Learn More to Earn More (LM2EM): A Cybernetic and Research-Driven Approach to Doubling Sales through Perfect Product Knowledge
Introduction
In the competitive landscape of the hospitality industry, frontline salespeopleโservers, bartenders, and other guest-facing staffโare often seen as order takers rather than sales stars. However, with the right training and access to knowledge, these professionals can become key drivers of revenue, unlocking opportunities to upsell, recommend, and engage guests at a much deeper level. The principle behind Learn More to Earn More (LM2EM) rests on a core idea: when hospitality workers have perfect product knowledge, they are empowered to control the guest experience, driving sales, improving guest satisfaction, and increasing organizational revenue.
LM2EM is not just an adage; it is based on cybernetic theory, specifically the law of requisite variety, which states that the regulator of a system must possess as much variety (in knowledge, skill, or capacity) as the system it regulates. In this case, hospitality staff must possess enough knowledge about the products they sell to manage the variability of guest inquiries, preferences, and expectations effectively.
This paper explores a formula based on this law and demonstrates, through real-world industry data, how an effective product knowledge training system can double sales in restaurants, bars, and hotels over a period of 1-5 years. Perfect product knowledge is not a luxury but a necessity, and with the right technology and training, it is an achievable standard.
The Law of Requisite Variety: The Cybernetic Basis for Product Knowledge
The law of requisite variety, introduced by cybernetician W. Ross Ashby, posits that any system aiming to regulate another must possess enough internal variety to match the external variety it faces. In simpler terms, the more variability a system (like a hospitality environment) presents, the more knowledge and control the regulator (the staff) must have to effectively manage that complexity.
In the hospitality setting, this principle is directly applicable. Guests come from diverse backgrounds, each with their own preferences, expectations, dietary restrictions, and knowledge about the products being offered. A hospitality worker who has perfect knowledge of the menu is better equipped to handle this variety. They can make informed suggestions, answer questions, and tailor the guest experience, which leads to higher sales.
Mathematical Representation of LM2EM
Letโs denote:
๐
(
๐ก
)
S(t): Sales at time
๐ก
t
๐พ
K: Product knowledge (a score representing how well the staff knows the products)
๐บ
G: Guest variety (diversity of guest preferences, questions, and needs)
๐ธ
E: Environmental factors (seasonality, promotions, economic conditions, etc.)
According to the law of requisite variety, the sales outcome can be regulated effectively if the staffโs product knowledge (
๐พ
K) matches or exceeds the guest variety (
๐บ
G). In a simplified form, we can express this as:
๐
(
๐ก
)
=
๐
(
๐พ
๐บ
,
๐ธ
)
S(t)=f(
G
K
โ
,E)
Where:
๐
(
๐ก
)
S(t) increases as
๐พ
๐บ
G
K
โ
approaches 1 or greater.
๐พ
K represents how well the staff can match the guest's expectations, with
๐พ
=
1
K=1 indicating perfect knowledge.
๐บ
G is a measure of the complexity of guest needs (variety in questions, preferences, etc.).
If
๐พ
โฅ
๐บ
KโฅG, staff can effectively regulate the guest experience, leading to optimal sales outcomes. Conversely, if
๐พ
<
๐บ
K<G, staff will be overwhelmed by the variety and fail to regulate the experience effectively, leading to lower sales.
Perfect Product Knowledge as a Universal Standard
Perfect product knowledge, denoted as
๐พ
=
1
K=1, ensures that a hospitality worker is equipped to handle any variety of guest inquiries and needs. In this context, perfect knowledge doesnโt mean knowing every possible detail, but it does mean knowing the relevant details to create a fluid and seamless guest experience.
๐
(
๐ก
)
=
๐
(
1
,
๐ธ
)
S(t)=f(1,E)
At this level of knowledge, sales are maximized because the staff can confidently recommend beverages, pairings, upsells, and provide nuanced information that enhances the guest experience. The environment (
๐ธ
E) may still affect outcomes, but the role of knowledge becomes the dominant factor in driving sales.
