Are you looking for ways how to build a pricing model in Excel? Check out this blog post that discusses the 8 best methods. I remember when I was first trying to learn how to build a pricing model in Excel, it felt like an impossible task. There are so many different formulas and functions, not to mention all of the different cells and tabs! But with a little bit of practice (and some help from online resources), I was eventually able to figure it out. And now I’m sharing my knowledge with you!
How to Build a Pricing Model in Excel
There is no one-size-fits-all answer to this question, as the best way to build a pricing model in Excel will vary depending on the specific circumstances and data involved.
However, some tips on how to build a pricing model in Excel include understanding the data and inputs involved, using formulas and functions to create a pricing model, and using sensitivity analysis to test different scenarios.
What are Pricing Methods?
Methods of pricing describe how the prices of products and services are determined.
There are many factors that go into determining the price of a product, including the competition, the target audience, and the firm’s vision of growth.
There are two primary pricing methods:
Cost-Oriented Pricing Method: Many firms use the price of producing the goods as an indicator of how much they should charge. These businesses employ the cost-of-production model, which involves setting a price that covers the expenses of making the good, plus a profit margin. Cost-oriented pricing covers cost-plus pricing, markup pricing, and target-return pricing.
Market-Oriented Pricing Method: Pricing is based on what the market will bear. There are different types of market-based prices, including prices that are based entirely on the perceived value of a product, on the value of the product itself, on what others in the market are charging, competitive bidding, and on sealed-bid auctions.
The type of product a company offers and the objectives of their pricing strategy will determine which market-oriented pricing method they use. The most common methods are perceived-value pricing, value pricing, going-rate pricing, auction type pricing, and sealed-bid auctions.
Building a Pricing System From a Spreadsheet
Do you have an Excel pricing model that we would love to turn into a system? However, the complexity of building a system has inhibited progress in your company.
This is a common challenge that insurance companies face, but new technology has made it easy to convert these models to the cloud. This makes them accessible and massively scalable.
The common misconception is that programming languages such as Java and Python are more popular than Microsoft Excel, but that’s only if you consider spreadsheets to be a form of programming.
There are 800 million people who use Microsoft Excel, but only 26 million people who develop software.
For years, Microsoft Excel has been the go-to tool for creating spreadsheets, but until recently, it has been ignored by programmers. Now, however, technology has been developed that leverages the power of Excel spreadsheets, allowing even non-programmers to build powerful, complex, and scalable applications.
As the ability to convert Excel spreadsheets into cloud applications improves, there is enormous potential to transition excel programmers into full-stack web developers. This would increase the speed of development and reduce overall costs.
This will increase the rate at which developers can build applications, thus lowering the cost of building them.
The widespread usage of Excel spreadsheets for pricing and quoting has led to a business landscape that is highly reliant on the results that come out of these sheets.
However, this dependence on these Excel models has also led to a lack of consideration for the necessity of connecting these formulas to underlying operating systems that are at the heart of businesses.
Spreadsheets, which have been around for decades, are still the most heavily-used tool by insurers.
Insurance professionals use spreadsheets to quickly create formulas and calculate values. This allows them to easily perform common tasks, such as calculating premiums, but at a much lower frequency than they would with a standard database.
Surveys like the one performed by Milliman in 2018 show that spreadsheets are critical or important to the work of over 91% of insurers. This highlights how important spreadsheets are to this industry.
The time is ripe for moving your spreadsheet data into the Cloud.
Data analysis and modeling have all moved to digital environments, now using cloud technology with features like a dashboard, database, and seamless integration of artificial intelligence and automated processes.
This digitalization of the insurance industry has greatly reduced the risks associated with operating in this sector, as well as accelerating the return on investment and profit.
A cloud-based digital solution provides the ability to scale model results easily, which in turn can lead to issuing more quotes and increased sales. The transparency and collaboration afforded by a cloud-based platform also offer distinct advantages over traditional spreadsheet-based solutions.
The transparency of cloud-based pricing is one of its major benefits. The logic of spreadsheets is what makes them so useful.
These models are not accessible to businesses as they are only stored on individual computers or in hidden folders.
