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Organizational leadership can draw on 3 Strategic Thinking Games to master Business Strategy and apply in varied scenarios and organizational structures. The Strategic Thinking Games provide Decision Making models for senior executives to choose from and use as per the situation.
The Strategic Thinking Games are based on mathematics and statistics, particularly Probability Theory, and exhaustive research into the Business Strategy realm. Probability Theory is actually a branch of mathematics that deals with analysis of random phenomena. The basic element of Probability Theory is an experiment that can be at least hypothetically repeated under identical conditions, but may lead to different outcomes on different trials.
Each of the Strategic Thinking Games warrants employing a different mindset and decision-making approach to confront the challenges presented by a particular problem. Executives can apply these Strategic Thinking Models to control their future:
- Planning as Positioning
- Organization Learning
- Constructive Transformation
Let’s discuss these Strategic Thinking Models in detail.
Planning as Positioning
The 1st Strategy game allows the players to make 40 blind draws from a pot holding 25 black and 75 red balls. It costs $10 per draw—which has to be paid beforehand—and it allows the players the opportunity to win $20 on drawing a red ball but naught on drawing a black ball. The game imitates a scenario where managers make informed bets about the future based on data and insights into the level of uncertainty encountered.
The Planning as Positioning Model enables the executives to learn about their industry and competition, gauge ambiguities and uncertainties, and select markets that have the potential to generate a positive Return on Investment (ROI).
A classic example of a company operating on the Planning & Positioning Model was the International Telephone and Telegraph Corporation (ITT). For 17 years, the company was led by Harold Geneen (from 1960 to 1977). Harold Geneen was unrestricted by any company mission. He expanded in multiple industries, acquired around 350 enterprises from varied industries, including auto parts, cosmetics, hospitality, insurance, and technology. As a formal accountant, Harold considered facts as indisputable, final, and a foundation for making strategic decisions. He would travel to far-flung regions to meet his business unit managers, who were free to make their own strategic decisions but were responsible for their unit’s performance and objectives’ achievement.
Organization Learning
The 2nd Strategy game allows the players to blind draw from a pot containing an unknown mix of red and black balls. This time it costs $5 per draw. Players have to bet on either color before each draw. They can draw up to 50 times, or stop whenever they want, and win $20 if they draw the right ball. This game imitates a scenario for training managers to dynamically respond to upcoming events with unpredictable degree of uncertainty.
Through the pot filled with balls experiment, it was revealed that when people are given complicated choices, they behave in manners conflicting with their beliefs. In his famous Ellsberg Paradox, Ellsberg hypothesized that people make illogical preferences in order to avoid ambiguity. The Organizational Learning Model underlines that in a world full of uncertainties instead of spending too much time predicting the future, planning and positioning, organizations should devise and implement an evolving strategy, take one step at a time, search for viable patterns, and then adjust the course based on results.
An example of successful implementation of the 2nd Strategic Thinking Model is Corning Inc. that embraced Organizational Learning to develop a healthy product pipeline. The company developed Pyrex, TV tubes…..
Interested in learning more about the 3 Strategic Thinking Games? You can download an editable PowerPoint on Strategic Thinking Games here on the Flevy documents marketplace.
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– Roderick Cameron, Founding Partner at SGFE Ltd
Strategy Development has followed a set path since the last century where a predetermined, rectilinear, and inflexible approach defined the process.
In the 21st century, however, business leaders are devising Strategy by evolving it into a probabilistic, repeated, and multifaceted process. An approach that can both endure and adapt to the growing pace of Change and Disruption that is manifesting itself in all industries.
Using gaming, AI, unremitting execution, and adjustment, with numerous scenarios to deliberate on, leaders create “Flywheels” that successfully tackle the not so deterministic world where the future is highly uncertain.
Flywheel is a concept originally used in the power industry to explain an origin of stabilization, energy storage, and momentum. The concept was propagated in the Strategy context by author Jim Collins. Employing the Flywheel concept, executives are able to validate assumptions through simulations as well as in the real-world scenarios.
