Seeing Around Corners: How Data Can Help

Computer scientist Alan Kay once said that “the best way to predict the future is to invent it.” Kay did: he helped invent the windowing user interface we now use every day.

It’d be nice if more companies could do what Kay did and invent the future, preferably one that includes a robust rebound. They can’t. But what they can do is anticipate its arrival. To do that, they need better data-collection practices. It’s the best way to hear the doorbell amid all the false alarms.

Lora Cecere over at AMR Research laid out some insights on this topic in her recent report Recovery Strategies: Seven Ways to Sense Demand and Predict the Upturn.

One piece of advice she has for businesses: think about your value chain, then design sensing mechanisms into your relationships. In doing so, your company can better understand point of sale and inventory movement data to help determine true shopper demand. This will make you more agile and efficient at all times. And — especially in these times — it may tip you to an upturn.

For retailers, it’s important to make use of downstream data from points of sale and inventory locations. This information can be used to reduce channel latency, shorten your …

Computer scientist Alan Kay once said that “the best way to predict the future is to invent it.” Kay did: he helped invent the windowing user interface we now use every day.

It’d be nice if more companies could do what Kay did and invent the future, preferably one that includes a robust rebound. They can’t. But what they can do is anticipate its arrival. To do that, they need better data-collection practices. It’s the best way to hear the doorbell amid all the false alarms.

Lora Cecere over at AMR Research laid out some insights on this topic in her recent report Recovery Strategies: Seven Ways to Sense Demand and Predict the Upturn.

One piece of advice she has for businesses: think about your value chain, then design sensing mechanisms into your relationships. In doing so, your company can better understand point of sale and inventory movement data to help determine true shopper demand. This will make you more agile and efficient at all times. And — especially in these times — it may tip you to an upturn.

For retailers, it’s important to make use of downstream data from points of sale and inventory locations. This information can be used to reduce channel latency, shorten your time for replenishment and provide intelligence on shoppers’ appetites.

Lora cautions that this type of strategy is most effective for manufacturers with a critical mass of retailers in the channel sharing data. That translates into a lot of data at critical points of the value chain for collecting intelligence.  She cites the effective data sharing efforts by a number of companies including Home Depot, Lowe’s and Wal-Mart. Thank you, Lora, for those insights and others in AMR’s blog.

Lora is also dead-on with her perspective on the benefits of moving from passive to active forecasting. It’s vital to move ahead in the area of forecasting processes so the timeframes are closer in line with the shifts in the market.

I’ll leave you with a final thought: the advantage in the next up economy will go to those companies that put in place active forecasting systems which better sense the shifts in customer demand. Or, as Lora puts it, “The answer is simple: improve capabilities to better sense demand. Companies need to reduce demand latency to see the upturn quicker. If not, decisions will be made two weeks too late.”

You can be sure Teradata will be helping businesses put those active forecasting systems in place to detect subtle shifts in demand and keep them ahead of the curve, just like we have for dozens of other industry leaders.

Darryl McDonald
CMO, Teradata

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