Learn the methodologies, frameworks, and tricks used by Management Consultants to create executive presentations in the business world.
Initiatives aimed at improving performance are often launched with great uproar, costing an organization significant investments. Such initiatives necessitate extensive changes in the Organizational Culture and the way the enterprise systems and processes function.
However, most initiatives fall short of realizing success. Decades of scholarly research on Change Management reveals that the issues that contribute the most to the failure of strategic initiatives are:
- Incompetence in sustaining process improvement.
- Lack of trust on senior leadership.
- Failure to embrace new ways of doing business.
- Performance relapse.
- Inability of the initiative to produce any positive financial returns.
- Skepticism towards the desired behaviors and return of impractical employee behaviors.
Researchers have carried out scores of studies to isolate the drivers of lasting change. Research published in MIT SMR in 2005 discusses how leadership can design and execute Transformation initiatives that bring lasting changes in the organization. The study entailed in-depth analysis of the strategic Customer Service Enhancement (CSE) initiative undertaken by a large clothing retailer, having franchises in multiple geographic locations.
The researchers conducted 20 semi-structured interviews with leaders, in-store operations and support function managers. Detailed notes of the interviews were shared amongst the researchers alongside an exhaustive literature review. A case study of the initiative was prepared using independent research to have an unprejudiced viewpoint, free from any bias. Feedback from the organization’s management was gathered and incorporated throughout the study to seek clarifications or corrections. Data analysis was carried out employing a coding scheme developed using Atlas.ti tool. Comparative analysis was conducted and similarities and differences in conclusions were discussed.
The study brought to light 4 key processes necessary for change to stick in an organization. These key processes assist in laying the foundation for successful institutionalization of change initiatives by creating a company-wide culture that encourages enduring change:
- Chartering
- Learning
- Mobilizing
- Realigning
Let’s delve deeper into the first 2 processes.
Chartering
Chartering is a process through which an enterprise classifies the purpose, scope, and the way people interact with each other on a strategic initiative. Clear delineation of project boundaries, resources, responsibilities, and reporting lines are the elements integral for the success of a change initiative.
The Chartering process entails 2 critical components:
- Boundary Setting
- Team Design
Boundary Setting involves the key steps a team takes for accurate definition of change initiative’s scope.
The project team should clearly outline the problem(s) that the project is, and isn’t, going to tackle. Ideally, while designing and executing a change initiative, the focus of the engagement should be on confronting the most crucial problem area. The leadership should ensure not to confuse the core team by eyeing too many priorities to deal with through the strategic initiative.
The Team Design element of Chartering involves ascertaining the roles, accountabilities, and guiding principles for team’s collaboration. Team design entails creating ground rules for team members to interact, devising mechanisms to manage conflicts. The leadership needs to not only maintain diversity of the project team’s expertise, but also ensure they complement each other, and inculcate a standardized approach to decision making in project teams. There needs to be fostered a culture of positive discourse and testing ideas amongst the team members. Incorporating these guidelines helps spark thinking, learning, and decision making.
Learning
Learning aids in anticipating and dealing with hurdles during implementation of Transformation initiatives. Learning enables the managers to improve the quality of the new processes. it is a process through which managers develop, test, and refine ideas before full-scale implementation. The process entails 2 critical components:
- Discovery
- Experimentation
The discovery element involves gathering data to identify the objectives of the change initiative and outlining ways to achieve those objectives. Before rolling out a complete implementation of a change initiative, testing and refining the individual elements of the initiative immensely assists in the success of the initiative. Gathering adequate information relevant to the initiative, setting up baseline metrics to measure performance, and identifying issues hampering customer satisfactions are the key aspects of this phase. The team should learn from the failures of prior initiatives, introduce change in a systemic fashion rather than piecemeal, and encourage people to change rationally as well as emotionally.
Interested in learning more about the other processes critical for change to stick? You can download an editable PowerPoint on 4 Processes of Sustainable Change here on the Flevy documents marketplace.
Did You Find Value in This Framework?
You can download in-depth presentations on this and hundreds of similar business frameworks from the FlevyPro Library. FlevyPro is trusted and utilized by 1000s of management consultants and corporate executives. Here’s what some have to say:
“My FlevyPro subscription provides me with the most popular frameworks and decks in demand in today’s market. They not only augment my existing consulting and coaching offerings and delivery, but also keep me abreast of the latest trends, inspire new products and service offerings for my practice, and educate me in a fraction of the time and money of other solutions. I strongly recommend FlevyPro to any consultant serious about success.”