Rather than using past assumptions and relying on instincts, using the Flywheel Strategy, decision makers exploit the power of Artificial Intelligence (AI) and Advanced Analytics. They model the multitude of variables and produce a sizable number of simulations that propose many strategic bets, option-value bets, and no regret moves.
Instead of numbing decision-makers with a profusion of options they created, the simulations render elucidative insights. Also, the AI system is made more capable through learning mechanisms called Reinforcement Learning by selecting from the above strategies.
The collection of strategic choices is increased exponentially and cost of experimentation is diminished by this approach. Decision-makers are also empowered by this tool to make better decisions. Likewise, organizations are able to select accurate market approaches, pricing, advertising, and customer strategies for several cities and communities, over a time span.
Strategy Flywheels can be used as a basis for developing Growth Flywheels by organizations. The Flywheel Strategy approach consists of the following 3 phases:
- Sense: Market Sensing
- Think: Strategy Formulation and Investment Planning
- Act: Performance Evaluation and Learning
The dynamic and resilient Flywheel Strategy of Sense, Think, Act has 3 parts, which are based on establishing policies, contending with dynamic models within the background of environmental assumptions, and handling randomness.
Let us delve a little deeper into the 3 phases.
Sense: Market Sensing
Environmental assumptions are formulated through this procedure of extraneous Market Sensing.
Uncertainties to which probability assignment is difficult are the target of Market Sensing activity. Most urgent strategic matters can be detected and senior leaders consistently engaged in devising a response to them by recurrently sensing extraneous market changes.
Improvements in Machine Learning and cutting-edge AI can aid in not only expanding the quantity of information scanned but also enhancing the quality of content evaluated.
Think: Strategy Formulation and Investment Planning
Conventional strategic thinking can be aided in the new way of strategizing by the 3-phase process for Gamification—Design and Build, Simulate, and Evaluate.
A stable strategy consists of a portfolio of investments and projects with diverse risk profiles. Diverse risk profile of performance is a mix of:
- No-regret moves
- Strategic bets
- Option-value bets
Act: Performance Evaluation and Learning
Performance Evaluation and Learning from the efforts has to be carried out so that improvement in proficiency to sense the market and experiment with new ideas occurs.
Interested in learning more about how Amazon and Uber used Flywheels, how the Gamification approach is used in Flywheel Strategy formulation, and what constitutes a diverse risk profile? You can download an editable PowerPoint on Flywheel Strategy here on the Flevy documents marketplace.
Editor’s Note:
If you are interested in becoming an expert on Strategy Development, take a look at Flevy’s Strategy Development Frameworks offering here. This is a curated collection of best practice frameworks based on the thought leadership of leading consulting firms, academics, and recognized subject matter experts. By learning and applying these concepts, you can you stay ahead of the curve. Full details here.
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“Strategy without Tactics is the slowest route to victory. Tactics without Strategy is the noise before defeat.” – Sun Tzu
For effective Strategy Development and Strategic Planning, we must master both Strategy and Tactics. Our frameworks cover all phases of Strategy, from Strategy Design and Formulation to Strategy Deployment and Execution; as well as all levels of Strategy, from Corporate Strategy to Business Strategy to “Tactical” Strategy. Many of these methodologies are authored by global strategy consulting firms and have been successfully implemented at their Fortune 100 client organizations.
These frameworks include Porter’s Five Forces, BCG Growth-Share Matrix, Greiner’s Growth Model, Capabilities-driven Strategy (CDS), Business Model Innovation (BMI), Value Chain Analysis (VCA), Endgame Niche Strategies, Value Patterns, Integrated Strategy Model for Value Creation, Scenario Planning, to name a few.
Learn about our Strategy Development Best Practice Frameworks here.
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– Roderick Cameron, Founding Partner at SGFE Ltd
With most Transformation initiatives people gradually revert back to their old habits of doing things. Sustainable Change Management necessitates 4 key processes:
- Chartering—defining the scope, rationale, and team for the change initiative.
- Learning—testing and refining ideas before a full-blown execution of the initiative.
- Mobilizing—using symbols and metaphors to engage people and gain their buy-in for the change program.
- Realigning—redefining the roles and responsibilities and managing performance of the initiative and the people driving it.
These processes are critical to enable an Organizational Culture which encourages execution of lasting change.
