This article assumes a familiarity with Wardley Mapping. This mapping technique is a valuable way of understanding the landscape of an industry, organisation or situation to allow effective movement and response. The outcomes of this article formed the core of my talk at Agile Scotland in March 2019.
Approximately a third of people, when using a calorie counting website under-reported consumption. Whilst this is statistically an improvement over verbal or written food journals, it is still a significant number of people who will be unwittingly disappointed in their results. Most weight-loss approaches seem to treat all reporting as equal. A Big Mac and a home cooked meal are the considered the same, and these two items are normalised in the data as underreported.
Why are these two items normalized? We know exactly how many calories there are in a Big Mac, there are 563. This is not necessarily the case for a home cooked meal. Why are diets with primarily known calorific foods and diets dependent on home cooking treated equally?
Iโve been working with Wardley Maps for digital transformation, but one of the core points struck me regarding my weight. Big Macs are a commodity. They are the same everywhere with a fixed value. Can we then use Wardley Maps to get a more granular understanding of why reporting may be inaccurate?
Understanding Wardley Maps:
Wardley Maps grew out of a desire to understand the landscape of a business to more properly understand the possible and likely movement of the players. Simon Wardley likens strategy without a map to playing Chess without being able to see the board.
Wardley maps operate with a Y axis showing the value chain and the higher on the map something is, the closer to the customer. The X axis shows from left to right the move to commoditisation from genesis.
For far more information, see Wardley Mapping
Fast food is a Commodity:
This represents scale and volume operations of production, the highly standardised, the defined, the fixed, the undifferentiated, the fit for a specific known purpose and repetition, repetition and more repetition. Our focus is on ruthless removal of deviation, on industrialisation, and operational efficiency. With time we become habituated to the act, it is increasingly less visible and we often forget itโs even there. [Wardley Mapping]
It was this thought, that fast food is a commoditised item, that a Big Mac is the same whichever store you buy it in that got me interested in how Wardley maps may apply.
Calorie counting apps and websites link to a series of official and crowd sourced data sources relating to the calories in foods. For fast food or chain restaurants and cafes these figures are well understood and reasonably dependable. Starbucks use the same milk, cup sizes, machinery and coffee in their stores. McDonalds has the same approach for a big mac in every country. (to the extend the Big Mac Index has existed for more than thirty years to help understand purchasing parity).
If you ate a primarily fast food based diet, and were honest in your reporting, youโd find it fairly easy to lose weight (ignoring the health issues with eating a fast food only diet). Indeed, many weight-loss approaches like Weight Watchers, with their controlled calorie ready-meals follow this approach.
However, people are poor at honestly reporting portion sizes. When related to fast food and chain food, it is easy to ignore the extra shot of syrup in your coffee, choose the medium fries rather than large as they were first in your search or otherwise misrepresent, but that inaccuracy is an inaccuracy of unwillingness to enter the data, rather than unavailability or incorrect data.
Fast food is a commodity, it is identical across different locations, and can be dependably described if you choose to.
Hypothesis: By recording the exact item and portion size for commoditised food with full honesty, speed of weight-loss will be increased.
Restaurant meals are Products:
This represent the increasingly common, the manufactured through a repeatable process, the more defined, the better understood. Change becomes slower here. Whilst there exists differentiation particularly in the early stages there is increasing stability and sameness. You will often see many of the same product. Our focus is on refining and improving.[Wardley Mapping]
Restaurants are a challenge for weight-loss, for a number of reasons, but the most challenging is that there is no way to know the exact ingredients used in a dish (or that they will be exactly the same each time). The differentiation exists, though it is relatively stable. A Spaghetti Carbonara in one Italian restaurant will be similar to the carbonara in another (assuming neither use cream and therefore are not carbonara). There are differences however.
In order to manage these differences, Iโve taken the estimation of dieticians as a baseline for error. Using the map, we know we are looking at something sitting between a fast food meals accurate calorie count, and an estimated home cooked mealโs 50% margin of error. In a study, unlike the untrained, dieticians under-reported their calorie intake by 20%. This seemed a reasonable starting point for these meals and, based on the hypothesis, could be amended if progress was stalling.
