PowerPoint presentation
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example2.pptxThe Impact of Data Driven Operations on Supply Chain COVID-19 Tammy Holcombe Keiser University Operations Management
Rationale
Organization strategy used: Sustainability - which is creating long-term value by taking into consideration how a given organization operates in the ecological, social and economic environment. This strategy will allow me to address the procedures, processes, practices and systems to initiate, create and deliver outputs that are both profitable, using the resources available while also taking preservation and improvement of the natural and social environment into account.
Problem Statement
Being able to take ownership of a post-COVID-19 future is necessary for all businesses to survive during this pandemic. Businesses have to start asking the question “why do we do what we do”? Leaders have to learn to articulate how the firm creates value for all stakeholders, not just shareholders, and accept that profit is the consequence of such value creation. The process of defining purpose makes it clear that businesses exist to serve society and not the other way round, and the link to sustainability becomes clear.
Leaders have to discover their company’s purpose. Once that purpose is defined, it can then be brought to life. Leaders have to define concrete sustainability goals by answering questions such as: Where is the company’s growth likely to come post-COVID-19 and in the future? What new trends will affect demand for our products and the supply of our raw materials? What do our stakeholders want from the business?
Forecasting
I can address the procedures, processes, practices and systems to initiate, create and deliver outputs that are both profitable, using the resources available while at the same time taking preservation or even improvement of the natural and/or social environment into account.
Improve accuracy and confidence in budgets and forecasts
Identify the true drivers of business value, both internal and external
Set data-driven financial targets, based on a machine learning approach
Determine and eliminate bias from forecasts
Leverage predictive modelling and external signals
Link decision making with profitability
This creates the forecast for:
Better data and signals
Continuous learning and evolution