In addition to these key processes, for the change to entrench into the organizational fabric, Leadership needs to put in place the environment necessary for the people to embrace and own the new processes, systems, and desired behaviors.
The 4 critical processes aid in creating the enabling conditions necessary for institutionalizing change in the organization. These enabling conditions for sustainable Change take place in 3 settings:
- Structural Context
- Procedural Context
- Emotional Context
The environment for sustainable change must be put in place way before the actual execution of the Transformation initiative. These enabling conditions encompass making changes to the organization’s structure, procedures, and sentiments / behaviors.
Let’s dive deeper into the 3 conditions critical to enable sustainable change in the institution.
Structural Context
The first element of the enabling environment requires the change leadership to work on reshaping the organizational structure. The 4 key processes have a direct bearing on the organization’s structure. Their effect pervades over:
- The organization’s hierarchy and reporting lines.
- Compensations, benefits, and rewards systems.
- Monitoring and control systems.
The Structural Context significantly affects the way employees’ work and expend their time and their interest in certain types of projects.
The structural context is altered during the Realigning process of Transformation in the way new personnel practices are employed. The Learning process informs the redefinition of linkage between the leadership and field staff. The Mobilizing process informs the changes to be made in the roles and responsibilities of the management and front-line people—through storytelling and metaphors. Whereas, the Chartering process helps instill a reformed, team-building culture in the organization. Together, these changes in the structural context cascade down across the organization.
Procedural Context
The Procedural context pertains to a feeling of objectivity and authenticity of new processes and systems. The Procedural environment involves the perception of people that their views are taken seriously and acted upon while designing and implementing a new initiative.
Procedural authenticity is critical in gaining commitment from the employees on initiatives that were not validated by them earlier. It involves belief of the people that the change initiative integrates well with the philosophies of the organization and the way business should be done. It makes the people feel heard, ensures trustworthiness of the change leadership through positive track records and effective decision making abilities, and alignment of the change initiative with the core values of the organization.
Interested in learning more about the other enabling conditions mandatory for institutionalizing change? You can download an editable PowerPoint on Conditions for Sustainable Change here on the Flevy documents marketplace.
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– Roderick Cameron, Founding Partner at SGFE Ltd
Accelerated pace of technological disruption has forced organizations to change. It has triggered leaders to think of the ways they must adopt to survive in these challenging times.
Organizations are confronting this scenario by embracing digital technologies. Traditionally, the focus of the organizations in these Transformation initiatives has remained on speed of change. To get the most out of their initiatives, they are making drastic changes, to include:
- Creating Agile Teams
- Introducing Mobile Apps
- Building Big Data and Analytics capabilities
- Experimenting with creative Digital Business Models.
Digital Transformation programs are launched with huge fanfare, see success early on, but fail to keep the momentum going. The issues that plague the sustainability of these initiatives are typically:
- Aging Technology Infrastructure
- Incompatible Operating Models
- Archaic ways of doing business
- Change-agnostic culture.
Drivers of change for the Digital Leadership have changed significantly over the years. There is an increased focus on building scale when executing Digital Transformation. Leaders have realized that quick Decision Making is not the only element required for successful Transformation. To achieve its full potential, they need to create differentiated offerings and scale the most viable initiatives across the organization to create value.
Traditional organizations have started following the footsteps of digital disrupters like Amazon and Tesla. They are implementing new digital services and adjusting their operations. However, typical hurdles—e.g., old enterprise systems, bureaucratic red tape, delayed decision making, and segregation between IT and business units—make them slip back into the outdated ways of doing things.
Sustainable Digital Transformation involves building not only the technology infrastructure but also revisiting the operating model. Successful Digital Transformations essentially involve embracing 4 key strategies to enable an ecosystem that encourages change to stick as well as scale:
- Create a strong Digital Foundation
- Integrate and consolidate the Digital Ecosystem
- Front-end to back-end approach
- Create a new Business Model
Let’s delve deeper into these strategies.
