functions performed by this system

The established strategic planning process is composed of a series of interrelated steps that consume large amounts of data before leading to the creation of strategies that must be implemented and monitored until their completion.

This generic process is explained well in the book, Managing Health Care Business Strategy, Second Edition.
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It is not plausible to automate that entire process with a single group of algorithms. Instead, the process has been divided into 21 components. The components are referred to by number. One or more algorithms will be engineered for each of those components; additional algorithms will be used to tie the components together.

Specific Functions

1. Assess “strategic thinking” in managers

   This component consists of an interactive program for assessing a person’s ability to think strategically. There are recognized characteristics of the thought processes of a person who is capable of thinking strategically. The program asks questions that elicit a person’s thoughts and attitudes about strategic or long-term or futuristic issues. Many will be multiple choice or yes-no. But the most useful questions will describe short (or longer) case situations and seek the person’s interpretation or suggestions for further action. The program will score the person’s strategic thinking IQ, perhaps iteratively as he proceeds through the questions. Being aware of his score may affect the person’s answers to later questions.

2. Develop managers’ ability to think strategically

   As a continuation of the assessment program, this one aims to improve a person’s competence in strategic thinking. It might be combined with separate offline reading of papers and case studies. It would ask questions and require completion of exercises. Feedback would be provided on the answers; a regularly updated score of strategic thinking IQ would be shown, indicating the person’s learning progress. In effect, the program would be a fairly aggressive form of online learning.

3. Gather and apply data on internal resources and competencies

   One of the most important functions that AI can contribute to the strategic planning process is the gathering, analyzing, interpreting, and regularly updating data about factors in the internal and external environments that affect strategy. That is the focus of this and the next component.

   The data gathered for this component will define what the organization is capable of accomplishing through its strategic plans. These are the assets of the organization, encompassing Resources and Competencies. These data inform the strategies that initially are created as well as any subsequent adjustments made to them as they are being carried out.

   The data will be found or generated within the organizations – in existing records, reports, and databases. For some types of resources or competencies, in some organizations that have never tried to quantify what they are capable of doing, it may be necessary to create systems to begin collecting data for the first time. These are some of the categories of internal data:

   • Physical organizational resources (finances, real estate, space, technologies, key raw materials, equipment)
   • Organizational systems (quality control, cost control, reporting)
   • Organizational operations (productivity, inventories, CGS)
   • Organizational human resources (competencies, skill licenses)
4. Gather and analyze data on the general effects of external environmental factors

   In this component, algorithms will be applied to data imported for these external factors in the same way that internal resources and competencies are addressed in the previous component. Strategies are affected by almost everything that goes on in the external environment in which an organization operates. These are some of the factors that comprise that environment:

   • Legal environment (laws, regulations, court decisions, enforcement vigor, at levels of city, state, national, other countries)
   • Political environment (specific politicians, ideological mood, lobbying opportunities, public policies, government spending/grants, government regulations)
   • Economic conditions (interest rates, inflation rates, consumer income, employment levels, government spending, at local, regional, national, international levels)
   • Technological innovations
   • Funding sources (financial markets, research grants, charitable contributions)
   • Market conditions (local, regional, national)
   • Consumer demographics (numbers, geographic location, age, employment, income, education, purchase behavior, lifestyle)
   • International markets
   • Emerging markets
   • Potential consumer demographics
   • Consumer product preferences (product features, price)
   • Competitors (number, size, strategies, competitive intensity)
   • Vendors (prices, service, product features, reputation)

   The most obvious benefit of these last two components is the assurance that an organization’s strategies will be based on all the factors that it believes might affect those strategies. And they will be based on accurate, scientific evidence concerning those factors. Another powerful benefit is that the continuous inflow of data means that strategic planning no longer must be a sporadic, once-a-year event. It becomes a constant stream of strategic decisions – initiating new strategies, cancelling old strategies, modifying existing strategies, and reacting to competitors’ strategies.

   Key to the success of these last two components: Both are highly dependent on large volumes of data. Which means gaining access to the data and putting them into a form that can be used by the algorithms that have been designed. Then, identifying the correlations, if not causalities, between levels of factors and chosen strategic objectives. The latter will be difficult. Over time, good learning algorithms should be able to describe meaningful relationships.