– Bill Branson, Founder at Strategic Business Architects
“As a niche strategic consulting firm, Flevy and FlevyPro frameworks and documents are an on-going reference to help us structure our findings and recommendations to our clients as well as improve their clarity, strength, and visual power. For us, it is an invaluable resource to increase our impact and value.”
– David Coloma, Consulting Area Manager at Cynertia Consulting
“FlevyPro has been a brilliant resource for me, as an independent growth consultant, to access a vast knowledge bank of presentations to support my work with clients. In terms of RoI, the value I received from the very first presentation I downloaded paid for my subscription many times over! The quality of the decks available allows me to punch way above my weight – it’s like having the resources of a Big 4 consultancy at your fingertips at a microscopic fraction of the overhead.”
– Roderick Cameron, Founding Partner at SGFE Ltd
Data and Analytics, today, play a key role in competing with rivals. Every passing day leads to creation of enormous amounts of data by organizations across the globe. These huge data lakes often go unused, or are underutilized, by organizations. This data, if utilized properly, is of great assistance in informed decision making.
Multiple data types and sources generated by discrete systems are often inconsistent, dispersed, and lacking integration, which makes them unworkable. Such data results in inaccurate analysis and flawed insights. Reliability and confidentiality of data can be ensured by stipulating rules and processes to govern access to data and its Metadata.
Metadata Definition
Metadata can be defined as “the Data in the context of Who, What, Where, Why, When, and How.” It’s the information pertaining to the data itself, its attributes, and elements. Metadata provides searchable key attributes of information to the users e.g., Customer ID or Name. Appropriate identification of Metadata is a major step in uncovering the potential locked in enterprise data assets.
Metadata Management
Metadata Management relates to handling of data, its description, relationships, and lineage within an organization. Metadata enables a user to search and identify information on certain key attributes. Context of data is of prime importance in managing Metadata.
Metadata isn’t all about identification of data. With ever-increasing volumes and complexity of data, Metadata management is getting critical to identify informational assets and convert those into enterprise assets of high business value. This entails setting up policies and ensuring efficient information management. Metadata Management integrates all data at the enterprise level.
Benefits of Metadata Management
- An efficient Metadata Management system helps the business users to comprehend the source of the data characteristic and the calculated measure of that characteristic.
- It supports the technical users in mapping business Metadata with technical Metadata.
- Metadata Management provides a holistic view of the various data systems in an organization.
- It enables automated parsing and loading of variety of Metadata types.
- Building an Enterprise Metadata model based on the data generated from discrete systems—e.g. data warehouse, integration tools, and data modeling tools—is quite efficiently done through Metadata Management.
- Mitigation of any challenges in data accessibility and utility.
- Enhancement of data quality.
- Supporting Digital Transformation by creating data reporting and data analysis experts.
Metadata Classification
People in the same organization perceive Metadata differently. Difference of opinion in the identification of Metadata within the company results in inadequate visibility and access to data. This is where a broader classification of the types of Metadata is helpful. A thorough understanding of the different classes or categories of Metadata assists in developing a standardized perception of data across the organization. These categories include:
Structured Metadata
Structured Metadata provides information on what the data looks like, e.g., data elements names mapped to columns, descriptions of data elements, data types, length of data elements, and the file layout. This can include tags, primary keys, or foreign keys.
Supplier Metadata
Entails information associated with data origination point, directives, constraints, owners, service level agreements for consumption of data, demographic information about the data asset e.g., size, number of records, date of production, or source of origin of data.
Processing Metadata
Refers to data production processes, including data lineage, any 3rd-party sources of data, derivations of data elements, or the process flows related to data pipelines.
Query Metadata
Describes information on the context and classification of data. It includes a glossary of business terms, definitions, taxonomies, master data, historical data, types of queries performed etc.
User Metadata
Provides data on Metadata consumers, their roles, data owners, and data stewards responsible for managing the quality and usability of data.
Interested in learning more about the other categories and classifications of Metadata? You can download an editable PowerPoint on Metadata Management here on the Flevy documents marketplace.
Do You Find Value in This Framework?
You can download in-depth presentations on this and hundreds of similar business frameworks from the FlevyPro Library. FlevyPro is trusted and utilized by 1000s of management consultants and corporate executives. Here’s what some have to say:
“My FlevyPro subscription provides me with the most popular frameworks and decks in demand in today’s market. They not only augment my existing consulting and coaching offerings and delivery, but also keep me abreast of the latest trends, inspire new products and service offerings for my practice, and educate me in a fraction of the time and money of other solutions. I strongly recommend FlevyPro to any consultant serious about success.”