Create a Strong Digital Foundation
Manufacturing and pharmaceutical industries are the major sectors that employ this strategy. The typical state of affairs in organizations implementing this strategy is such that they are in need of developing new digital capabilities from scratch to tackle nimble rivals who are churning out novel value propositions using digital tech. These companies are burdened by dated tech infrastructure, sluggish decision making, and dated business models. The risk of disruption to these businesses is growing but it hasn’t challenged them to transform drastically.
To them, building a digital foundation warrants acquiring novel foundational capabilities. Their approach should be to start implementing and managing small changes one step at a time. For instance, building a smart technology architecture with advanced Big Data, Analytics, and predictive modeling capabilities. This should be followed by testing prototypes of the new model to prove their worth before implementing a full-blown execution.
Integrate and Consolidate the Digital Ecosystem
This strategy has gained traction most in organizations from the Consumer Products industry. These organizations are typically marred by scores of fragmented IT systems running in different parts of the organization. There is a general inability to prioritize the most viable projects and scale them. The need to reform and rapid deployment of Digital Infrastructure is critical for survival.
The approach to Digital Transformation in these organization should be to establish a central management position to manage the initiative and streamline dispersed technology landscape. This entails revising the technology infrastructure and operating model, deploying a unified IT platform for gathering and storing customer data, establishing a common data repository accessible to all units to recognize customers’ needs, and creating a culture that encourages innovation, acts on creative ideas, and refines them through experimentation and advanced tools.
Interested in learning more about the other strategies to enable Digital Transformation? You can download an editable PowerPoint on Sustainable Digital Transformation here on the Flevy documents marketplace.
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– Roderick Cameron, Founding Partner at SGFE Ltd
Do people always follow a rational linear process to come to a decision? Studies have suggested that a combination of Decision Making Models are used by people to reach quality decisions.
Strategic Decision Making is a complex process with a lot riding on those decisions. Eliminating risk from Decision Making is unthinkable but radically enhancing chances of success is a realistic goal.
In making Strategic Decisions, executives tend to rely only on those Decision Support Tools they know best. The usage of non-optimal Decision Support Tools is, in part, due to lack of knowledge about which tools work best in a particular scenario and, in part, due to lack of information regarding what tools are available out there.
Having access to a variety of Decision Support Tools increases the likelihood of making a successful decision provided the decision maker has knowledge of which tool to employ or a combination thereof in various scenarios.
The following 5 Decision Support Tools or their combination is applicable in a variety of Decision Making scenarios:
- Conventional Capital-Budgeting Tools
- Quantitative Multiple Scenario Tools
- Qualitative Scenario Analysis
- Case-based Decision Analysis
- Information Aggregation Tools
In some cases, just one tool is needed while in others an assortment of tools makes for the best combination.
Let us delve a little deeper into some of these tools.
Conventional Capital Budgeting Tools
Projected Incremental Cash Flows are used from likely investments to ascertain whether a project merits being funded through the firm’s Capitalization Structure. Included in it are Discounted Cash Flow, Expected Rate of Return, and Net Present Value models.
Quantitative Multiple Scenario Tools
Decisions are analyzed by completely specifying possible outcomes and their probabilities. Mathematical, Statistical, and Simulation methods are employed to distinguish the Risk and Return properties of prospective choices. The tools include:
> Monte Carlo Methods
> Decision Analysis
> Real Options
Qualitative Scenario Analysis
These techniques are beneficial to decision makers who encounter excessive levels of uncertainty about outcomes because the techniques do not assume a conclusive and entirely specified set of possible outcomes.
Real-life business Decision Making often comprises of judgments that are based on incomplete and uncertain information. This can be mitigated by using appropriate Decision Support Tools. However, which tools are appropriate will depend on the answer to the following critical questions:
- Do I know what it will take to succeed?
- Can I predict the range of possible outcomes?
The Causal Model question—combination of Critical Success Factors (CSFs) and economic conditions leading to success—needs settling before we can proceed to answer the 2nd question regarding Outcome Prediction.
Managers need to ask the following in order to clarify the state of the Causal Model hence the answer to the question:
- Do I comprehend what combination of Critical Success Factors will decide if my decision leads to a successful outcome?
- Do I recognize what metrics need to be met to guarantee success?
- Do I have an accurate understanding of how to attain success?
