79

Life-weather Merchandising
Katsumi TOKIWA
Life & Business Weather, Inc., Japan
2-6-4 Kanda-Jimbocho, Chiyoda-ku, Tokyo 101-0051, Japane-mail: tokiwa@lbw.jp

Abstract
Retailers in Japan are planning today, selling, ordering and stocking according to the daily weather
forecast, taking into consideration the relationships between weather and customers’ needs. Many retailers have succeeded at reducing losses and increasing their profit ratios. “Life-weather Merchandising(LMD)” is an application of biometeorological knowledge and techniques in human society for retailmarketing. In order to develop further solutions to the problems involved, this paper reviews the present
status of the science, based mainly on the observed facts in Japan.
Key words: biometeorology application, business biometeorology, consumers’ needs,
life-weather merchandising, retail markets

1. Introduction
Basically, all businesses are based on sales of commodities and services that meet the demands of theconsuming public. Ordinarily, if commodities notmatching the consuming public’s main needs are being sold, that business will not gain success easily.
However, even if commodities that match the needs
are arranged, the business will not necessarily advancesmoothly without losses. When the amount of the supply is greater than the amount of demand, it results inexcess stock and reduction in profitability. On theother hand, the business will fail to grow if it becomestoo cautious and refrains from obtaining sufficient
supply. What is necessary for more efficient management is to stock only the appropriate amount at theright time and to merchandise products that match
consumers’ major needs at a reasonable price. This
achieves stock optimization and high ratios of sales
and profits for the business. At present, it is more
important to analyze the consumer’s future needs correctly. World Meteorological Organization (WMO)(1990), Asakura et al. (1992) and Asakura (1995)
dealt with economic activities and weather, but nodetailed analyses were given due to a lack of data. In
the present paper, the present status of our business
related to life-weather merchandising is reviewed.

2. Methodology: Basic Logic
Climate repeats the same pattern every year fromwinter, the coldest season, to summer, the warmest
season. In particular, these seasons predominate in the
Global Environmental Research
11: 79-82 (2007)
printed in Japan

middle latitudes. The annual change patterns are notsmooth, however, showing irregular inter-diurnalchanges. In other words, day-to-day fluctuations are
not small in general. These affect the human bodyfrom the outside.
Within the human body, on the other hand, theconditions of physiological activities, such as blood
sugar levels, vary from moment to moment in accordance with the amount of time passing after meals, thecontent and amount of the meal, and the supply ofcalories. They differ according to age and sex. Living
body functions cannot be controlled by conscious
thought, but react mechanically under the influence ofthe environment, mainly weather.
In Fig. 1, relationships of weather conditions to thehuman body, acting through vital reactions, such as
blood pressure changes, nutritional balance, andhormonal balance, are shown for consideration of preconditions for application of biometeorology. They
result in changes in tastes of foods, falling sick anddeveloping mental conditions. Stress from meteorological conditions can be considered physiologicalstress, and cold or warm meals are introduced.
For consideration of comfortable temperatures,
Fig. 2 shows, relationships between air temperatureand death rate in the 1970s, 1980s and 1990s. Thisreveals following facts: in the 1990s, death rates
decreased to about 90% of those of the 1970s and1980s at every 5°C from 8°C to 33°C. Secondly, thedeath rate is at a minimum in the temperature rangesof 23°C-28°C and 28°C-33°C. These ranges can be
defined as the “Comfortable temperature range for thehuman body” (Japanese Journal of Biometeorology,©2007 AIRIES80

K. TOKIWA

1999). This figure was obtained by data from a part of
the Kinki District, Japan, for males.
For considering the basic logic of Life-merchandising, Fig. 3 illustrates the range of demand as
divided into two parts, demand for cold items and demand for hot items in the retail market. The comfortable zone in Fig. 3 is defined as the range of
22°C-25°C which corresponds to the lower part of therange in the 1990s shown in Fig. 2. If we consider itroughly, it should be 23°C-28°C. Above 29°C,
demand for cold items predominates, and below 15°C,
demand for hot items predominates. Between a rangeof 15°C and 29°C, physiological functions will fulfill
human bodies’ needs.
Figure 4 shows annual changes in basal metabolism and monthly air temperature (Shin-seiri-kagaku-

