Q. In a post pandemic world, what are some ways that companies can make their supply chain more resilient without weakening their competitiveness?
A. The short answer is demand-supply near real time response. Using demand signals such as regional Covid outbreaks, price, promo, demographics, econometric data (GDP etc.) to produce a more accurate demand forecast integrated to Supply Response determining exceptions in inventory (stock outs and overstocks), $GM, etc. Adding Risk Analytics to model different scenario’s and to analyze Forward Buys other risk mitigations strategies.
Q. Most global shipping lines have more money in the last 6 months than they have combined in the prior 10 years!I am interested to hear if retailers are finding it harder to forecast demand/tastes in an online world compared to face to face customer interactions.
A. Absolutely yes, retailers are finding it harder to forecast demand. Most forecasting systems CANNOT automatically and dynamically change models based on rapidly changing underlying factors effecting demand. SAS Visual Forecasting on the other hand produces better forecast accuracy by using these underlying factors to create models unique to the sku/location. These underlying (causal) factors can also be used in scenario planning to mitigate risk in the supply chain.
Q. In a low margin export business and with shipping companies continually increasing shipping rates with very little notice, how do business best plan for these changes as any move in logistic costs will have a big impact on profit margins?
A. The short answer is scenario planning, network optimization and profit analytics. Scenario planning using advanced analytics provides management guidance on potential outcomes of logistics costs, network optimization advises on the least cost shipping and powerful guidance on least cost/risk logistics, and profit analytics provides accountability for customers, vendors, routes, products etc.
Q. How do you monetize the risk/benefit of supply chain transformation (whetherAI/ML/process engineering) to justify and defend the investment decision to key stake holders? How do PoCs play a role in making a cost-benefit argument?
A. The only way to empirically prove the value of a AI/ML project is to do an assessment followed by a proof. A proof would use sample data for a past period and use the proposed AI/ML tools to generate ‘backcasts’ and what improvements would have occurred. An assessment identifies opportunities and the proof (PoC) conforms them.
Q. How relevant is the 18-month rolling forecast when there is a lot of uncertainty in the next 6-12 months?
A. Rolling long term forecasts are always relevant but may be less accurate. We’ve seen adoption of formalizedIntegrated Business Planning, Merchandise Planning, or S&OP process which aligns demand, supply, logistics, marketing etc. measuring results for continuous improvement.
Q. Is there a major shift on retail considering the covid situation in terms of product that the customer wants? Like giving more importance on essentials like food and household stuff…? What can you suggest about managing contracts on the supply side given the various disruptions we are experiencing at the demand side? Many are using the inventory replenishment model and uses data to predict the levels according to the demand. But given the many disruption on the demand side, the suppliers or manufacturers might not be able to follow the supply contractual terms.
A. Most industries are seeing major shifts in consumer behavior in terms of pantry loading, response to promotions, supply disruptions resulting in less adherence to vendor contracts. Our best recommendation is to consider a near real time demand – supply response system highlighting exceptions. Using demand signals such as regional Covid outbreaks, price, promo, demographics, econometric data (GDP etc.) to produce a more accurate demand forecast integrated to Supply Response determining exceptions in inventory (stock outs and overstocks), $GM, etc. Adding Risk analytics to model different scenario’s and to analyze Forward Buys other risk mitigations strategies.
