Case Study
Menu Engineering
Beirut, LebanonPricing Strategy, Cost Analysis
Our client, Farid Mattar, is a seasoned culinary business consultant with years of experience. He was approached by an established restaurant/bar in town, looking to launch a new brand and rejuvenate their existing one.
Audit
The pre-setup phase was pivotal in defining the client's needs. Collaboration with Farid on this project required a well-defined scope to ensure synergy without overcrowding. After several sessions and workshops, it became evident that Farid sought assistance primarily in cost metrics, pricing strategy, within the context of menu engineering advisory services. The primary workshop objective was to instill greater confidence in the transition and adopt a contemporary approach to cost and pricing models.
Setup
The setup phase commenced with defining the scope of work and addressing potentially sensitive areas of engagement. It was essential to establish a clear decision-making process. Based on the audit findings, Cousins assigned a dedicated partner to oversee the project and assembled a team of experts from their network, ensuring a customized approach throughout.
Partner
Victor Ayache
Managing Partner, Consultant at Cousins
Team
Gibran Assad (Consultant)
Joelle Rizkallah (Analyst, Junior)
Workshop
Given the specificity of COUSINS' scope and the need for seamless integration with other project teams, we initiated conversations with stakeholders and teams.
01/ Qualitative Research
Through stakeholder interviews, the analysis aimed to assess the current situation, future direction, and any existing business strategies or efforts by peer consultants. The objective was to gain insights into the presence of a clear business strategy guiding ideal gross food margins and other performance targets and assumptions.
02/ (Unstructured) Data Collection & Analysis
The restaurant, with over five years of transaction history and available data, necessitated a parallel qualitative research effort. Cousins initiated a discovery phase and conducted desktop research, involving the collection and analysis of unstructured data, such as administrative documents, invoices, texts, emails, P&Ls, and even social media and customer reviews. The data analysis involved extracting essential metrics, values, and knowledge tables/graphs.
03/ The Critical Tasks Approach
Given the constraints of limited digitization in administrative and procurement operations, as well as time and resource limitations, prioritization became crucial. Initially, a project plan was formulated, with a strong emphasis on critical tasks such as cost analysis and POS sales data. Subsequently, we introduced a Potential-Profitability Matrix to assess existing portfolio items, deciding whether to invest in, discontinue, or develop them. These two data collection strategies streamlined the process significantly, allowing us to concentrate on just two data categories and a reduced number of portfolio items.
04/ Cost Analysis and Margins
By categorizing and analyzing purchasing and procurement data, we obtained accurate cost data for all ingredients used in previous menu items. This data allowed us to calculate future costs for new menu options proposed by the culinary consultant. Accurate cost data also enabled us to calculate margins and benchmark them against targets outlined in the overall business strategy.
05/ Potential-Profitability Matrix
The Potential-Profitability (PP) Matrix, a variation inspired by the Boston Consulting Group’s (BCG) Growth-Share Matrix, was specifically crafted by COUSINS for situations characterized by strategy shifts, rebranding, market changes, and similar scenarios. These circumstances are more common in micro and small organizations at the inception of their brand lifecycle, a recurring theme at COUSINS. The PP matrix integrates weighted variables, options, and scenarios from the overall business strategy and contributions from collaborators. Instead of collecting data indiscriminately, our approach now focuses solely on data that aligns with the intended outcomes of the PP Matrix.
06/ Benchmarks, Deviation, and Elasticity
Having clarified costs and portfolio items, we initiated market research to acquire pricing knowledge and conduct benchmarking. Three key aspects were monitored: Standard Deviation analysis of different pricing, Price Elasticity of Demand (PED), and the correlative relationship between the two. These benchmarks provided the client with the information needed to approach pricing strategically.
07/ Potential of Dynamic Pricing Strategy
The strategy workshop, in general, and the data analysis process, established a digital infrastructure for the client to monitor and adjust prices based on feedback loops. This transitioned them from fixed pricing to a dynamic pricing strategy responsive to market inputs and data collected.