Falling
Falling sicksick

Blood pressure changes
Nutrition unbalanced

ChangeChange inin one’s
one’s
taste
taste forfor foodfood
Hormones
unbalanced

Change in Weather

ChangeChange one’s
one’s
mentalmental condition
condition

Vital Reaction

Fig. 1 Flow of processes from weather conditions to the human body through vital reactions.
Comfortable Temperature Range for
Human Body (Valid Point)

20,0001990
1980

Death Rate×100,000,000

18,0001970
16,00014,00012,00010,000Below 8℃

8-13℃

13-18℃

18-23℃

23-28℃

28-33℃

Above 33℃

Fig. 2 Relationships between air temperature and death rates in the Kinki District,Japan (males). (after Jpn. J. Biometeor. (1999))
＋40℃

％

Hot

5

5℃

4

22℃

Comfortable

Valid Point

Usually 36.5℃

2Basal metabolism

Temperature

1

Annual mean

0

15

-1
-2
-3

Cold

Demand for Hot Items
－40℃

25

-4
-5

J

Fig. 3

Schematic expression of ranges of demandfor hot and cold items.
(after Ishikawa and Tokiwa (2004))

Fig. 4

F

M

A

M

J

J

A

S

O

N

Annual change in basal metabolism and airtemperature.
(after Shin-seiri-kagaku-taikei, (1987))

D

Temperature(°C)

25℃

3Basal metabolism

Range of Demand

Demand for Cold Items

Life-weather Merchandisingtaikei, 1987). They show almost parallel fluctuations.
It can be concluded, therefore, that because air temperature relates basically to basal metabolism, we cantake air temperature as a basic factor in life-weather
merchandising.

3. Examples
3.1 Mechanism of demand
Estimation of the amount of supply from thebiometeorological point of view is crucial in foodsupermarket operations. Many housewives who cometo the supermarket to buy foods in the evening don’t
decide on the menu before they go shopping. Afterlooking at that day’s ingredients on the food counter,they start considering, “What does my family want to
eat this evening? What have my family eaten recently?
Which are the most delicious of today’s ingredients?”
Then they choose ingredients to their own liking.
Finally, they decide on that day’s supper menu. At thistime, how did they select these from the many commodities on the food counter? Why did they feel thosewere the most fascinating among the commodities
unconsciously? Are there any correlations between theneeds and demands in supermarkets and weather
conditions? A lot of supermarkets have grasped thatsales change in relation to temperature fluctuations.
However, there is no answer to the reason for appetites in the analytical results. There are only result ofsales amounts and the weather conditions at the
moment. The mechanisms of body function, including
food needs, react to weather changes as mentioned
above. For example, if one food looks fascinating, it isa suitable food for this person in supplementing an
insufficient nutrient. Changes in the nutritional balance of the human body are often brought on bychanges in weather and temperature.
3.2 Needs: Hot items and cold items
Generally speaking, the amount of waste at theretailers that remains unsold “abandonment loss”
accounts for about three percent of sales each year.
Until the “LMD” solution was brought into the retailmarket, to optimize the amount of an order, various
approaches were tried, but there was no establishedtechnique for predicting customers’ needs, so an
inductive means was relied upon; the repetition ofwork hypothesis. Or, based on a correlative analysis of
POS (Point of Sales) data and meteorological data, therelationship was derived between the quantity of commodities and temperature and made routine. For
example, it could be said that if the temperature
exceeded 25°C, sales of ice cream would increase.”
Regarding commodities such as box lunches, riceballs and bread, however, the relationship was notclear. Therefore it was not possible to create routines
which would reduce losses. We have proceeded with
our research to develop a technique for forecasting
more precisely customer needs from changes in81

