guiding coalition
  • Underestimating the power of vision
  • Under communicating the vision by a factor of 10 ( or 100 or even 1000 )
  • Permitting obstacles to block the vision
  • Failing to create short-term wins
  • Declaring victory too soon
  • Neglecting to anchor changes firmly in the corporate culture

We find that organizations which embrace evolutionary change through process improvement and process redesign achieve sustainable change. The most common vehicles for driving process improvement and process design in ascending order of magnitude of change can be classified into four categories :-

  • Data Analysis
  • Process analysis
  • System Assessment
  • Customer Feedback

The magnitude of change obtained by these vehicles is as follows. Data Analysis leads to initiation of process improvement teams. Process Analysis leads to mostly process improvement and some process (re)design activity. System Assessments result in both process improvement and process (re)design activities. Customer Feedback is an effective vehicle for driving both (re)design and re-engineering activities. Details on each follow.

 

Data Analysis

 

A large number of organizations collect product and process metrics, and as long as these metrics indicate that product or process quality is within acceptable limits, no further action is taken. They are reviewed at the monthly management meetings, reports for senior management are produced, they are posted on factory walls, etc., but nothing much is done with the data. Valuable information about the organization’s performance just sits there.

 

Progressive organizations perform rudimentary analysis of the data collected using trend charts, pareto analysis, histograms, scatter diagrams, etc. to identify problems and spawn problem solving (or process improvement or quality improvement) teams. Some organizations go a step further and conduct a more detailed analysis of the data. However, the end result of this detailed analysis is the same: identification of a problem and initiation of a team to rectify the problem. 

 

Process Analysis

 

Whereas Data Analysis focuses on the outcomes of the process: product quality, process measurements, etc., Process Analysis is careful examination of various elements of the process to ascertain effectiveness of the process. Analysis consists of developing a high level flow diagram of the process and establishing the process boundaries followed by detailed documentation of each step in sequence. The detailed documentation is reviewed for completeness and accuracy, usually by those who are most familiar with the detailed steps or activities. 

 

Once the detailed process is documented, it is reviewed for rework loops, non-value added steps, waiting periods, etc. It is this review that reveals process weaknesses and opportunities for improvement. In most instances, the process of flowcharting itself reveals a number of disconnects, loose ends in the process and leads to process improvement activity. 

 

Outcomes of process analysis vary from organization to organization. In some organizations, the very task of developing a very high level flow diagram and defining process boundaries itself becomes so overwhelming that a decision to discard the current process and redesign it from ground up is taken. In other organizations, even detailed process flow diagrams do not reveal any major weaknesses. In this case, analysts dig deeper. They estimate time for each task versus total elapsed time to identify waiting periods, calculate the cost of quality, i.e. costs associated with product or process failures, internal and external, etc. to identify opportunities for improvement.

 

Data Analysis leads to process improvement whereas Process Analysis results in process improvement as well as some process design activity.

 

System Assessment 

 

Process Analysis focuses only one process at a time whereas System Assessment requires examination of the entire organization. It is an assessment of organizational effectiveness using one of the several models or criteria available: Malcolm-Baldrige National Quality Award ( MBNQA ), Canadian Award for Excellence, organization’s internal award criteria ( usually President’s Quality Award, or something similar ). These system assessments ascertain organization’s effectiveness by assessing such attributes as leadership, customer and market focus, business results, etc. 

 

Although these models have varying criteria and different relative weights for the various attributes, they are generally equally effective in identifying weaknesses. These weaknesses are more systematic in nature, usually span more than one functional group and require redesign of a process as opposed to a process improvement to alleviate a specific weakness. Cross-functional teams usually address process redesign. These teams ascertain the stakeholders and their needs, systematically translate these needs into features or attributes and build a process to satisfy these needs.

