Strategy formulation forces enterprise leadership and management to look at the changing environment and position themselves to compete in the ever-changing business landscape. Imagine if there was a framework that facilitated the automation of this process to expedite access to the intelligence and knowledge to build enterprise strategy. An automated process that emulates the collective minds of enterprise leadership and management.
Businesses today are complex structures and to capture data and information in a manual or semi-manual process is daunting, timely, and laborious. The enterprise generates so much data and information that is being captured or should be captured and analyzed to determine the breadth and depth of mechanisms that contribute to enterprise performance. The capture of the enterprise data and information should be done by way of artificial intelligence (AI).
There is a synergistic relationship between AI and building the strategic plan to continuously guide the enterprise to success. What needs to be known is how and where AI fits into the existing strategic management process and the changes necessary to achieve successful integration. Strategy starts with the definition of a vision and mission, which is then supported by strategy formulation to define the goals and objectives to meet the vision.
However, prior to beginning the strategy formulation process, enterprise leaders and managers must first perform an internal and external analysis of their environment. These analyses seek to surface information about occasions, patterns, trends, and relationships, which uncover strengths, weaknesses, opportunities, and threats (SWOTs) that help managers decide the best path of action for the enterprise.
Many enterprises are already implementing AI solutions, not knowing if they are formulated on an inclusive set of measures and indicators that provide insights into the enterprise’s performance. The ultimate goal is to capture relevant and essential measures and indicators—both financial and non-financial—that collectively represent the vital or essential components of an enterprise. The goal should be to build an Enterprise Intelligence Repository (EIR) that captures relevant and essential measures and indicators in a structure that supports the complexity of the enterprise. This is a first step to enhancing the integrity of strategy formulation, and subsequently, enterprise strategy.
Understanding the Business Is Key
In order to accomplish this, enterprises must first understand the discrete components of their business, as well as the way that they interact with one another. The many moving internal and external parts of an enterprise, or its vital components, have been codified as follows:
Customer: The associations (e.g., loyalty, satisfaction, longevity, etc.) an enterprise has built with consumers of its goods and services
Competitor: The position (e.g., reputation, market share, name recognition, image) an enterprise has built in the business marketplace
Employee: The collective capabilities (e.g., knowledge, skill, competence, know-how) of an enterprise’s employees
Information: An enterprise’s ability to collect and disseminate its information and knowledge in the right form to the right people at the right time
Partner: The associations (financial, strategic, authority, power) an enterprise has established with external individuals and organizations (e.g., consultants, customers, suppliers, allies, competitors) in pursuit of advantageous outcomes
Process: An enterprise’s ability (e.g., policies, procedures, methodologies, techniques) to leverage the ways in which the enterprise operates and creates value for its employees and customers
Product/Service: An enterprise’s ability to develop and deliver its offerings (i.e., products and services) that reflects an understanding of market and customer requirements, expectations, and desires
Technology: The databases, hardware, and software an enterprise has invested in to support its operations, management, and future growth and renewal
This taxonomy—put forth by Green & Ryan in 2005—establishes a path for enterprise leadership and management to identify assets, and subsequently, their related measures and indicators. It also, provides a foundation to construct a network of interactions (Green, 2009) (Green, 2010). Each of the enterprise vital components and assets introduces key questions that align with performance measures and indicators. Defining the measures and indicators beneath each asset builds a neural network of performance information, or enterprise memory. This structure paves the way to construct algorithms and machine learning for the strategy formulation.
It's important to recognize that constructing artificial Intelligence in an enterprise is not an overnight project. It must be thoroughly planned and introduced in a phased-in approach that targets high and low level gains. If intelligence is to be automated, then it is critical that functions and operations of intelligence be understood. Most importantly, in order to successfully implement AI, leadership, management, and workers must share the same goals and objectives and communicate effectively.
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Annie Green, D.Sc.
Annie Green, D.Sc., is a published author, speaker, and lecturer and serves as faculty advisor for the Certificate in Artificial Intelligence Management. She has built a career on the effective and efficient operations of organizations. Her experience surfaces from the grassroots of systems engineering which is inclusive of all components to produce business systems that align with the optimum performance of organizations.
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