weather.
We defined certain technical concepts, including“Hot Items,” “Cold Items,” “Rain Items,” “Sunny
Items” and “Abnormal-Weather Items.” “Hot Items”
are categories of commodities suitable for sellingwhen air temperatures are rising and consumers feel
hot or warm, such as ice cream, cold drinks, soba andso on, as shown in Table 1. On the other hand, “ColdItems” are categories suitable for selling when air
temperatures are falling and consumers feel cold orcool, such as stews, soups, oden and so on, as shownin Table 2. “Rain Items” are categories suitable forselling on rainy days, such as umbrellas, rubber boots,
miscellaneous goods for daily use, and so on. “Sunny
Items” are categories suitable for selling on fine days,
such as hats, rolls of film, sun oil and so on. “Abnormal-Weather Items” are categories suitable for sellingwhen severe storms are approaching or it is snowing
heavily, such as flashlight batteries, gloves, radios andso on. These are shown in Table 3.
Categorizing all commodities that are dealt with at
the store simplifies merchandising. If the commodities
suited to customer needs are always displayed in theshop, the abandonment loss can be reliably reduced.
Moreover, with regard to the relationship of sales
trends of specific commodities to temperature, byapplying the results of our research, a logical explanation can be obtained, so the person in charge of placing orders can make quick decisions, which is effective at decreasing the loss rate. Maunder (1986) has
dealt with business-weather relationships, but not withmerchandising information.
In a chapter, he discussed weather- and climatebased forecasts of economic activities, which take theassessment process one stage further, namely throughthe use of commodity-weighted weather and climate
information in formulating weather/climate-based forecasting models of economic activities and production.
In addition, the development and use of weather/climate-based economic forecasting models are
considered, including their real-time application tonational business activity indicators.
LMD, Life-weather merchandising, is a techniquefor managing orders, store operations and so on, bypredicting food preferences or needs by people, basedon biometeorology considerations and weather forecasts. By this method of merchandising, more detailedordering can be expected with higher accuracy, andestimation of customer numbers and human behavior
is also possible, so this merchandising information is
expected to be very useful in stocking raw materials,
product planning, and general distribution, For reducing abandonment losses at retailers, this approachshows hope and should be developed, too.
Gabe (1985) reported “how weather information isused in day-to-day decision-making,” based on the
past-30 years data on brewery in Japan. According to
the relationships between growth in beer consumption
and the weather index, compiled by recording daily

82

K. TOKIWA
Table 1

Examples of “Hot Items.”

Vegetables
Meat
Seafood
Processed Food
Delicatessen
Groceries
Clothing
Miscel-laneous

Table 2

Examples of “Cold Items.”

Vegetables
Meat
Seafood
Processed Food
Delicatessen
Groceries
Clothing
Miscel-laneous

Table 3

Lettuce, Cabbage, Tomatoes, Cucumbers, Onions, Green Peppers, Ginger, Broccoli, Bamboo Sprouts,
Celery, Burdock, Cauliflower, Garlic, Field Peas, Bean Sprouts, Green Beans, Leeks, Green Soybeans
Beef：Sliced, Fillet, Sirloin
Pork：Sliced, Loin, Fillet
Chicken：Sliced, All Parts, Grilled Chicken
Processed Meat：Ham
Raw fish, Whitefish, Eel, Short-necked Clams, Squid, Lobster, Mozuku
Milk, Soft Drinks, Tofu, Kimchi, Fried Noodles, Yogurt
Salad, Box Lunches, Rice Balls (Tuna, Plum Pickles), Chinese Food
Rice Crackers, Biscuits, Retort-packed Curry
T-shirts, Sleeveless Dresses, Swim wear, Tank Tops, Hats
Dehumidifiers, Insecticides, Sandals, Sunglasses, Goods for Camping,
UV Care Cosmetics