The other question to answer is: Can I predict the range of possible outcomes?
Managers should ask the following in scenarios predicting various outcomes and probabilities:
- Can I outline the range of outcomes that may result as a consequence of my decision, both as a whole and for each Critical Success Factor?
- Can I measure the probability of each outcome?
Even where the CSFs and Model for Success are understood, it sometimes becomes difficult to predict range of outcomes and their probabilities due to uncertain conditions.
Interested in learning more about Decision Support Tools? You can download an editable PowerPoint on Decision Support Tools here on the Flevy documents marketplace.
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1. How to elevate your management skills to becoming a Leader in your organization.
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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
How do people make decisions? Do they always follow a rational linear process to come to a conclusion?
Studies have suggested that the traditional Decision Making model—commonly known as the Rational Decision Making Model—does not explain the whole ambit of Decision Making.
People, including managers of organizations, arrive at decisions using a variety of routes. Experts suggest that there are at least 3 Decision Making Models that work in consonance to make the best decisions. The 3 Decision Making Models are:
- Thinking First – Rational Decision Making
- Seeing First – Insight-driven Decision Making
- Doing First – Experimentation-based Decision Making
The latter 2 models need to supplement the 1st in order, for people in general and managers in particular, to improve the quality of Decision Making. Developing a strong understanding of these foundational Decision Making models is recommended for any Business Leader who seeks to make better, more informed, more rational decisions.
Experts have suggested that people have the capacity to use all 3 models for arriving at a decision and so do organizations.
The 3 approaches to Decision Making draw a parallel from science, art, and craft. People who are partial to Thinking are more into facts, those who favor Seeing appreciate ideas, and people who prefer Doing always value experiences.
Let us delve a little deeper into the details of the 3 Decision Making Models—Thinking, Seeing, Doing.
Thinking First
More commonly known as the Rational Decision Making Model, this model has a clearly identified process. It is linear, logical, effortless, and iterative—i.e., keeps travelling back and forth with interludes for new events, alterations for opportunities until conclusively arriving at a decision.
Thinking First Model is associated with science and is mainly verbal in nature i.e., comprising of linear words. People leaning towards the Thinking Model prefer facts.
Usually, the Thinking First Model is used in well-founded production processes. Thinking First succeeds when:
- The matter is well-defined.
- The data is trustworthy.
- The situation is structured.
- Thoughts can be restrained.
- Discipline can be applied.
However real-life Decision Making exposes some limitations in the Thinking First Model as rational Decision Making is uncommon.
Seeing First
Decisions are motivated as much by what is Seen as by what is thought. Visualization and conceptualization of a problem or situation is the basis for the Seeing First Model. It is usually used in creative solution finding. Experts have identified 4 steps in creative discovery:
- Preparation
- Incubation
- Illumination
- Verification
An example of Seeing First Model will be Mozart’s allusion to the best part of creating his music; “when I am able to see the whole of it at a single glance in my mind.”
Seeing First Model works ideally in circumstances where:
- Numerous elements have to be pooled into a creative solution.
- Commitment to the solution is steadfast.
- Communication takes place beyond boundaries.
Doing First
When stumped for a solution, diving head first and tinkering with a problem—bringing Problem Solving Mindset characteristics into play—leads to the necessary insights following trial and error. Attempting various things, discovering which among them functions, finding meaning in that and repeating the productive behaviors while abandoning the rest is the gist of Doing First Model.
Experts have identified 3 stages of this process:
- Enactment
- Selection
- Retention
Doing First Model is ideal, when for example, companies are faced with disruptive technologies or unchartered territories.
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Product managers, marketers, and designers are often confused as to what they should do to increase the chances of customers’ engagement and uptake of their offering. Changing individuals’ behavior to enhance engagement, productivity, innovation, and happiness isn’t straightforward.
It takes a lot of effort, time, and resources to execute initiatives aimed at transforming behaviors and Organizational Culture. However, most people aren’t interested in changing and like the status quo to prevail. This is where Behavioral Economics can help to know how customers behave, interpret their decision-making methods, and create solutions targeting those behaviors.