By using a similar โchainโ meal as a baseline from the calorie app, and then applying a 20% contingency to the portion size, we can align to a more likely โlargerโ calorie count without overestimating. It is, of course, still vital to be honest on the sundries eaten with the main meal, such as bread and butter.
Hypothesis: By finding a comparable commodity or home cooked item to the meal consumed and adding a 20% increase in portion size, speed of weight-loss will be increased.
Home-cooked meals are Custom Built:
This represents the very uncommon and that which we are still learning about. It is individually made and tailored for a specific environment. It is bespoke. It frequently changes. It is an artisan skill. You wouldnโt expect to see two of these that are the same. Our focus is on learning and our craft.[Wardley Mapping]
When thinking about food, weight-loss and mapping, I thought a lot about how I prepare my meals at home. Iโm not a scientific cook, I operate more by instinct than recipe and add ingredients as I see fit. There is little replication between my meals.
As I started to map this space out, it became clear there are two paths to the same outcome. I could make a burger by meticulously measuring everything, knowing exactly what was going into it, step by step. This would easily allow for translation to accurate information on the total calories. In this case, if I am taking known ingredients, and measuring them accurately, then I can be safe in adding the exact calories to the food log.
Or, I could cook as I would normally, putting ingredients in as I felt were necessary. I would finish with a rough idea of what was in there and in what portions, but accuracy would be missing. When looking into the research, people are very poor at estimation, and underestimate by approximately 50% when keeping a journal.
Hypothesis (1): By accurately measuring and recording every ingredient going into a custom meal, speed of weight-loss will be increased.
Hypothesis (2): By adding a 50% contingency to my estimated calorie count for an unmeasured meal, speed of weight-loss will be increased.
Application of the theory:
From the 19th of January, I started applying the above approach to my personal weight-loss journey. Moving from simply recording the food as I ate it in MyFitnessPal to amending the portion sizes or choices based on where in the map it would fall. Home-cooked meals where I was cautious and measured everything went in accurately, trusting to my diligence. Last minute meals which were estimated, had a 50% contingency added. Fast food, when eaten, was put in exactly as eaten and for restaurants, the closest parallel was found and a 20% contingency added.
Hypothesis: By accurately measuring and recording every ingredient going into a custom meal, speed of weight-loss will be increased.
Hypothesis: By adding a 50% contingency to my estimated calorie count for an unmeasured meal, speed of weight-loss will be increased.
Hypothesis: By finding a comparable commodity or home cooked item to the meal consumed and adding a 20% increase in portion size, speed of weight-loss will be increased.
Hypothesis: By recording the exact item and portion size for commoditised food with full honesty, speed of weight-loss will be increased.
These actions resulted in an measurable increase in the speed of my weight-loss, moving from 0.4kgs to 1.0kgs per week. This occurred during a period (post-8th February) where I finished my 100 days dry challenge and started drinking alcohol again with some regularity. Gym attendance was static, or slightly reduced than in the earlier measured period.
Whilst it would be easy to dismiss these results as โthe contingencies you were adding just meant you were eating more below your TDEE(Total Daily Engergy Expenditure) than previouslyโ, is missing the point. Any weight-loss is driven by reducing your consumption below your expenditure, and this is a mechanism for applying that effectively.
By mapping the types of consumption, and understanding the accuracy of their estimation, you gain greater understanding and control and can apply different approaches to the different contexts to achieve the same result.
Additionally, note that the contingency applied was variable, applied at a different level depending on the mapping space and only applied to two of the four hypothesis rather than being a blanket โincrease by x%โ all entries.
One significant challenge in weight-loss is people are very poor at estimating how much they eat, as well as being poor at honestly reporting portion sizes. By creating a deeper and more varied understanding around this, in my case this has increased my weight-loss whilst also not impacting the way I was eating during the whole experimental period. The reasons behind underreported fast food, and home cooked meals are different, and understanding the context assists in action.
Note: This is anecdotal as a weight-loss tool. It is a single use of Wardley mapping to assist in weight-loss. The application of mapping to assist in gathering and understanding context is well supported.
