Show Me the Data - Constructing Business Cases with Limited Data
In large enterprises, market data is often abundant, with extensive research and deep pockets available to commission bespoke studies. However, for those of us working in smaller organizations or niche markets, the landscape is starkly different. Data is harder to come by, and budget constraints mean customized market research is often not feasible.
Yet, robust business cases and strategic decisions demand high-quality market analysis. How do you bridge the gap? The key lies in creatively leveraging fractional information, making educated assumptions, and building a dynamic model that evolves as new data becomes available.
Why Market Analysis?
Constructing a well-founded business strategy starts with a solid understanding of the market. To do this, we need data that can help us size up the Total Available Market (TAM), Serviceable Available Market (SAM), and Target Market (TM). While TAM and SAM are commonly expressed in terms of revenue, we must also take volume into account, especially when it comes to planning for capacity and delivery forecasts.
If you're using market data from leading analyst firms, I would recommend to automate your data updates so that it will be easy to refresh your analysis results regularly. Tools like Microsoft PowerQuery can help by allowing you to link to external data sources and update your analysis seamlessly when new data is published.
The Perfect World of Data
In an ideal scenario, we would have all the information we need. Here’s what to focus on when constructing your analysis in that perfect world:
When the Data Isn't Perfect: How to Make It Work
More often than not, the data we have is incomplete or lacking in granularity. This is where we need to be resourceful and start making assumptions, always documenting these for later refinement.
1. Estimating Service Revenues
Let’s say you only have data for equipment revenues in a given market. You can still estimate services revenues by using similar markets where both sets of data are available. For instance, you might compare the equipment-to-services ratio in a comparable region and apply that to your current market. By reverse-engineering these figures, you can arrive at a reasonable estimate for services.
2. Estimating CAGR
If specific growth rates aren’t available, turn to broader economic factors. For example, if you’re manufacturing components, look at growth rates for related industries like electronics or automotive. Tech equipment growth can be a good proxy for component sales growth (e.g., using PC growth rates to estimate memory or CPU sales).
3. Working with ASP and Volume Data
Sometimes, the only available data might be revenues. To convert this into a meaningful forecast, you can calculate the average selling price (ASP) and volume by using the formula:
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Revenue = Volume x ASP
If you know two out of these three, you can calculate the third. Document your assumptions, and refine them as more information becomes available. Sensitivity analysis can also help you test the robustness of these assumptions.
4. TAM, SAM, TM Considerations
Are you selling equipment for multiple use cases, services or both? To use the above PC as an example it has use cases (or segments) such as desktop, laptop, rack-mount servers, standalone servers, etc.
All combined is your TAM. Now each has its own unique form factor and performance vs price points that you need to take into consideration when defining what you targeted use cases are and thus what is your SAM. Of course if you are only selling equipment this will limit you SAM as serviceable market. This can also be limited by the countries in which you or your partners operate in. It does however offer significant growth opportunities if currently you are operating in a single country or region. It also allows you to evaluate your or your partners performance is up to par across different regions (revenue-, market share-wise).
Then it comes to what market share do you have in your SAM? This is your target market i.e. you revenue you are aiming for.
Is It Worth the Effort?
At first glance, this process may seem like a mix of guesswork and wishful thinking. But the real value of conducting market analysis, even with limited data, lies in creating a reality check for your business strategy. It helps ensure that revenue projections are realistic and aligned with market opportunities.
It also allows you to evaluate if you are leaving money on the table. As a product company should I be offering professional services and / or managed services also. Alternatively it helps to understand the Total Cost of Ownership to you clients as typically they will need people to support your product (which leads to an interesting discussion about USPs if your product requires less maintenance or is maintenance-free, could you be charging it premium?)
Additionally, market analysis helps you avoid overestimating your share of the market. No company can realistically expect to capture 100% of their TAM, and understanding your actual target share is crucial for making informed decisions.
Conclusion: Start simple, add details as you move forward
Remember, the goal isn't to create a perfect, once-and-done analysis but rather to construct a living document that evolves as new data becomes available. Make your assumptions clear and review them periodically with your team and stakeholders to refine your business case. In this way, even limited data can guide you toward making better, more informed decisions as you are using consistent approach to capturing and analysing the data.
P.S. I am planning to share some practical examples, so if you have some scenarios that you would like me to cover get in touch with me.