– Bill Branson, Founder at Strategic Business Architects
“As a niche strategic consulting firm, Flevy and FlevyPro frameworks and documents are an on-going reference to help us structure our findings and recommendations to our clients as well as improve their clarity, strength, and visual power. For us, it is an invaluable resource to increase our impact and value.”
– David Coloma, Consulting Area Manager at Cynertia Consulting
“FlevyPro has been a brilliant resource for me, as an independent growth consultant, to access a vast knowledge bank of presentations to support my work with clients. In terms of RoI, the value I received from the very first presentation I downloaded paid for my subscription many times over! The quality of the decks available allows me to punch way above my weight – it’s like having the resources of a Big 4 consultancy at your fingertips at a microscopic fraction of the overhead.”
– Roderick Cameron, Founding Partner at SGFE Ltd
Identifying what the market wants is a critical issue for most executives. Likewise, the decision on how much to charge for a product is also crucial for planners. This is where Market Research comes to rescue.
One of the Marketing Research methods that researchers most commonly employ is the Conjoint (Trade-off) Analysis. Conjoint Analysis helps in identifying product features that consumers prefer, discerning the impact of price changes on demand, and estimating the probability of product acceptance in the market.
In contrast to directly inquiring from the respondents about the most important feature in a product, Conjoint Analysis makes the survey participants assess product profiles. These product profiles comprise various linked—or conjoined—product features, therefore the analysis is termed “Conjoint Analysis.” Conjoint Analysis simulates real-world buying situations where the researchers statistically determine the product attributes—that carry the most impact and are attractive to the participants—by substituting the features and recording the participants’ responses.
The Conjoint Analysis Approach
The Conjoint Analysis is useful in creating market models to estimate market share, revenue, or profitability. The Conjoint Analysis is widely used in marketing, product management, and operations research. The Conjoint Analysis approach entails the following key steps:
- Determine the Study Type
- Identify Relevant Features
- Establish Values for Each Feature
- Design Questionnaire
- Collect Data
- Analyze Data
1. Determine the Study Type
The first step of the Conjoint Analysis involves ascertaining and selecting from a number of different types of Conjoint Analysis methods available. This should be determined based on the individual requirements of the organization.
2. Identify Relevant Features
The next step of the Conjoint Analysis entails categorizing the key features or relevant attributes of a product. For instance, setting the main product attributes in terms of size, appearance, price.
3. Establish Values for Each Feature
After selecting the key features of the product, the next step in Conjoint Analysis is to choose some values for each of the itemized features that have to be enumerated. A combination of features in different forms should be chosen to present to the participants. The presentation could be written notes describing the products or in the form of pictorial descriptions.
4. Design Questionnaire
The basic forms of Conjoint Analysis—practiced in the past—encompassed a set of product features (4 to 5) used to create profiles, displayed to the respondents on individual cards for ranking. These days, different design techniques and automated tools are used to reduce the number of profiles while maintaining enough data availability for analysis. The questionnaire length depends on the number of features to be evaluated and the Conjoint Analysis type employed.
5. Collect Data
A statistically viable sample size and accuracy should be considered while planning a Conjoint Analysis survey. It is up to the senior management to decide how they want to gather the responses—by taking the responses from each individual and analyzing them individually, collecting all the responses into a single utility function, or dividing the respondents into segments and recording their preferences.
6. Analyze Data
Various econometric and statistical methods are utilized to analyze the data gathered through the Conjoint exercise. This includes linear programming techniques for earlier Conjoint types, linear regression to rate Full-Profile Tasks, and Maximum Likelihood Estimation (MLE) for Choice-based Conjoint.
Types of Conjoint Analysis
There are a number of Conjoint Analysis types available for the marketing researchers to choose from, including:
- Two-Attribute Tradeoff Analysis
- Full-Profile Conjoint Analysis
- Adaptive Conjoint Analysis
- Choice-Based Conjoint Analysis
- Self-Explicated Conjoint Analysis
- Max-Diff Conjoint Analysis
- Hierarchical Bayes Analysis (HB)
Interested in learning more about Conjoint Analysis? You can download an editable PowerPoint on Conjoint Analysis Primer here on the Flevy documents marketplace.
Are you a Management Consultant?
You can download this and hundreds of other consulting frameworks and consulting training guides from the FlevyPro library.
Subscribe to our Newsletter
Most Viewed Posts
PowerPointing Templates
twitter
Error: Twitter did not respond. Please wait a few minutes and refresh this page.