Name: Sales Forecasting in Excel for Management Consultants
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Créé parAsen Gyczew

Dernière mise à jour : 05/2026

Anglais

Ce que vous apprendrez

Identify main drivers for specific business models
Translate the drivers into a basic sales forecast models
Create the sales forecast models in Excel
Create simple simulations & sensitivity analysis

Contenu du cours

5 sections • 70 sessions • 3 h 31 min de durée totale

Introduction2:06
We begin with a little intro to the course as well as some general info on how the course is organized.
A little bit about me1:47
A few words about your humble teacher
How the course is organized1:41
Let's see how the course is organized.
How to deal with Blurry image2:04
Here I will show you what to do if a blurry image appears
How to reach additional resources1:06
Here I will show you how to find additional resources attached to the course like Excel files, presentations, links, etc.

Basics of Sales Forecasting – Introduction1:13
In sales forecasting, you can use different approaches. We will discuss them in this section and I will give you some tips on which one you should use in a specific situation.
Different approaches to sales forecasting3:18
You can use a different approach to sales forecasting in 3 main areas
Which side of the market drives the sales?
What is the starting point
What you forecast?
Data Base for Sales forecasting2:25
You can base your forecast on 3 main groups of data
Historical Data
Future Data
Capacity data
What you have to account for in sales forecasting4:19
There are plenty of things you may have to consider when forecasting sales. Below some of them
Seasonality effect, Demographics & other structural changes
Growth or contraction of your markets, Growth or contraction of your sales channels, Growth/contraction of related markets
One-offs, Cycle of sales
Different level of promotions/marketing support
Sales elasticity
Change in customer behavior
Bundling of products
Stock / Inventory level

Useful Tools for Sales Forecasting – Introduction1:14
In sales forecasting, you can use different tools. We will discuss them in this section. We will talk about disaggregation, simulations, sensitivity analysis, and random variables. We will later on need those concepts to solve case studies
Scenario analysis – Introduction3:21
The future is pretty difficult to figure out. You don’t know what will happen. In those cases, it is a good idea to consider a few different scenarios. One of the ways to face it is via scenario analysis. I will show you how to use it in practice
Which price formula is the best for my profits – Introduction2:47
Price formula in B2B services can drastically impact the margins and net profit. In this lecture, we will go through a case that will show you how to approach the analysis of the price formula with uncertainty on the scenario that will happen
Which price formula is the best for my profits – Solution – Times & Materials an3:47
In this lecture, I will show you how to solve the case shown in the previous lectures
Which price formula is the best for my profits – Solution – Mixed Options2:37
In this lecture, I will show you how to solve the case shown in the previous lectures
Simulation analysis – Introduction3:10
In some cases, you want to check all potential scenarios and not just the selected number of them. For that, you should use the simulation analysis. In the next few lectures, we will discuss this method.
What will be the effect of the price increase – Introduction2:09
The future is pretty difficult to figure out. You can use scenario analysis or you check ALL the potential options and see which is optimal. I will talk about this technique in this lecture and when to apply it. The impact of the price change on your profit will depend on a few factors. I will discuss in this lecture what you should take into account and how to calculate it.
What will be the effect of the price increase – Solution – Impact on coffee only4:01
In this lecture, I will show you how to solve the case shown in the previous lectures
What will be the effect of the price increase – Solution – Impact on coffee and2:34
In this lecture, I will show you how to solve the case shown in the previous lectures
Juice Producer – Simulation – Introduction4:28
In this case, we will do the simulation of the whole logistics system and show you how to choose from many options
Juice Producer – Simulation – Tips how to do it8:23
Here we will give you tips on how to calculate the cost of the whole system and how to prepare for the simulation
Juice Producer – Simulation – Solution8:33
We present here the final solution to the case. We show how to do the simulation of logistic costs for 8 different options in 5 minutes
Decomposition of effects analysis – Introduction2:48
Decomposition analysis shows you what are the components, driving forces behind certain phenomena. I will talk about this technique in this lecture and when to apply it.
LFL analysis – Introduction2:36
I will show you here how to analyze Like for Like sales (Same-store sales - LFL, L4L)
LFL analysis – Solution – Part 13:06
In this lecture, I will show you how to solve the case shown in the previous lectures
LFL analysis – Solution – Part 22:58
In this lecture, I will show you how to solve the case shown in the previous lectures
LFL analysis – Solution – Power Point2:14
In this lecture, I will show you how to solve the case shown in the previous lectures
Sensitivity analysis – Introduction2:02
Once you come up with an optimal solution you want to see how sensitive it is too small changes in underlying assumptions. The solution can be pretty stable…. … or the contrary very volatile. The sensitivity analysis helps you check that. I will talk about this technique in this lecture and when to apply it
Sensitivity analysis – Solution In Excel5:43
In this lecture, I will show the solution to the case study introduced in the previous lectures
Sensitivity analysis – Solution in Power Point1:18
In this lecture, I will show the solution to the case study introduced in the previous lectures
Simple Regression Model – Introduction2:23
A regression model is a powerful tool you can use to analyze data, predict things, and find relations between different phenomena. I will show you how to use it in Excel.
Simple Regression Model – Example6:03
A regression model is a powerful tool you can use to analyze data, predict things, and find relations between different phenomena. I will show you how to use it in Excel.
Random Variables3:30
In many cases the outcome of certain phenomena is unknown. In such situations, we need Random Variables.
Random variables at the end will produce a specific outcome but we don’t know exactly what it will be.
Random Variable is what you will find behind the closed doors. Once you open the door you will know for sure but before that, there are only some potential results, nothing certain.
Random Variables in Excel – Introduction5:09
In order to be able to recreate the game in Excel, we will have to reframe it. I will show you how to do it and how later on to use it for modeling in Excel.
Random Variables in Excel – Examples3:51
In order to be able to recreate the game in Excel, we will have to reframe it. I will show you how to do it and how later on to use it for modeling in Excel.

