Strategic planning stages and AI
| Stages | Purpose | Examples of AI |
|---|---|---|
| Analysis – external environment | Understand the external factors that might affect the organisation's performance. Identify opportunities and threats in the external environment that can be leverage or mitigate | Machine learning algorithms can scan and analyse vast amounts of data from a wide range of relevant sources to identify trends and insights related to the external environment. Natural Language Processing (NLP) can be used to extract sentiments and emerging themes from news articles, customer feedback, or market discussions E.g. Google Cloud Natural Language or Brandwatch |
| Analysis – internal environment | Evaluating the organisation's strengths and weaknesses by examining internal processes, resources, capabilities, culture, financial health and other relevant aspects | AI-powered analytics platforms can analyse internal data sources, such as sales data, operational metrics and employee feedback. Predictive analytics can then help anticipate potential internal challenges, while recommendation systems can suggest areas of improvement or highlight strengths to capitalise on E.g. Tableau or IBM Watson Analytics |
| Identify objectives | Setting clear, measurable and achievable goals for the organisation which give direction to the organisation and help to prioritise efforts | AI can analyse historical data to predict achievable targets. For instance, sales forecasting tools can predict future sales trends based on past performance and external factors, helping set sales objectives. Additionally, AI-driven simulations can test various scenarios and outcomes, aiding in more informed goal setting E.g. DataRobot or ThoughtSpot |
| Propose actions | Proposing strategies and tactics to help the organisation achieve its objectives. Setting up strategic choices, considering various options and selecting the most effective and efficient course of action | Optimisation algorithms can suggest the most efficient strategies or actions to achieve set objectives. For instance in marketing, AI can recommend the best channels or campaigns for reaching a particular audience segment or goal. At the same time decision support systems can evaluate the pros and cons of various strategic options E.g. Optuna or H2O.ai |
| Determine resources required | Ensuring that the organisation has the necessary resources to implement the proposed actions through effective budgeting, resource allocation and resource mobilisation | Machine learning models can forecast staffing needs, capital requirements, or other resources based on historical data and the proposed actions as well as optimise resource allocation efficiency E.g. AnyLogic or Jedox |
| Stages | Purpose | Examples of AI |
|---|---|---|
| Analysis – external environment | Understand the external factors that might affect the organisation's performance. Identify opportunities and threats in the external environment that can be leverage or mitigate | Machine learning algorithms can scan and analyse vast amounts of data from a wide range of relevant sources to identify trends and insights related to the external environment. Natural Language Processing (NLP) can be used to extract sentiments and emerging themes from news articles, customer feedback, or market discussions |
| Analysis – internal environment | Evaluating the organisation's strengths and weaknesses by examining internal processes, resources, capabilities, culture, financial health and other relevant aspects | AI-powered analytics platforms can analyse internal data sources, such as sales data, operational metrics and employee feedback. Predictive analytics can then help anticipate potential internal challenges, while recommendation systems can suggest areas of improvement or highlight strengths to capitalise on |
| Identify objectives | Setting clear, measurable and achievable goals for the organisation which give direction to the organisation and help to prioritise efforts | AI can analyse historical data to predict achievable targets. For instance, sales forecasting tools can predict future sales trends based on past performance and external factors, helping set sales objectives. Additionally, AI-driven simulations can test various scenarios and outcomes, aiding in more informed goal setting |
| Propose actions | Proposing strategies and tactics to help the organisation achieve its objectives. Setting up strategic choices, considering various options and selecting the most effective and efficient course of action | Optimisation algorithms can suggest the most efficient strategies or actions to achieve set objectives. For instance in marketing, AI can recommend the best channels or campaigns for reaching a particular audience segment or goal. At the same time decision support systems can evaluate the pros and cons of various strategic options |
| Determine resources required | Ensuring that the organisation has the necessary resources to implement the proposed actions through effective budgeting, resource allocation and resource mobilisation | Machine learning models can forecast staffing needs, capital requirements, or other resources based on historical data and the proposed actions as well as optimise resource allocation efficiency |
Source(s): Authors' own elaboration