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In today's analytic-savvy world, supply chain optimization has reached a commoditized plateau that is readily achievable and expected, resulting in scenarios where any additional operational cost margins will only occur if working inventory is reduced. Because of this, one of the great challenges for effective supply chains is in effective demand planning.
However, in end user interviews and inquiries in the Fall of 2014, Blue Hill found that companies have several key challenges in effectively implementing demand planning because of the inherent difference between operational production planning and the challenges of accurately forecasting sales channel activity.
First, demand planning often starts with mapping every relevant demand-based action that can be quantified. Although this approach is not inherently wrong, it leads to a flood of ad hoc messages that constantly provide new adjustments to corporate demand expectations. Rather than focus on the most recent changes in demand, supply chain officers have to shift to a mindset of prioritizing the most important demand inputs in a specific time segment.
Second, supply chain officers often lack an understanding that demand-based inputs are inherently biased and wrong. Unlike predictable machine behavior where the data biases and flaws are generally understood, demand inputs typically come from employees and channels with their own biases. Salespeople are inherently hired to be bullish on potential corporate outcomes. Support and operational personnel are “goaled” on always being available and never having failure, which makes them inherently conservative. However, businesses have to ultimately take all of these biases into account to accurately divine demand planning.
Third, demand planning is currently part of the most interesting battleground in enterprise applications: design. This does not simply mean that an application should be inherently beautiful, mobile, social or supportive of any other buzzword, but that the functionality should be obvious and valuable to the executives and managers seeking updates. Demand planning must be responsive to employee requests for specific demand drivers and effectively model each demand signal to a realistic range of potential results. For demand planning to be successful, the workflows and visualization must be well-designed and easily accessible.
Finally, demand planning comes with a poor reputation from those who have been burnt by poor demand planning initiatives in the past. Because demand planning can easily be damaged by poor planning and insufficient preparation, it is not difficult to find naysayers who will be reticent to buy into a demand planning project or program. To get past these concerns, demand planning must start with low-hanging fruit and easy departmental wins that will eventually be shared across the organization to align demand planning with success.
Design, data and departmental success are the keys to supporting successful demand planning in 2015. Although basic demand mapping and analytic modeling still matter, the real challenges are to take the necessary steps to ensure that supply chain officers can actually translate demand planning efforts into measurable business success. Net-net: demand planning is ultimately not a mathematical exercise, but a business enablement exercise.
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