Case studies – Overview1:33
Here we will build sales forecasting models in Excel for specific case studies.
Plywood sales forecasting – Case Introduction1:13
Let’s imagine that you have to forecast the sales of 1 factory of plywood. We will see how it can be done given that the main driving side will be the supply side – production capacity.
Plywood sales forecasting – Drivers2:42
In this lecture, we will be solving the previously introduced case study.
Plywood sales forecasting – Engine4:03
In this lecture, we will be solving the previously introduced case study.
Plywood sales forecasting – Simulations3:31
In this lecture, we will be solving the previously introduced case study.
Book publisher – Case Introduction1:07
Let’s imagine that you have to forecast the sales of a book publisher. His sales are driven by novelties and the sales of already existing content.
Book publisher – Drivers4:09
In this lecture, we will be solving the previously introduced case study.
Book publisher – Seasonality & Aging4:46
In this lecture, we will be solving the previously introduced case study.
Book publisher – New Books Modeling4:17
In this lecture, we will be solving the previously introduced case study.
Book publisher – Old Books Modeling3:15
In this lecture, we will be solving the previously introduced case study.
Book publisher – Summary1:46
In this lecture, we will be solving the previously introduced case study.
Cosmetics producer – Case Introduction1:14
Now let’s try to build a sales forecast for a cosmetics producer selling via a retail chain. Here we will have to take into account the chain size and growth of the market for every category.
Cosmetics producer – Drivers1:49
In this lecture, we will be solving the previously introduced case study.
Cosmetics producer – Data Available4:08
In this lecture, we will be solving the previously introduced case study.
Cosmetics producer – Next Year Forecast2:28
In this lecture, we will be solving the previously introduced case study.
Cosmetics producer – Changes3:49
In this lecture, we will be solving the previously introduced case study.
Retailer new & old stores – Case Introduction1:29
Let’s imagine that you have to forecast the sales of a retail chain. They have 10 old stores and plan to open another 5. Use the data from the previous year.
Retailer new & old stores – Drivers2:26
We will look at the drivers of sales for a retailer. For simplicity, let's assume that we will be estimating the sales of a chain consisting of 2 stores.
Retailer new & old stores – Data Available3:51
In this lecture, we will be solving the previously introduced case study.
Retailer new & old stores – New Stores3:20
In this lecture, we will be solving the previously introduced case study.
Retailer new & old stores – Old stores3:26
In this lecture, we will be solving the previously introduced case study.
Retailer new & old stores – Change2:31
In this lecture, we will be solving the previously introduced case study.
Consulting Firm Sales Forecast – Case Introduction1:16
Let’s try to predict the sales level for a consulting firm. This is difficult due to the high unpredictability of the projects. We will try to account for it in our analysis.
Consulting Firm Sales Forecast – Drivers2:00
On the face of it is easy to predict sales in consulting as there are only 3 drivers
# of consultants
Duration of the projects in months
Price per consultant per month
Consulting Firm Sales Forecast – Data Available3:37
In this lecture, we will be solving the previously introduced case study.
Consulting Firm Sales Forecast – Maximal and Expected Sales4:27
In this lecture, we will be solving the previously introduced case study.
Consulting Firm Sales Forecast – Sales by Type3:49
In this lecture, we will be solving the previously introduced case study.
Consulting Firm Sales Forecast – Random Delay in the Start1:57
In this lecture, we will be solving the previously introduced case study.
Drones Sales Forecasting – Case Introduction1:30
Now let’s try to estimate the sales of a drone producer. He is selling via 2 channels: Amazon and 3rd party retail chain.
Drones Sales Forecasting – Drivers1:18
Let’s see how we can estimate the sales of the drone producer in one channel (Amazon or Retail Chains)
Drones Sales Forecasting – Data Available4:01
In this lecture, we will be solving the previously introduced case study.
Drones Sales Forecasting – Modeling Sales via Amazon5:00
In this lecture, we will be solving the previously introduced case study.
Drones Sales Forecasting – Modeling Sales via Retail Chain3:20
In this lecture, we will be solving the previously introduced case study.
Drones Sales Forecasting – Total Sales2:10
In this lecture, we will be solving the previously introduced case study.
Drones Sales Forecasting – How to create the simulation1:53
In this lecture, we will be solving the previously introduced case study.

