Did you know that the iHome alarm clock, common in many hotels, shows a small PM when the time is after 12 noon? You wonder how many people fail to note the tiny ‘pm’ isn’t showing when they set the alarm, and miss their planned wake up. Seems a little complicated and unnecessary, wouldn’t you agree?
Did you also know that most microwaves also depict AM or PM? If you need the clock in the microwave to tell you whether it’s morning or night, somethings a tad wrong.
More data/information isn’t always better. In fact, in many cases, it’s a costly distraction or even provides the opportunity to get the important stuff wrong.
Contrary to current thinking, data isn’t free.
Unnecessary data is actually expensive.
If you’re like me, then your life is being subjected to lots of data and noise…unneeded and unwanted information that just confuses and adds complication.
Just think about shopping now for a moment. In a recent and instructive study sponsored by Oracle (see below), the disconnect between noise and what consumers really want is startling:
- 95% of consumers don’t want to talk or engage with a robot
- 86% have no desire for other shiny new technologies like AI or virtual reality
- 48% of consumers say that these new technologies will have ZERO impact on whether they visit a store and even worse, only 14% said these things might influence them in their purchasing decisions
From the consumers view what this is telling us, and especially supply chain technology firms, we don’t seem to understand what’s noise and what’s actually relevant. I’d argue we’ve got big time noise issues in supply chain planning, especially when it relates to retail.
I’m talking about forecasting consumer sales at a retail store/webstore or point of consumption. If you understand retail and analyze actual sales you’ll discover something startling:
- 50%+ of product/store sales are less than 20 per year, or about 1 every 2-3 weeks.
Many of the leading supply chain planning companies believe that the answer to forecasting and planning at store level is more data and more variables…in many cases, more noise. You’ll hear many of them proclaim that their solution takes hundreds of variables into account, simultaneously processing hundreds of millions of calculations to arrive at a forecast. A forecast, apparently, that is cloaked in beauty.
As an example, consider the weather. According to these companies not only can they forecast the weather, they can also determine the impact the weather forecast has on each store/item forecast.
Now, since you live in the real world with me, here’s a question for you: How often is the weather forecast (from the weather network that employs weather specialists and very sophisticated weather models) right? Half the time? Less? And that’s just trying to predict the next few days, let alone a long term forecast. Seems like noise, wouldn’t you agree?
Now, don’t get me wrong. I’m not saying the weather does not impact sales, especially for specific products. It does. What I’m saying is that people claiming to predict it with any degree of accuracy are really just adding noise to the forecast.
Weather. Facebook posts. Tweets. The price of tea in China. All noise, when trying to forecast sales by product at the retail store.
All this “information” needs to be sourced. Needs to be processed and interpreted somehow. And it complicates things for people as it’s difficult to understand how all these variables impact the forecast.
Let’s contrast that with a recent retail implementation of Flowcasting.
Our most recent retail implementation of Flowcasting factors none of these variables into the forecast and resulting plans. No weather forecasts, social media posts, or sentiment data is factored in at all.
None. Zip. Zilch. Nada. Heck, it’s so rudimentary that it doesn’t even use any artificial intelligence – I know, you’re aghast, right?
The secret sauce is an intuitive forecasting solution that produces integer forecasts over varying time periods (monthly, quarterly, semi-annually) and consumes these forecasts against actual sales. So, the forecasts and consumption could be considered like a probability. Think of it like someone managing a retail store. They can say fairly confidently that “I know this product will sell one this month, I just don’t know what day”!
The solution also includes simple replenishment logic to ensure all dependent plans are sensible and ordering for slow selling products is based on your opinion on how probable you think a sale is likely in the short term (i.e., orders are only triggered for a slow selling item if the probability of making a sale is high).
In addition to the simple, intuitive system capabilities above, the process also employs and utilizes a different kind of intelligence – human. Planners and category managers, since they are speaking the same language – sales – easily come to consensus for situations like promotions and new product introductions. Once the system is updated then the solution automatically translates and communicates the impact of these events for all partners.
So, what are the results of using such a simple, intuitive process and solution?
The process is delivering world class results in terms of in-stock, inventory performance and costs. Better results, from what I can tell, than what’s being promoted today by the more sophisticated solutions. And, importantly, enormously simpler, for obscenely less cost.
Noise is expensive.
The secret for delivering world class performance (supply chain or otherwise) is deceptively simple…
Strip away the noise.