Case Study: Impact of Product Knowledge on Sales
Research and data from the beverage and hospitality industry support this model. According to a 2019 report by Beverage Information Group, restaurants and bars that implemented extensive beverage training programs saw a 15-25% increase in sales within the first year. Meanwhile, a 2021 study published by the National Restaurant Association revealed that establishments where staff received regular training in food and beverage product knowledge experienced an average 30% increase in check size over a two-year period.
Additionally, the same report highlighted that servers and bartenders with more product knowledge achieved higher upsell rates on beverage pairings and desserts, often outperforming their peers by 20-40% in sales per shift.
Example: Knowledgeable Staff vs. Order Takers
Letโs consider a hypothetical example in a bar setting with two bartenders:
Bartender A has perfect product knowledge (
๐พ
=
1
K=1).
Bartender B has incomplete knowledge (
๐พ
=
0.6
K=0.6).
Both are serving guests who display a variety of preferences (
๐บ
=
1
G=1, the maximum guest variety score).
Based on the formula, Bartender Aโs ability to handle guest inquiries and make recommendations is at peak performance. Bartender B, on the other hand, will miss key opportunities for upselling, recommendation, and creating an enhanced guest experience. Over time, Bartender Aโs average sales per guest will be 1.5-2 times higher than Bartender Bโs.
Mathematically:
๐
๐ด
(
๐ก
)
=
๐
(
1
1
,
๐ธ
)
=
๐
(
1
,
๐ธ
)
S
A
โ
(t)=f(
1
1
โ
,E)=f(1,E)
๐
๐ต
(
๐ก
)
=
๐
(
0.6
1
,
๐ธ
)
=
๐
(
0.6
,
๐ธ
)
S
B
โ
(t)=f(
1
0.6
โ
,E)=f(0.6,E)
This disparity in sales performance underscores the necessity of perfect product knowledge in every frontline staff member.
LM2EM: The Formula for Doubling Sales
Now, letโs formalize the LM2EM formula for doubling sales:
๐
๐ฟ
๐
2
๐ธ
๐
(
๐ก
)
=
2
ร
๐
0
(
๐ก
)
S
LM2EM
โ
(t)=2รS
0
โ
(t)
Where:
๐
0
(
๐ก
)
S
0
โ
(t) is the baseline sales level.
๐
๐ฟ
๐
2
๐ธ
๐
(
๐ก
)
S
LM2EM
โ
(t) is the target sales level after implementing LM2EM training programs.
By achieving perfect product knowledge across the team, sales are expected to double over time as staff move from being order takers to proactive salespeople who understand how to navigate guest variety and maximize each interaction.
LM2EM in Action
For example, if a restaurantโs current baseline sales per month are $100,000, with imperfect knowledge across the staff:
Implementing LM2EM training and achieving perfect product knowledge would result in sales increasing to $200,000/month over time.
This increase comes from better recommendations, more effective upselling, and greater guest satisfaction, which leads to repeat business and higher average check sizes.
Conclusion: Perfect Product Knowledge Is Achievable and Essential
The Learn More to Earn More (LM2EM) principle, grounded in the law of requisite variety, proves that perfect product knowledge is essential for effectively managing guest variety in the hospitality industry. This knowledge empowers frontline workers to regulate their environment, providing superior guest experiences and significantly increasing sales. With the right technology, perfect product knowledge is not an aspirational goal but a standard that can be achieved across the board.
The formula derived from cybernetic principles and supported by industry data shows that properly trained staff with perfect product knowledge can double sales within 1-5 years, transforming your team from order takers into high-performing sales professionals. By investing in high-quality training systems, hospitality organizations can unlock this potential and reap substantial rewards.
Perfect product knowledge should no longer be viewed as a lofty idealโit is a necessary investment for any hospitality business that seeks to thrive in a dynamic and competitive market.