 

Some organizations have successfully identified opportunities for redesign as a result of their regular process audits to comply with ISO 9000 registration requirements. These are not the short-term corrective actions but the long-term preventative actions required by ISO 9000 standards. Some software development organizations have even used CMM to identify systematic problems and initiate system design.

 

Customer Feedback

 

Data Analysis focuses on outcomes, Process Analysis on the whole process and System Assessment on the whole organization. Customer Feedback goes a step further or a level higher to examine organizational effectiveness from the standpoint of the most important constituent, the customer. The jingle from the early eighties, “We do it all for you at Macdonald’s” applies to all organizations. Customer feedback in the form of both complaints and customer satisfaction surveys is one of the most effective drivers of organizational change.

 

The source of a complaint is a pro-active customer whose needs have not been addressed satisfactorily by the organization. The customer gladly provides details on reasons for dissatisfaction. Thus, customer complaints make the organization’s job easier by pinpointing the opportunities for improvement. Successful organizations capitalize on this and use this information to initiate process improvement teams. Repeated complaints about a certain product or service often lead to redesign of the product or process.

 

Compared to complaints, which are voluntary, Customer Satisfaction surveys are solicited feedback, and in a number of instances, forced feedback. Their effectiveness in identifying and driving improvement within an organization depends upon how the survey is designed, who is surveyed and how the data is analyzed. 

 

Survey responses are to some degree distorted: they are usually from existing customers and address issues deemed important by the surveying organization, and not the customer. In terms of respondents, written surveys are quite often passed on to other personnel within the organization, in some cases to persons far removed from the true recipients of service or product. In telephone interviews, while respondents fall within a wide range of satisfaction scores, they tend to be over-represented by extremely satisfied and extremely dissatisfied customers. There is opportunity for improvement also in the analysis of data collected. Some organizations go no further than cursory examination of the satisfaction scores and depending upon the results, ‘patting the back’ of the subordinates or ‘screaming’ at them.

 

A better driver of organizational change based on customer feedback is Customer Loyalty Analysis

 

Loyalty Analysis is based on customer behaviour, instead of a survey response. It provides this next step beyond satisfaction. It focuses on the subset of customers who are so dissatisfied that they take some or all of their business elsewhere. It is their feedback that provides the critical insights into economically leveraged deficiencies of the company. The feedback zeroes-in on the attributes important to the customer and not the organization. It enables an organization to use customer behavior expressed as lost business or opportunities as the basis for prioritizing and selecting improvements that will directly impact the bottom-line. It results in some process improvement, but mostly process redesign and re-engineering activities.

 

In summary, then, a number of vehicles are available to drive the desired level of improvement or magnitude of organizational change. As indicated in Figure 2, this magnitude of change is a function of the vehicle selected. Use of appropriate vehicles is necessary to achieve the desired change. Our research indicates that the two extremes, process control and re-engineering, are of limited use. We find organizations that embrace evolutionary change through process improvement and process redesign achieve sustainable change.

 

Arc of Sustainable Organizational Change

 

The most common vehicles for this sustainable change, in ascending order of magnitude of change, are Data Analysis, Process analysis, System Assessment and Customer Feedback.

 

Data Analysis focuses on specific outcomes; product quality and process measurements. The data is analyzed using trend charts, histograms, scatter diagrams, Pareto analysis, etc. 

 

Process Analysis examines the whole process. Starting with high level flow diagram, detailed process steps are documented and analyzed. Some organizations analyze these detailed process steps further using task and wait times or cost of quality data. 

 

System Assessment audits the whole organization using a recognized award model (Malcolm-Baldrige, Canada Award for Excellence), an international standard ( ISO 9000 ), a business specific model ( CMM model for software development ) or an internal award criteria ( corporation’s President Award ). 

 

Customer feedback scrutinizes the organization from standpoint of its most important constituent, the Customer. Customer feedback may be voluntary ( complaints ), solicited ( satisfaction surveys ) or based on analysis of customer behaviour.


© Copyright 1999 by Raj Phalpher. All rights reserved.

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