Prérequis

Basic or intermediate Excel
Basic knowledge of economics
Basic Math

Description

What is the aim of this course?

During many consulting projects, you may be asked to forecast the sales of the firm or check sales forecast models done by the customer. Sales forecasting requires a specific approach to data and also a lot of creativity, thinking outside the box, to address the issue of insufficient data and the changing environment. In this course, I will teach you how to do fast and efficiently basic sales forecast models in Excel. We will create relatively simple sales forecasts. Nevertheless, they will significantly help your customer define strategy, and decide whether he should open a new factory, enter a new field, or buy a business. We will NOT get into complicated models, or forecasts as in most cases you will have neither time nor data to do them. It would also require a wider knowledge of mathematics, statistics, econometrics, and the usage of more advanced tools than Excel. The things you will learn in this course will be sufficient in 70% of the cases and can be done with the knowledge of basic Math. Such basic sales forecasts are especially important during Strategy projects, M&A projects, and business development projects. In such projects, you want to get fast rough sales forecasts using simple methods. A similar approach as we will show in this course can be used as the starting point for budgeting models.

In the course, you will learn the following things:

The essential concepts in sales forecasting and the main tools that you may need.
How to forecast sales in Excel using simple methods fast and efficiently
What drivers of sales you should take into account for selected industries?
We will look at different case studies to see how you can move from drivers to a working model in Excel

This course is based on my 15 years of experience as a consultant in top consulting firms and as a Board Member responsible for strategy, performance improvement, and turn-arounds in the biggest firms from Retail, FMCG, SMG, B2B, and services sectors that I worked for. I have carried out or supervised over 90 different performance improvement projects in different industries that generated a total of 2 billion in additional EBITDA. On the basis of what you will find in this course, I have trained in person over 100 consultants, business analysts, and managers who now are Partners in PE and VC funds, Investment Directors and Business Analysts in PE and VC, Operational Directors, COO, CRO, CEO, Directors in Consulting Companies, Board Members, etc. On top of that my courses on Udemy were already taken by more than 300 000 students including people working in McKinsey, EY, Walmart, Booz Allen Hamilton, Adidas, Naspers, Alvarez & Marsal, PwC, Dell, Walgreens, Orange, and many others.