If these systems were connected and were more accessible to businesses, the spreadsheets that were built on top of them could add value to the business.
However, many regulatory agencies are wary of spreadsheets, as numerous cases of model failure have come to light. A move to a cloud-based system, however, resolves these issues.
There are 3 different ways to convert spreadsheets.
1. Recode the system into another language.
This would require building out a system from scratch and working closely with the Model Builder to understand the logic and verify the outputs.
- Internal development teams can handle this project without the need for external systems
- It’s expensive (requires developer and pricer experience).
- Converting large numbers of models take a lot of time.
- Modeling errors are everywhere.
- Resources are not available.
- Systems are expensive to update when models change
2. Recode the spreadsheet on an existing commercial pricing platform.
There are several platforms that make it easy for developers to build their own pricing structures. These often have an internal language of their own, and often require experts to maintain them properly.
- Commercial pricing platforms have tools that allow you to recode the spreadsheets in a fraction of the time it would take you to do it manually.
- These tools have methods to check for mistakes.
- Recording phone calls in Salesforce is notoriously difficult.
- The platform can be quite expensive.
- Identifying software developers who know the pricing structure can be more challenging than locating regular programmers.
3: Use an Excel converter.
An excel conversion tool allows a user to upload an Excel spreadsheet and convert it to a cloud based application. This eliminates the need for a developer to build the application from scratch and also reduces the cost of development.
The amount of time it takes to train a model is significantly reduced.
Updating your models in Excel is a breeze, and the changes will automatically update in the system.
Testing can be conducted against the Excel spreadsheet while the model is maintained independently by the Excel developer.
Integrating with other systems can be difficult as some Excel converters may not work well with all Excel models. This can make it difficult to get the data you need from one system to another.
There may also be system requirements when designing a screen for data entry if not provided.
We have worked with all three options and have found that using the excel converter is the most efficient and effective way.
Enterprise-level software is often the best choice for many businesses, but Excel spreadsheets can still be a useful option for many. This is because you can update models without relying on developers for recoding. This can save you both money and time.
Our view on this is based primarily on cost, accuracy and speed.
The very best excel conversion tools have these features:
- Ability to convert Excel models: At its core, an excel converter software should allow you to create exact models from existing spreadsheets, and these need to be tested for accuracy. The software should support complicated formulas, and other important features, like tables, charts, and macros.
- Testing: The Excel spreadsheet conversion tool must be able to produce the same results as the source document, and it must allow the end-user to test their conversions.
- Connections: The finished Excel spreadsheet needs to be connected to all the other systems that it’s involved with. This can be accomplished through APIs, a web interface that can be embedded into client websites, or custom integrations with underlying quoting or administrative software.
- Model governance: The converter should be capable of tracking all versions of the models used, along with a record of the equations and algorithms used for any checks or debugs. It should also be able to identify any changes made to the model that may need updating.
- Model updates: All models and versions of an Excel spreadsheet must go through several changes before being promoted to live use. Any conversion tool should allow for these changes to be made easily and without affecting other systems.
- Databases and dashboards: This system must track the usage of models, and display an overview of the health of the database in a visual dashboard.
There are a number of features that can be useful, but they are often found in better converter systems or insurance pricing platforms. These features can make a big difference in the quality of the conversion process.
We are advocating that systems designers position their excel conversion tools as core components of their intelligent platforms. This is because the number of existing models and the ease of converting them necessitates that software takes advantage of these capabilities.
This approach to building software will greatly reduce the bottlenecks that are currently present in software development and will result in quicker, cheaper, and more innovative applications as 800 million people with basic programming skills start developing their own.
The impact of this will be felt by companies who are quick to adopt this new system, quickly testing and deploying it. They’ll do this because their employees already have the IP they need on their desktops.
The ability to quickly build new products with spreadsheets that can be run in the Cloud will help insurance companies become more nimble, and ultimately, profitable. This newfound flexibility will allow them to easily test out, deploy, and scale up their existing systems using their existing desktop software.
If you’re still struggling with how to build a pricing model in Excel, don’t worry! There are plenty of resources and tutorials online that can help you out. Just keep at it and eventually, you’ll get the hang of it.