Discussion of the impacts of Weather on FMCG supply chain, and what businesses can do to increase their preparedness.

1. WEATHERING
THE STORM
During World War Two, radar operators
discovered that local weather produced
radar echoes and masked potential targets.
At the time, these echoes were an unwanted
nuisance and techniques were developed to
filter this type of scatter. Soon after the war
however, the value of viewing rainfall in real
time rapidly became apparent and surplus
radars were commissioned specifically to
track rainfall. Today, radar meteorology is
critical to short term weather forecasting
and helps to protect the lives and property
of millions every year.
In much the same way, weather driven
demand volatility has previously been
viewed by some as ‘scatter’, masking the
truly valuable information behind it. This
sentiment is changing fast. As improved
forecasting and observing systems allow
users of weather data unprecedented
understanding of past and future weather
conditions, volatility associated with weather
is fast becoming a key source of insight, and
even predictability.
The influence of weather on products on
supermarket shelves is profound, from
global supply, through transportation to
storage all the way to the consumer’s
decision on whether or not to buy. Some
variability is easy to understand anecdotally:
the amount of BBQ goods sales increase
around warm sunny weekends and the
amount of cold-remedy/Vitamin C increases
around the first cold turn of the winter.
However, the influence of weather extends
well beyond this anecdotal relationship
and in many cases this key source of
predictability is ignored or at least not
thoroughly understood.
In the past, without consistent data on
sales or consumer behaviour and with only
a handful of reliable weather observations
across the UK, producing meaningful
relationships between weather and demand
was difficult or impossible.
Furthermore, once this relationship was
understood, using weather forecasts to
predict demand or wider behaviour was
often discounted because of the relatively
low perceived quality of weather forecasts.
A quantum leap in understanding
In every respect, the science of using
weather to help predict human behaviour
has advanced rapidly in (relatively) recent
years. Widespread use of powerful IT
systems, capable of capturing historical
sales and other data, has allowed users
analyse historical demand simply and
efficiently. A quantum leap in weather
observation data (including the previously
mentioned weather radar and private
weather observations) has allowed users to
understand past weather in ways we never
imagined.
As a professional Meteorologist,
Byron has spent the last six
years helping companies and
individuals make effective use of
weather data, from supermarkets
estimating FMCG variability to
utilities estimating power demand,
and even rugby teams determine
match-day strategy.
www.metraweather.com
BYRON DREW DISCUSSES HOW METEOROLOGISTS ARE HELPING TO
BRING A BLIND SPOT INTO FOCUS WITHIN THE FMCG SUPPLY CHAIN
BYRON DREW
Manager of International
Meteorological Consulting
at MetraWeather.

2. Byron Drew
Manager International Meteorological Consulting
MetraWeather UK
T +44 118 3805063
M +44 7864 140 441
E byron.drew@metraweather.com
Alongside this deeper understanding of past weather, our
understanding of future weather is deeper and more accurate than
ever. The rapid advance of computing power (and particularly cloud
computing) has allowed numerical forecasters to create weather
models that are more hyper-local and more accurate than ever,
these models can now show us which borough in London will be
warmest tomorrow or just how far down a mountain slope the
snow will extend. Global collaboration has also allowed us to share
resources in centres like the ECMWF to build weather systems
capable of accurately predicting trends 2 to 4 weeks into the future
and provide valuable guidance on seasonal trends up to 7 months
ahead.
Today, a 5 day forecast is as accurate as a 1 day forecast was 40
years ago, and a 3 day forecast was only 20 years ago. This means
that in one generation, we now know as much about what will
happen on Saturday by the previous Monday as we used to know on
the Friday.
Arguably as important as all this is the changing attitudes of the
public and professionals within the sector to weather data and
forecasts, which is now providing the collaborative framework
between the Meteorological community and the FMCG community
to drive insights, and ultimately improve business practice.
Meaningful business decisions
While the advancement of science is interesting, what is more
exciting is what this allows a user to do with the information. In the
past, a rather vague understanding of past conditions and potential
future conditions led to few decisions being made based on a
weather forecast. Now, users can use the deep insights they have
learned from their data, apply it to a very accurate weather forecast
and make real meaningful business decisions. A forecast of an
upcoming warm weekend causes demand analysts to order more
BBQ’s and Pimms.
A manager can roster more staff at a bowling green on the first
sunny weekend of spring or a store manager can move the Vitamin
C to the front of store to coincide with the first cold snap of winter,
increasing opportunistic sales.
The simple example of lettuce helps show the depth and breadth
of weather’s influence. A mild March (like the one we had in 2017)
will produce an early UK lettuce crop. Warmer weather will increase
refrigeration costs during storage. Spring rain and wind can causing
flash flooding or bridge closures, which will delay or interrupt
distribution.
Impacts on buying behaviour
Even when the produce reaches the customer, a warm sunny day
will significantly increase the customer’s likelihood of buying. With
today’s data, we can model lettuce growth based on past years and
provide the farmer with guidance on how early he/she can plant
based on growth-risk factors and alert supply analysts that the
lettuce season will produce early yields, weeks before the lettuce is
ready.
We can model storage electricity consumption alongside
temperature and humidity and provide site manager estimates of
increases/decreases in electricity consumption. Incredibly detailed
and accurate rainfall forecasts help us to warn transporters hours
or even days ahead of a potential flood risk and sophisticated wind
force models help us alert transporters on whether a bridge may
close and whether their vehicles will be affected on the road.
We can model lettuce sales based on weather behaviour and provide
a demand analyst with an objective demand forecast four weeks
before the warm weather hits, helping them to more accurately plan
where to move their stock and when to put it on the shelves.
These decisions ultimately reduce waste, increase profit and prevent
reputation damage associated with stock-outs. Using the right data
in smart ways, businesses can and do seen real change in their
operations.
As with weather radar, what started as unwanted ‘noise’ is fast
turning into an invaluable tool to help us understand the tightening
balance between supply and demand.