5. Define and recommend market segments

   Organizations rarely try to sell their goods or services to the entire market of prospective customers. Their strategies focus on segments of the total market. This component defines and recommends segments for the organization’s strategic attention.

6. Generate a strategic vision

   An organization’s strategic vision describes where it would like to be and what it would like to look like in five or ten years. It is the ultimate goal toward which all its activities are directed. That vision should reflect three things – what it is capable of doing (its resources and competencies), the setting in which its vision will be realized (markets, competitors, external factors), and the preferences of its key stakeholders.

   This system component presents two challenges. It will not be easy to develop algorithms that can read the preferences of stakeholders and translate them into a strategic vision for the organization. Those preferences often are not clearly and explicitly expressed. Furthermore, stakeholder preferences may change frequently over a period of time. Yet, it is a rule of thumb that strategic visions ought not to be changed very often.

   There are similar difficulties with the environmental factors that influence strategic vision.

   It is not likely that the algorithms in this component will be able to recommend a useful, binding strategic vision. Perhaps the best that can be achieved are pointers to the issues that should be addressed by the vision.

7. Guide understanding of internal value chain

   To fully appreciate its range of strategic options, an organization needs to fully comprehend its internal value chain. This knowledge will help it to find ways to lower costs or differentiate its product and service offerings. This system component guides the organization to recognize and describe its internal value chain and all its interlinked value-adding activities, and to simulate modifications of the chain through new configurations or new activities.

8. Guide understanding of industry value chain

   Each organization’s internal value chain extends backwards and forwards into an industry value chain. System algorithms will perform the same work for the entire sequence as they do for the internal segment.

   It is important to note that, like most of the other components in this strategic planning system, the algorithms in these last two components function dynamically. The data on which they are based change constantly, and therefore the effects on the organization’s strategies are constantly changing. One of the key benefits of this AI-driven system is that it reports those changes in as close to real-time as possible.

9. Identify value chain activities for Low-Cost Leadership strategy implementation

   This component takes the value chain analysis a step further by identifying activities and decisions at specific points in the chain that might be modified to implement a Low-Cost Leadership strategy. That is one of the most popular strategy alternatives espoused by Michael Porter.

10. Identify value chain activities for Differentiation strategy implementation

    The algorithms in this component identify activities and decisions at specific points in the internal value chain that might be modified to implement a Differentiation strategy. In particular, they will compare the organization’s capabilities with the market’s needs and wants to find points of potential differentiation in product or service. A Differentiation strategy is another important type of strategy defined by Porter.

11. Identify key success factors

    Many organizations make an effort to identify their Key Success Factors (KSFs) – the functions, activities, and business practices (defined by the market, not the company, and as viewed by its customers) that are critical to their relationships with customers. These are the three to five areas that a company must emphasize to realize its vision. AI will assist in this discovery by applying algorithms to the organization’s knowledge of the activities in its value chain (gained in components 7 and 8) that seem most closely related to those factors.

12. Propose competitor-focused strategies

    The ultimate purpose of this AI-driven system is the formulation (and constant update) of strategies that fulfill an organization’s mission and move it toward realization of its strategic vision. A valuable component of this system would be one that proposes competitor-focused strategies. That is, strategies that are responsive to the threats or opportunities that competitors present. Algorithms will apply rules of response to data on those threats and opportunities in order to propose specific courses of action.

13. Recommend strategies to achieve competitive advantage

    The ultimate achievement of the strategic planning function is the creation of a competitive advantage, preferably one that is sustainable. This, one of the most sophisticated components, analyzes all potential sources of competitive advantage in an organization’s operations and compares them to its competitors’ similar activities. Where it sees opportunities to gain an advantage, it recommends actions and initiatives to seize them. This will be one of the most difficult system proficiencies to create, especially if the goal is a sustainable competitive advantage.

    Algorithms will be trained on numerous examples of “competitive advantage” (described uniquely for each organization) containing large volumes of data about organizational resources, competencies, products, and services, as well as similar data for competitors, along with economic trends, emerging technologies, and legal constraints. They will generate repeated iterations of competitive advantage, that will be persistently evaluated for plausibility and “sustainability”.

