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Instinct meets evidence: using operational data to drive planning by David S. Linthicum:
Many believe big data analytics are always the answer. In reality, most sales, financial, and operational planning is still run on incomplete data sets. Why? It’s hard to find the right people who can help enterprises understand their data. Understanding the efficiencies of product lines and market factors are perhaps the most important aspects of understanding the business. However, the traditional approaches to analytics largely overlook these aspects. Business is lost, a company’s value moves downward, and most companies have no clue why it happened.
A sale gained and a sale lost are not typical data points that are considered in the planning process alongside the historical sales of accounts, market growth, and new product offerings. While some IT-built reporting tools provide on-demand information, they tend to work within very rigid constraints. Without timely access to the data needed to make daily decisions, operations managers rely upon instinct over evidence. This is no way to run a business.
To take full advantage of what modeling and analytics can offer for effective planning and execution and integrate data into every decision process, businesses must put flexible tools directly into the hands of operations. This paper will evaluate the challenges and potential for creating models and applications and making those tools available and useful to those who need the information the most.
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