I teach through case studies, so you will have a lot of lectures showing examples of analyses, and tools that we use. For every lecture, you will find attached (in additional resources) the Excels as well as additional presentations, and materials shown in the lectures. Therefore, as a part of this course, you will also get a library of ready-made analyses that can, with certain modifications, be applied by you or your team in your work.

Why have I decided to create this course?

Most management consultants avoid the topic of sales forecasting due to insufficient knowledge of mathematics, probability, and statistics. To make advanced models you need those things. However, in most cases, a simple approach using Excel can produce pretty good results. For that, you don’t have to spend 5 years studying math.

Therefore, I have decided to create this course that will help students understand or refresh the main skills and tools that they need during consulting projects to do basic sales forecasting. The course will give you the knowledge and insight into real-life case studies that will make your life during a consulting project much easier. Thanks to this course, you will know what and how to do during the consulting project, when you will be asked to forecast sales. You will see how to identify what drivers are important in specific businesses and how to use them to build simple models in Excel.

To sum it up, I believe that if you want to become a world-class Management Consultant or Business Analyst you have to have a pretty decent understanding of how to do essential sales forecasting. That is why, I highly recommend this course to Management Consultants and Business Analysts, especially those that did not finish, mathematics and econometrics. The course will help you become pretty good at doing simple sales forecasting models in Excel on the level of McKinsey, BCG, Bain, and other top consulting firms.

In what way will you benefit from this course?

The course is a practical, step-by-step guide loaded with tons of analyses, tricks, and hints that will significantly improve the speed with which you understand, and analyze businesses. There is little theory – mainly examples, a lot of tips from my own experience as well as other notable examples worth mentioning. Our intention is that thanks to the course you will learn:

The essential concepts in sales forecasting and the main tools that you may need.
How to forecast sales in Excel using simple methods fast and efficiently
What drivers of sales you should take into account for selected industries

You can also ask me any question either through the discussion field or by messaging me directly.

How the course is organized?

The course is divided currently into 3 sections. Currently, you will find the following sections:

Introduction. We begin with a little intro to the course as well as some general info on how the course is organized
Basics of Sales Forecasting. In sales forecasting, you can use different approaches. We will discuss them in this section and I will give you some tips on which one you should use in a specific situation.
Useful Tools for Sales Forecasting. In sales forecasting, you can use different tools. We will discuss them in this section. We will talk about disaggregation, simulations, sensitivity analysis, and random variables. We will, later on, need those concepts to solve case studies
Case Studies in Sales Forecasting. Finally, in the 4th section, we will move to case studies devoted to specific industries. We will look at 6 case studies and I will show you how to move from general drivers for the business to a model in Excel that you can use

You will be able also to download many additional resources

1. Useful frameworks and techniques

2. Analyses shown in the course

3. Additional resources

4. Links to additional presentations, articles, and movies

5. Links to books worth reading

At the end of my course, students will be able to…

Identify the main drivers for a specific business
Translate the drivers into basic sales forecast models
Create the sales forecast models in Excel
Create simple simulations & sensitivity analysis

Who should take this course? Who should not?

Management Consultants and Business Analysts
Financial Controllers
Investment Analysts
Startup Founders
Project Managers
Managers responsible for Acquisitions and Mergers

What will students need to know or do before starting this course?

Basic or intermediate Excel
Basic knowledge of economics
Basic or intermediate knowledge of finance & accounting

À qui ce cours s'adresse-t-il ?

Management Consultants
Business Analysts
Financial Controllers
Investment Analysts
Startup Founders
Project Managers
Managers responsible for Acquisitions and Mergers

Ce que vous apprendrez

Découvrir les sujets associés

Contenu du cours

Introduction5 sessions • 9 min

Basics of Sales Forecasting4 sessions • 11 min

Useful Tools for Sales Forecasting25 sessions • 1 h 31 min

Case Studies in Sales Forecasting35 sessions • 1 h 39 min

Conclusions1 session • 2 min

Prérequis

Description

À qui ce cours s'adresse-t-il ?