14. Check for availability of resources and competencies

    As strategies are being formulated, often after consideration of multiple alternatives and iterations, this component constantly assesses the resources and competencies that they require and match them with what is available. It also suggests additional amounts of these assets that should be acquired and where they can be found. This is a complement to the work performed in component 3 above, though, if that is done thoroughly, this component should be unnecessary.

15. Check for effects of environmental factors

    The algorithms in this component perform the same function for external environmental factors as the previous component did for resources and competencies. They constantly assess the ways the factors may help or hinder the implementation of strategies, and suggest steps to exploit opportunities and overcome barriers. They build on the output created by component 4.

16. Perform quantitative assessment of strategy risks

    Different strategies present different levels of risk and managerial tolerance for risk varies. This component informs strategic decision-making by measuring risk. Applying algorithms to relevant risk metrics enables the quantitative assessment of the perils of each strategy, the threat posed by various competitors, and even the attractiveness of different market segments. Over time, attention will focus on metrics that appear to have the greatest influence on strategy success.

    Eventually, algorithms will assign risk scores to specific strategies, allowing comparisons among strategies. It also will be possible to balance strategy risk with leaders’ risk tolerance.

17. Guide managers to select specific strategies

    This component goes to the heart of the strategic planning process. Through pointed inquiries (about leader preferences, corporate mission & vision, strategic objectives, supporting data) and analysis of related data (market trends, consumer demographics, competitor behaviors, environmental factors), the system algorithms guide the selection of specific strategies. This is the most complex, most challenging of all the components in the system. It is likely to be one of the last developed as it relies extensively on data from other components like 3, 4, 5, 6, 7, and 8.

18. Prompt for functional area sub-plans

    To be implemented effectively, organization-wide strategies must be backed up by sub-plans within individual functional areas (e.g., finance, marketing, human resources, operations).. The algorithms in this component take information from already formulated corporate-level strategic plans (component 17) and, with knowledge of operational activities in each of the functional areas (reflected in the value chain, components 7 and 8), propose the basic terms of those sub-plans.

19. Suggest operational decisions for strategy implementation

    The final step in the strategic planning process is the implementation of the chosen strategies at the operational level. This component’s algorithms will be trained on data describing the operational activities carried on throughout the organization’s value chain. The results will be correlated with the specific requirements of each strategy, indicating what must be done to implement the strategy – and whether the organization is capable of doing that. Management then can make the appropriate operational decisions.

20. Analyze and propose multi-SBU portfolios

    For businesses with multiple strategic business units (SBUs), this system component analyzes the composition of their SBU portfolios and proposes adjustments to maximize strategic goals. One or more algorithms will be trained to apply the organization’s criteria for the SBU’s in its portfolio to the data that are gathered about relevant market conditions and organizations available for acquisition. Suggestions will be made to corporate leaders about changes in the composition of the portfolio, such as divestments and acquisitions, or a complete portfolio reconfiguration.

21. Monitor the implementation and effectiveness of a strategy

    It takes some time to fully implement a strategy which then may be in effect for many years. For optimum impact, the strategy must be monitored and managed throughout this period. This AI-driven component watches the metrics of implementation and reports on subpar performance, allowing management to step in and make corrections. Another feature of this component monitors the strategy’s achievement of strategic objectives, noticing when it is falling short, as well as changes in the external environment that may call for revision in the strategy (such as expanding, restricting, or dropping it).

There are two important characteristics of this sequence of strategic planning activities:

The activities do not operate independently of each other; they are tied together by algorithms that take the output of one component and feed it as the input to one or more other components. The net result is an integrated, synergistic, smoothly functioning strategic planning and management continuum.

There are critical points within the sequence at which human intervention and judgment is necessary. They are acknowledged and included in the design of the system.

The initial development phase will produce a prototype AI-driven system serving the planning needs of an exemplar business organization. This will not be a template that can be used without further modification by other organizations. Every entity (whether for-profit or non-profit) is faced by such diverse circumstances that the system will have to be custom-tailored to its unique conditions. This applies particularly to the data required and the configuration of the algorithms employed.