Product designers and marketers aspiring to drive acceptance of their products can make use of the 3 Bs of Behavioral Change to change understand consumer behavior. The 3 Bs of Behavioral Change classify the 3 elements essential to change behaviors, i.e.:
- Behavior
- Barriers
- Benefits
Understanding and employing these 3 Bs helps the designers and product managers instill change, inspire design and strategy-related decisions, increase the acceptance of new products / features and product engagement levels, and build new behaviors in people.
Let’s discuss the first 2 elements in detail.
Behavior
People have an inherent tendency to maintain the status quo. Behavioral change necessitates:
- Identifying individuals’ existing attitudes.
- Assessing and tackling psychological biases affecting individuals’ decisions.
- Carefully tracking behaviors that need to be changed.
- Ascertaining the most important desired behavior and exact action that is imperative to drive results.
- Getting the buy-in from all stakeholders on the key behavior.
- Deciding if the behavior should be permanent or transient.
Examples of key actions to change behaviors include spending 30 minutes thrice weekly doing cardio exercises and consuming salad at lunch daily to stay healthy.
Barriers
Understanding the barriers in behavior adoption assists in creating effective solutions to improve uptake of key behavior. The second step to induce behavioral change is to reduce barriers in its adoption.
- Every decision that a product user has to make, no matter how negligible, increases resistance in the likelihood of completing a specific behavior.
- These actions and decisions an individual has to take in order to achieve the desired behavior create points of friction in embracing key behaviors. For instance, people often find it difficult to decide when presented with complex choices. They tend to procrastinate or become a victim of decision paralysis.
- Removing the points of friction and resistance from any key behavior necessitates documenting and streamlining all decisions. The path of least resistance leads to desired key behaviors.
Examples of barriers include the thought process involved in the decision to select where to have dinner. This thought process is, in fact, a psychological barrier in actually going out and having dinner. Likewise, the decision to walk or drive to a restaurant is a logistical barrier and a point of friction that warrants making a decision.
To eliminate these barriers, we can either remove barriers entirely or just simplify the decision. For instance, elimination of a non-critical, open text field from a sign-up form—that probed the users about their business, which requires significant time to think and answer—can increase page-over-page conversion. In case choices are helpful for the users and cannot be eliminated, then it is best to simplify the decision process by giving fewer options instead of many, or by suggesting “recommended option” to the users.
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Enterprises invest in Analytics to improve Decision Making and outcomes across the business. This is from Product Strategy and Innovation to Supply Chain Management, Customer Experience, and Risk Management. Yet, many executives are not yet seeing the results of their Analytics initiatives and investments.
Every organization putting on investment in Analytics has experienced several stumbling blocks. This differentiates the leaders from the laggards. Analytics-driven Organizations have clearly established processes, practices, and organizational conditions to achieve Operational Excellence. Their commitment to Analytics is creating a major payoff from their investments and a competitive edge.
What It Takes to Be Analytics-driven
The Harvard Business Review Analytic Services conducted a survey of 744 business executives around the world and across a variety of industries. Their focus was on the performance gap between companies that have struggled to get a return on their Analytics investment and those that have effectively leveraged their investment.
The survey showed that Analytics-driven Organizations get sufficient return on investment in Analytics. In fact, they have been highly successful in gaining a return on Analytics investment. This is gainfully achieved as organizations use Analytics consistently in strategic decision making. Executives of Analytics-driven Organizations rely on Analytics insights when it contradicted their gut feel.
Essentially, Analytics-driven Organizations have reduced costs and risks, increased Productivity, Revenue, and Innovation, and have successfully executed their Strategy. Yet, in evolving the organization’s Analytics approach, there can be 4 core obstacles that can affect their drive to getting a greater return on investment in Analytics.
The Core Obstacles to Finding Return on Analytics Investment
There are 4 core obstacles to being an Analytics-driven Organization.
Let’s briefly take a look at the first 2 obstacles:
- Communication and Decision-making Integration. The lack of Communication and Decision-making Integration limits the integration of Analytics into workflows and decision processes do not reach decision-makers. As a result of these core obstacles, the use of Analytics is limited in specific areas.
