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9662216489?profile=RESIZE_400xStrategy 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:  

  1. Sense: Market Sensing
  2. Think: Strategy Formulation and Investment Planning
  3. 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:

  1. No-regret moves
  2. Strategic bets
  3. 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.

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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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AI-2Artificial Intelligence (AI) is one area considered by many executives to enable Automation and steer positive growth.  A couple of years ago, most executives thought that deployment of Artificial Intelligence isn’t a big deal.  However, revamping traditional systems, implementing AI, and scaling it, in reality, is not as simple as it seems.

A survey by PwC Research in 2020, which gathered responses of 1062 business leaders, validates that scaling and industrializing AI is not straightforward at all.  Only 4% of the respondents asserted that they plan on implementing organization-wide AI in 2020.  A year earlier, the same survey revealed 20% of the executives planning to do that.  The survey shows a significant decrease in the number of senior leaders thinking of executing AI.

The reason for this dwindling interest in AI deployment is mainly because of the tough prerequisites necessary—contemplation, resources, preparedness, overhauling legacy systems, and integration of technology applications—for enterprise-wide AI implementation.

A robust AI Implementation Strategy needs to be first devised in order to assist the organizations in moving forward with their AI deployment plans.  Research reveals 5 key priorities of AI Strategy that businesses should follow to position themselves as AI leaders and reap value from Transformation in future.  These priorities not only highlight the key requirements for AI deployment but also pinpoint ways to maximize pay offs associated with the initiative:

  1. Boring AI
  2. AI-ready Workforce
  3. Responsible and Ethical AI
  4. AI Operationalization
  5. Business Model Innovation

Let’s delve deeper into a few of these key priorities.

Boring AI

One of the key reasons to employ AI, as cited by PwC research, is to automate routine administrative functions—e.g., using AI to pull information from tax forms, bills of lading, or invoices that can otherwise take up long hours of human effort.  44% of respondents revealed that AI will help them operate more efficiently.

To ensure AI adds value to the business, leaders should develop a strategy to identify the areas where AI can have a much deeper impact; build capabilities to do that; develop AI solutions, govern them, and embed them with existing systems.

AI-ready Workforce

Building or enhancing the capabilities of the workforce to become AI ready is critical today not only for technology enterprises but also for other businesses.  Organizations should identify the skills required for AI and train their people to deploy AI solutions.

However, thinking of achieving this through traditional means of offering training sessions isn’t a viable strategy to tap the opportunities offered by AI.  In addition to training people, organizations should cross-skill their people in multiple trades and provide them the opportunities to apply and hone in the skills learnt.  In fact, organizations should reward people who apply what they learn into real-time problem-solving and productivity enhancement.

Responsible and Ethical AI

AI can be perilous if adequate understanding of its responsible use and necessary procedures to protect against its risks and negative usage are not taken.  There are growing apprehensions around AI related risks e.g., biased algorithms, facial recognition tools, and deep fakes.  As per PwC survey, a large majority of respondents, using AI routinely, declared readiness in their organizations in terms of taking sufficient measures to protect against AI risks.

However, in reality most organizations are quite far from implementing controls around data and decisions generated using AI.  Just about 33% businesses mentioned having the ability to fully tackle risks associated with data powering AI, AI models, outputs, and reporting. It is imperative to have rigorous Risk Management processes in place to effectively use AI in the workplace and address the risks associated with it.   AI risks can be mitigated by integrating processes, tools, and controls needed to address AI bias, explainability, security, accountability, and ethics.

Interested in learning more about the other key strategic priorities essential for AI deployment readiness?  You can download an editable PowerPoint on Artificial Intelligence Strategy: Top Priorities 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

Learning n Development

Survival of a business in this digital age largely depends on its ability to timely embrace Digital Transformation.  Digital Transformation entails using Digital Technologies to streamline business processes, culture, and customer experiences.

In order to compete today—and in future—and to enable Digital Transformation, organizations should work towards fostering a culture of continuous learning, since Digital Transformation depends on learning and innovation.  The organizations that holistically embrace this culture are called “Next-Generation Learning Organizations.”

The next generation of Learning Organizations capitalize on the following key variables; Humans, Machines, Timescales, and Scope.  These organizations incorporate technology in enabling dynamic learning.  Creating Next-Generation Learning Organizations demands reorganizing the entire enterprise to accomplish the following key functions to win in future:

  1. Learning on Multiple Timescales
  2. Man and Machine Integration
  3. Expanding the Ecosystem
  4. Continuous Learning

Learning on Multiple Timescales

Next-Generation Learning Organizations make the best use of their time.  They appreciate the objectives that can be realized in the short term and those that take long term to accomplish.  Learning quickly and in the short term is what many organizations are already doing, e.g., by using Artificial Intelligence, algorithms, or dynamic pricing.  Other learning variables that effect an organization gradually are also critical, e.g., changing social attitudes.

Man and Machine Integration

Rather than having people to design and control processes, Next-generation Learning Organizations employ intelligent machines that learn and adjust accordingly.  The role of people in such organizations keeps evolving to supplement intelligent machines.

