This article originally appeared on the BeyeNETWORK.
By submitting your email address, you agree to receive emails regarding relevant topic offers from TechTarget and its partners. You can withdraw your consent at any time. Contact TechTarget at 275 Grove Street, Newton, MA.
Planning, forecasting and aligning resources on the demand side of the supply chain still elude many organizations. Success is often defined by critical factors, such as exceeding customer commitments, reducing excess inventory and obsolescence and meeting plans. These are major objectives that affect bottom-line results. Without the right information to plan and forecast, manufacturers may not know how to balance satisfying customer needs and delivering to promise. This balancing act requires organizations to arm themselves with answers to tough questions. These questions include:
- Is my current inventory position in alignment with target inventory (snapshot – actual versus target)?
- Is my future inventory plan in alignment with my target inventory (plan versus target)?
When the answers to these questions are misaligned, inventory costs can soar and customers are left hanging.
Bill Mackie is the Managing Principal at Oliver Wight, a leading supply chain performance consulting firm. “Organizations have to understand market conditions and historical demand patterns so as to proactively forecast future demand for products and services,” states Mackie. “This information must be aggregated across multiple dimensions as required by many different consumers of demand information.” Mackie further clarifies this statement. “Demand Management emphasizes supporting collaborative planning to prioritize these different types of demand when supply is lacking. In this way, a company can better plan and use resources to improve profitability.”
To enable and sustain collaboration across the demand management function, you must continuously communicate critical and time-sensitive information. This must be done in a way that is meaningful to various constituents. In Demand Management Best Practices: Processes, Principles and Collaboration, Colleen Crum successfully summarizes the problem. Crum, another Managing Principal with Oliver Wight, states “Success is not predicated upon the mere communication of demand information… success is dictated by the reliability of the demand information and what company managers and trading partners do with the information; that is, how the demand information enlightens decisions and drives actions.”
Why is communicating, planning, forecasting and actuals for demand management so difficult? Let’s explore these dimensions in more detail, as well as how business intelligence can help companies improve reliability of information and enlightened decisions that drive action.
Reliability of Information
Reliability means having accurate information in the hands of decision-makers in a timely and consistent manner. Organizations with numerous systems and technologies are vulnerable when they cannot integrate the required information to deliver insight on operations. Why is this? Executives desperately need access to operational metrics from across the supply chain so they can assess the impact on revenue, costs, asset utilization and possibly even shareholder value and earnings per share. Today, with the current state of reporting across many manufacturing companies, decision-makers are forced to sift through disconnected data. These decision-makers must painstakingly piece together operational clues, which reduce the reliability of their decisions. Today, guessing is not good enough.
How can business intelligence help? Business intelligence technologies can enable a single source of integrated and trusted data from across the supply chain landscape. And it does not have to be expensive. The key for most manufacturing companies is defining what matters most: a subset of key performance measurements (KPIs) that drive bottom-line results. For demand management, Crum says that “The purpose of performance measurements is to determine the effectiveness of the demand management process, which includes planning, communicating, influencing, prioritizing and managing demand.” How many KPIs are required? Ignoring units of measure, variance and time series analysis, Mackie suggests that around ten KPIs generally drive demand. Whatever particular KPIs these are depend on your business. The point is that there is some minimal subset of KPIs that can deliver the right operational insight to assess financial impacts. In general, the KPIs will be organized around product family, product mix, SKU, market share, market segment, sales region and overall accuracy. SKU-level forecasts are a good example: Which SKUs make up 80% of profit? Business intelligence can quickly deliver such operational insight. By doing this, the business can focus its attention on controlling the demand for higher-margin products. Getting help to define these KPIs may significantly reduce your company’s data integration costs, which increases the velocity of critical insight for changing your business.
Enlightened Decisions that Drive Action
Enlightened decisions that drive action arise from the presention of information that can easily be interpreted by management. This is done, so that management can know what to do. One example of this is in demand management. Decision-makers must know how to differentiate which customers are willing to purchase (unconstrained demand) versus the result of a decision to control the demand and match the supply to the opportunity (constrained demand). They must also understand how to handle excess inventory, product obsolescence, capacity, abnormal demand, or whether they are over-forecasting or under-forecasting. These are complex questions, requiring specific presentation techniques that enable action. Reports and dashboards thrown together and crammed with dials, pie charts and bar graphs are clearly not informative by themselves, because they do not help management translate the meaning of the visuals into necessary actions.
How can business intelligence help? BI technologies, which constructively present both quantitative and qualitative information, can help “connect the dots” for decision-makers. Information visualization is not an art, it is a science. While there are several authorities on applying specific visuals to display certain types of information, the key to effective information presentation begins with the definition of KPIs and their range of legitimate values, thresholds or exceptions. From these decision points, a sequence of actions can be derived. This is often called workflow. The chain that links actions together, based on KPIvalues, describes how management will use the information to make decisions. Applying the right visual at each decision point in the chain can be a powerful technique for providing insight. When visualization and workflow are combined, they can reduce autonomous decisions, which in turn improves operational performance. New insights are created as the business improves. These new insights change the business, which requires new information about operations, and therefore new KPIs. Thus, the cycle continues.
Increasingly, manufacturing companies are realizing they cannot contain the data explosion—or the growing need to deliver more insightful information across supply chain operations. This is particularly true for those with large and complex supply chains. With respect to demand management, Crum asserts that correlating demand “with other financial-related measurements demonstrates how an effective demand process contributes to the company’s financial performance.” She also states, “improved demand plan accuracy allows a company to operate with fewer buffer resources like inventory, thus lowering operating costs.” This is where business intelligence can help companies. Particularly for demand management, BI technologies can provide more timely and accurate information throughout the supply chain, as an input to the sales and operations planning process (S&OP). This is done to help sales and marketing generate more detailed product mix forecasts. Business intelligence can also assist in the distribution and communication of demand planning information, as well as the measurement of the overall performance of the demand planning process. Giving management access to more reliable and timely information (in the appropriate format) gives them the option to re-schedule or re-prioritize decisions that can improve demand accuracy.