- Skills to Interpret and Apply Analytics. A second core obstacle is the inadequate skills of business staff to interpret and use Analytics. In fact, the survey showed that only one-quarter of frontline employees use Analytics with only 7% using Analytics regularly.
The other two core obstacles are siloed and fragmented Analytics and time delay. These are two equally important core obstacles that can hinder the use of Analytics to maximize return on investment. Further, the 4 core obstacles are barriers to analytic success.
Are You Ready to Be an Analytics Leader?
Leaders use Analytics consistently in decision making. In fact, based on the survey, 83% of executives use it in business planning and forecasting. On the other hand, laggards only use it 67% of the time. Even in various aspects of the organization such as Marketing, Operations, Strategy Development, Sales, Supply Chain, Pricing and Revenue Management, and Information Technology, laggards use Analytics only half the time compared to Analytics Leaders.
Analytics Leaders always ensure that they establish the processes and organizational conditions to allow them to successfully deploy Analytics. In fact, to increase return on Analytics, organizations must undertake the use of four interrelated initiatives that will drive greater return on investment Analytics. These are four initiatives essential to building an Analytics-driven Organization.
One is building an organizational culture around Analytics. To achieve this the organization must have clear, strategic, and operational objectives that are set for Analytics. Second is deploying Analytics throughout all core functions of the business.
Starting with an Analytics-driven Culture can greatly facilitate cross-functional deployment of Analytics.
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Human judgment can be unreliable as these are all susceptible to errors. In Strategy Development, organizations make a lot of strategic decisions. These strategic decisions share a common feature: they are evaluative judgments.
In making these tough calls, a large amount of complex information must be weighed down and evaluated. While some management decisions are made without weighing quite so much information, yet strategic decisions involve the distillation of complexity into a single path forward.
With the unreliability in judgment, particularly in decision making, there is a need for a practical, broadly applicable approach to reducing errors. This approach is called the Mediating Assessments Protocol (MAP).
Why Human Judgment Can Be Unreliable
Human judgment can be unreliable as evaluations are susceptible to errors. These errors stem from known cognitive biases. There can be a tendency to give more weight to information that comes to mind easily because it is recent or striking than other more important facts. We have the tendency to notice, believe, and recall information selectively which confirms our preexisting hypotheses and beliefs.
Making decisions can also be affected by the Mental Model we have formed. This is an impression of a complex situation that is often less nuanced and more coherent than the reality it represents. When decision making is influenced by biases, there will be errors in decision making.
The 3 Core Elements of MAP
MAP or Mediating Assessments Protocol is a structured approach to Strategic Decision Making. It consists of 3 core elements.
- Advanced Assessment Definition. The first core element requires the identification of mediating assessments. Mediating assessments are key attributes critical to the evaluation.
- Independent Assessments. The second core element is grounded on the evidence available. It uses fact-based independently made assessments.
- Final Evaluation. The third core element is undertaken when the mediating assessments are complete. The final decision is discussed only when all key attributes have been scored and a complete profile of assessments is available. However, the final evaluation may not be undertaken if a deal breaker fact has been uncovered.
Understanding the Importance of MAP
Any organization is a decision factory. Many decisions made can shape the future of organizations. At the same time, many decisions have caused organizations to fail. Decisions, unlike physical products, cannot be quality checked. However, it can be improved by working on processes by which they are made.
Mediating Assessments Protocol (MAP) is an approach that can bring quality assurance to complex decisions. One of its strategic application is in structuring one-off decisions.
Structuring one-off strategic decisions is a type of strategic decision that makes use of explicit assessment as a basis for the decision. It requires leaders to make separate, explicit assessments of each aspect.
The use of MAP in structuring one-off decisions can limit the risk that a compelling narrative will sway board discussions and affect quality decisions. When there is a rigor of formal structure in strategic decision making, it has the benefit of sequencing the process resulting in more quality decisions.
The use of MAP requires very trivial extra effort yet it can bring a lot of benefits. Board discussions are more organized and focus than the usual process, but is not necessarily longer or more contentious. Important facts are less likely to be overlooked and thoughtful, self-critical consideration of trade-offs is more likely to occur.
Most importantly, the use of the MAP can lead to producing strategic outcomes when used in structuring recurring decisions.
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