Trying to fundraise, invest in or acquire a company? Time to conduct your due diligence! Regardless of which side of the deal you sit on – the way you handle that data will dictate how swiftly, smoothly and successfully this process goes. Which begs the question, how should you handle your data? The answer: With a fine tooth comb.
Sadly this is not how traditional due diligence is done. In reality, the status quo for this analysis is simply scratching the surface of performance data, basing a deal’s viability on revenue and growth rate, while neglecting the context of that revenue and the type of customer that business holds. This can often lead to unsatisfactory deals that waste time, money and resources.
Luckily somewhere deep in the shadows, unbeknownst to the majority of people, a brand new kind of due diligence has been brewing. This approach automates the analysis of granular transaction level data, providing an up-to-date detailed picture of true performance and growth potential from which no subtle nuance can escape.
So what we’re saying is that when it comes to your due diligence: Granularity = Clarity.
The automation of this granular analysis is the bedrock upon which your deal needs to be built. Without these two features, your information is either too vague or completely out of date. However, if you do adhere to these guiding principles we guarantee that you will be able to easily expose risk, validate KPIs and even uncover fresh opportunities for growth. Let’s review 4 opportunities you mustn’t miss out on.
1. Freshness of data
In a traditional due diligence setup, data is often collected and held in a digital data room 2-3 months in advance of undergoing any analysis at all. The problem with this is that by the time it actually gets reviewed…it’s already old news. As a lot can happen in a few months, this is not the safest way to judge a prospect. Couple this with pre-pandemic assumptions on underlying performance and stability now being questionable at best and you’ll realise just how important it is to have your data constantly flowing.
Fortunately for everyone involved, gaining access to automated, anonymised analysis completed in near real time is now as simple as plugging into a company’s ERP and other related systems. This of course allows for faster and more comprehensive compiling of due diligence reports for urgent timelines. Having this fresh data on hand means that there are no gaps in performance history, enabling investors to make quick, informed decisions and giving them fewer reasons to cast doubt on the viability of a business.
The moral of the story is that the longer data is stored, the more it depreciates in value.
2. Granularity of analysis
Ingesting buy side or vendor due diligence at a high level increases the likelihood of missing out on important details that could mean the difference between a good deal and a disastrous one. You might see a prospect with great revenue and consider it an attractive prospect. But dig a little deeper and find that while sales are high, so are customer acquisition costs. Add a weak gross margin and a poor repurchase rate on top and all of a sudden future viability is cast into doubt.
On the buy side, having customer data broken down by marketing channel, territory, product category, customer cohort, customer segment, and purchasing device will allow you to spot opportunities or major operational flaws.
On the sell side, having prepared this level of detail to support your fundraising efforts will put you in a prime position to ask and receive the funds you seek. A business that conducts granular analysis won’t need to justify their worth – because their data will do it for them.
3. Context of data
It’s easy to misinterpret data from a birds eye view. Which is why looking at rolled up averaged metrics such as overall cost of customer acquisition without taking into account a breakdown by channel, country and product – is rather problematic. Because a company may look like they are profitably acquiring customers (as far as the 3 month old data is concerned), while they were in fact benefitting from a specific ephemeral trend such as bikinis in the lead up to Summer or face masks during the Pandemic.
Meanwhile investors can use their granular data to understand any events or influences that have led to business performance, allowing them to spot where a company may be over or under indexing. For example, revenue growth may be driven from lots of new customers trying a brand once or it could be from brand loyal existing customers. If a company has a great repurchase rate then it may indicate the presence of a strong CRM function in the business. But whilst positive, this is not a lever that can be improved upon therefore new customer acquisition may represent the opportunity for accelerating growth. For an investor trying to understand where they would slot into a business and be able to add value, context matters.
For companies seeking investment, using data to contextualise things such as how a management team has responded to the pandemic, whether the operating model proved resilient and what customer or product groups were most significantly impacted, showcases depth of thinking as well as where you are at in your data journey.
4. Robustness of Infrastructure
Data is useful for more than just evaluating sales and marketing performance. How a company handles their data says a lot about how they handle their business. Having access to this information presents an excellent opportunity for investors to verify whether a business has the right infrastructure to genuinely scale and sustain the exciting growth it promises.
To start with, if they aren’t set up with a data lake that is ingesting from all of their data sources, then it is likely that this information is not being coherently fed to the broader marketing, operations and merchandising teams, nor is it likely to be accessible across the organisation.
You’ll have a good idea of how data driven an organisation is by how well they have connected and used their data. If the due diligence process unearths trends and insights that they had no visibility on whatsoever, this indicates that they are earlier on in their data journey and have a ways to go before intelligently using data as a catalyst for growth.
An automated flow of data can not only be used to identify what’s happening within a business, but also the quality of the team behind it. In fact, the quality of the metrics used as well as the configuration of tools is a very helpful proxy for how strong the teams are. So if performance marketing has been highly optimised, then we know the individuals involved are generally high performers.
Takeaways
With all of this in mind, investors and fund seekers alike should be well prepared to capitalise on these valuable opportunities within the due diligence process; helping you to better understand the level of insight that you can and should collect and how this approach can ensure a successful deal execution that delivers value to all stakeholders.
If in doubt, just remember that:
- If your data isn’t new, it’s too old.
- If your analysis isn’t granular, it’s obscuring the true picture of performance.
- If you don’t contextualise data, you’ll make unfair assumptions about a company’s strengths & weaknesses.
- If you don’t investigate a company’s infrastructure, you can’t truly verify that it is data driven.