Expanding the Ecosystem

The Next-generation Learning Organizations incorporate economic activities beyond their boundaries.  These organizations act like platform businesses that facilitate exchanges between consumers and producers by harnessing and creating large networks of users and resources available on demand.  These ecosystems are a valuable source for enhanced learning opportunities, rapid experimentation, access to larger data pools, and a wide network of suppliers.

Continuous Learning

Next-generation Learning Organizations make learning part and parcel of every function and process in their enterprise.  They adapt their vision and strategies based on the changing external environments, competition, and market; and extend learning to everything they do.

With the constantly-evolving technology landscape, organizations will require different capabilities and structures to sustain in future.  A majority of the organizations today are able to operate only in steady business settings.  Transforming these organizations into the Next-Generation Learning Organizations—that are able to effectively traverse the volatile economic environment, competitive landscapes, and unpredictable future—necessitates them to implement these 5 pillars of learning:

  1. Digital Transformation
  2. Human Cognition Improvement
  3. Man and Machine Relationship
  4. Expanded Ecosystems
  5. Management Innovation

1. Digital Transformation

Traditional organizations—that are dependent on structures and human involvement in decision making—use technology to simply execute a predesigned process repeatedly or to gain incremental improvements in their existing processes.  The Next-generation Learning Organizations (NLOs), in contrast, are governed by their aspiration to continuously seek knowledge by leveraging technology.   NLOs implement automation and autonomous decision-making across their businesses to learn at faster timescales.  They design autonomous systems by integrating multiple technologies and learning loops.

2. Human Cognition Improvement

NLOs understand AI’s edge at quickly analyzing correlations in complex data sets and are aware of the inadequacies that AI and machines have in terms of reasoning abilities.  They focus on the unique strengths of human cognition and assign people roles that add value—e.g., understanding causal relationships, drawing causal inference, counterfactual thinking, and creativity.  Design is the center of attention of these organizations and they utilize human imagination and creativity to generate new ideas and produce novel products.

3. Man and Machine Relationship

Next-generation Learning Organizations (NLOs) make the best use of humans and machines combined.  They utilize machines to recognize patterns in complex data and deploy people to decipher causal relationships and spark innovative thinking.  NLOs make humans and machines cooperate in innovative ways, and constantly revisit the deployment of resources, people, and technology on tasks based on their viability.

Interested in learning more about the other pillars of Learning?  You can download an editable PowerPoint on Digital Transformation: Next-generation Learning Organization here on the Flevy documents marketplace.

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Learning n DevelopmentTransformation of an organization into a Next-generation Learning Organization (NLO) is a challenging endeavor.  The main hurdles include convoluted hierarchies, bureaucratic red tape, delayed decision making, and complicated organizational systems and processes.

To develop a learning organization, leadership needs to trim down bureaucracy and complexities.  They should make the best use of technology to gather holistic real-time data, deploy Artificial Intelligence at scale, and develop data-driven decision-making systems.

Five Core Pillars of Learning are essential for the creation of a Next-generation Learning Organization, including:

  1. Digital Transformation
  2. Human Cognition Improvement
  3. Man and Machine Relationship
  4. Expanded Ecosystems
  5. Management Innovation

Let’s take a deep dive into the first 3 Core Pillars.

1. Digital Transformation

The first pillar is Digital Transformation.  Next-generation Learning Organizations (NLOs) are characterized by their speed of learning and their adeptness to take action based on new insights.  They use emerging technologies to automate as well as “autonomize” their businesses, without relying too much on human intervention and decision-making.

By autonomizing, the NLOs enable machines to learn, take action, and evolve on their own based on continuous feedback.  They create integrated learning loops where information flows automatically from digital platforms into AI algorithms where it is mined in run-time to gather new insights.  The insights are passed to action systems for necessary action that create more data, which is again mined by AI, and the cycle continues, facilitating learning at fast pace.

2. Human Cognition Improvement

Next-generation Learning Organizations (NLOs) schedule time for their people to have unstructured reflection on their work.  While most organizations fear disruption of human work in future by AI and machines, NLOs assign unique roles to their people based on human cognition strengths—e.g., understanding relationships, drawing causal judgment, counterfactual thinking, and creativity.  These organizations are aware of AI’s advantage—in analyzing correlations in complex data promptly—as well as its shortcomings in terms of reasoning abilities and interpretation of social / economic trends.  NLOs make design the center of their attention and utilize human creativity and imagination to generate new ideas and produce novel products.  They assign roles accordingly, inspire imagination in people by exposing them to unfamiliar information, and inculcate dynamic collaboration.

3. Man and Machine Relationship

NLOs foster innovative ways to promote collaboration between people and machines.  They recognize that this helps them in better utilization of resources, maximize synergies, and learn dynamically.

To create effective collaboration between people and machines, NLOs develop robust human-machine interfaces.  The existing AI systems lack the ability to decipher everything, which is an area where humans excel.  NLOs supplement these shortcomings by setting up human-machine interfaces, where humans assist the AI by corroborating its actions and suggesting sound recommendations.  These learning organizations bifurcate responsibilities based on the risks involved, assign humans and machines appropriately against each job, and select a suitable level of generalization and sophistication between humans and machines.

Interested in learning more about the Core Pillars of Learning?  You can download an editable PowerPoint on Next-generation Learning Organization: Core Pillars 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.