Carrots, Potatoes, Taro, Sweet Potatoes, Spinach, Corn, Shiitake Mushrooms, Chinese Cabbage, Asparagus,
Eggplant, Pumpkin, Okra, Japanese White Radishes
Beef：Chuck, Rib, Rump
Pork：Chuck, Rib, Spareribs
Chicken：Minced
Processed Meat：Meat Balls, Sausages
Raw Whitefish, Salmon, Yellowtail, Pond Smelt, Sea Urchins, Scallops, Octopus, Corbicula
Vegetable Drinks, Pickles, Boiled Fish Paste, Pudding, Cheese, BreadFried Food, Tempura, Seasoned Food, Shaomai
Instant Noodles, Chocolate, Stews, Soups
Cardigans, Sweaters, Coats, Gloves, Mittens, Mufflers
Pocket Body Warmers, Blankets, Kerosene

Examples of “Sunny Items,” “Rain Items” and “Abnormal-weather Items.”
Sunny Items

Laundry Detergent, Gardening Tools, Carpenters’ Tools,
Insecticide, Car Washing Goods, Film, Lottery, Sports
Equipment, Gasoline, Rent-A-Car, Sunglasses, UV Care
Cosmetics, Plastic Bottle Drinks, Hat

Rain Items

Sweet Potatoes, Pumpkins, Wraps, Dish-washing Liquid,
Umbrellas, Theatres, Rental Videos, Delivery Pizza, Game
Software, Magazines, Cakes, Socks, Rubber Boots, Medicine for
Colds

Abnormal-Weather Items
Kind of Abnormal Weather
Typhoons (Hurricanes )Heavy Snow
Droughts

maximum temperatures in 15 areas in Japan. Whenthe maximum temperature is 1°C above the normal ona fine day in July and August, beer sales that day
increase by 2,470,000 large-size bottles.
In such, beer consumption is closely related toweather. But, it is not easy to plan beer production
based on weather forecasts, because beer cannot be
stocked for a long time. It was said that, in theplanning process, we should produce a less sensitive
product to weather and climate to minimize the risk.
Gabe (1985) noted also the demand for air conditioners affected by the weather in Japan. The intense
summer heat in 1978 was responsible for the sale of
3,150,000 units, 450,000 more than 2,700,000 units
anticipated.

4. Summary
Previously there has been a lot of research on
changes in health conditions due to changes inweather, but there are few examples of research referring to food preference changes or changes corresponding to seasonal and daily fluctuations in details

Items with Rising Purchase Indices
Gloves, Flashlight Batteries, Ropes, Timber
Rubber boots, Shovels
Wraps, Paper Diapers, Paper Dishesof units of nutrients. Further development is needed
urgently.
References
Asakura, T., K. Akatsu and K. Okuyama (1992) Economic
activities and weather, Asakura-shoten, Tokyo. (in Japanese)
Asakura, T. (1995) Economic activities and weather information. Kisho-Handbook, Asakura-shoten, Tokyo, 506-519. (inJapanese)
Gabe, M. (1985) Weather information – valuable economic toolin an era of low growth –. Tokyo Newsletter (August), Tokyo
Corporate Communications Office, Mitsubishi Corporation,
1-4.
Ishikawa, K. and K. Tokiwa (2004) Introduction to merchandising. Akinai-Gyokai, Tokyo. (in Japanese)
Japanese Journal of Biometeorology (1999) 36(3).
Maunder, W.J. (1986) The uncertainty business. Risks andopportunities in weather and climate. Methuen, London.
Shin-seiri-kagaku-taikei (1987) Igakushyoin, Tokyo. (in Japanese)
WMO (1990) Economic and social benefits of meteorologicaland hydrological services. World Meteorological Organization, Geneve.
(Received 13 April 2007, Accepted 27 April 2007)