COVID-19 – click here for our latest updates

Demand Planning – The Future is Like the Past… Just Completely Different

December 12, 2020

by Fabio Rubeo

Supply Chain Director Strategy & Results Delivery, PMI


Here below I have summarized a few thoughts and a summary of my experiences with data coming from an interesting Digital Round Table discussion that I participated in with 15 other senior Supply Chain professionals. The Round Table was organized by Leon Wheatle from VF Media Limited, a meeting that I was honored to host.

The future is like the past….. just completely different.

I grew up in Rome in a burrow where buying goods and services at small local businesses was the norm. Honestly not out of any civic loyalty to local communities, simply because at those times, big retail had not reached Rome.

A local café on one of the old streets of Rome.

The beauty of small shops was clear, yes, the convenience but above all, the satisfying fact that the owner knew you well. Their ability to observe you, ask snoopy questions allowed them to know your tastes, your preferences your habits so made them able to serve me better faster and reducing the stress of multiple choices’, because we consumers always thrive with less choice.

Consumers don’t want more choice, but to be more confident in the choices presented.

Professor Scott Galloway

The same attitude of the super algorithms of TikTok, Netflix , Spotify is allowing these well-known companies to know me like the local owners at those time. Thanks to ubiquitous cookies and automatic snoopy questions, they are able to suggest video , series , movies , and music to me that I do not know but perfectly match my tastes, my preferences my habits. The data revolution, the algorithms is like a digital back to the future.

So like the more emphatic shop owners who were the most successful in the past, those who are able to be emphatic in data collection will open to the success of the future.

Marketers have known this for a long time. We in supply chain, have tried to press out as much as we can from the data available, but are surprisingly getting there just a tad later.

My direct experience….

I’m working for PMI , a company that built the world’s most successful cigarette company, with the world’s most popular and iconic brands. A company that a few years ago made a dramatic decision, declaring to work for smoke-free products that—while not risk-free—are a far better less harmful choice, than cigarette smoking. Results of more than a decade of efforts and important investments finally recognized recently by the Food and Drug administration too.

We in supply chain were among the first to understand the impact on the whole operations.

With classic tobacco product, the main ingredient being tobacco leaf, we were thinking in harvest time speed.

A farmer working the crop at a tobacco plantation.

Product, and packaging changes? in semester, Demand forecast accuracy? above 90 % almost effortlessly.

Suddenly we were projected in a space made by new brands, new categories being a mix of tobacco leaf, electronic devices, software upgrades and fashionable accessories. All coming with frequent updates, change of colors ( gosh,,,the change of colors!) , phase in phase out , product returns .

In a second we were catapulted into a world where we were collecting the best (or the worst ) of  our old past tobacco tradition, FMCG, fashion, electronics and software updates – all at once.

Forget the 90%+ forecast accuracy, forget the time measured in harvests. We suddenly were forced to measure our time in months, weeks, days and in the same big markets in hours!

We understood that near real time data were the only safe line to hang on.

That’s why we took the brave decision to jump in the (data) ocean and base all our supply chain , first in the FMCG world , on a platform that is allowing to project daily weekly demand forecast sensing signs ( and not any longer based on past experiences only ) that is automatically translated in a matter of minutes in mid-term plans for all our global mfg sites ( and not in painful 4 weeks ) while having full visibility of inventory and orders between production and markets.

The fun fact is that we started all of those for improving/speeding up atomization of our dear Supply Chain but soon after we realized that the SC data is fundamental to derive insights that are instrumental to take better strategic business decisions , better simply because of fresh, almost daily data.

Planning for demand on a global scale – driven by data.

A vertiginous journey where we made, oh yes, all mistakes we could make but that it is getting, step by step, one of competitive edge of the success of our brands worldwide as leading a reduced risk tobacco product.

I could continue for a long time with many trade stories of this dramatic change in my professional life.

Allow me to summarize the most important learning in few bullet points:

  1. Change Management
    • With any technological change somebody wins somebody thinks that they will lose. It’s trivial but we learnt that for every hour of change you need to invest at least 10 hours explaining, coaching, counseling the people impacted by the change.
  2. Data Democratization
    • As the quantity of data marginally grows, what changes In that data are now shared in a common platform open to everybody inside the company vs previous data always locked in personal excel, data base , ppt , CRM…where the line was “ the less I share the best it is for my career”:… Data democratization unlocks enormous opportunities in the field of inventory, obsolete and speed.
  3. Data Quantity and Insight
    • Quantity of data doesn’t improve the insights and resolution of problems. Quality of the business questions drives the search for the right data that helps the answer.
  4. Visibility doesn’t help action resolutions
    • Visibility alone, especially when brought where there was not, fuels debates discussions and does not help resolve things, insights well represented do. So do not expect that just by connecting SC hubs and sharing data for that approach alone to do the trick. Understanding the key business questions and extracting the data that gives the best insight will do.
  5. Speed is fundamental, it is important that processes are redesigned to build the capability to support the ingestion of so much data at such a speed.
    • Traditional IBP processes are designed to be monthly, weekly at best. Data with a new platform are poured with daily speed. How to leverage this high frequency is as important as collecting them.

Get new articles delivered straight to your inbox

Industry-led insights, opportunities and idea.
Subscribe to article updates below.

  • This field is for validation purposes and should be left unchanged.