Using Data to Tell Your Company's Unique Story in a Transaction [PODCAST]

Every company has a story that details how their innovative product or service idea came to be. That story typically includes how they were founded, 它们是如何成长和扩张的, and how they matured into the organization they are today. That story may encompass a journey that started over one hundred years ago—or it could be the newest startup that began with a fledgling idea less than a few years prior.

But what type of story does your company’s data tell? 你有数据吗? 如果有，你有 访问 它? And what role does that data play in today’s M&一个市场? 

听播客:

The story your company’s data tells is almost more important than the historical record that you might have documented in a book, 一本小册子, or perhaps in a digital document on your laptop. So how do you leverage it as part of an M&一个事务?

Aaron Yentz, Vice President at 蓝色行动伙伴, 加入乔·赫尔曼, partner at Redpath和公司, to discuss the role that data analytics plays in helping deal teams, 管理团队, 私人股本, and investment bankers make the most of data during the sale process and to maximize value for their clients.

Assessing Data Quality: “Garbage In, Garbage Out!”

The quality of your company’s data relies on a myriad of factors including what systems you’re leveraging, 数据是如何输入的, and how often it gets updated. But what’s certain is that the quality of data is greatly affected by whether or not you have well-established processes and systems for collecting and entering the data you do gather.

Factors the contribute to less-than-optimal data quality include:

• Data that’s entered manually or multiple times.
• Non-user friendly systems that do not get used which results in missing or incomplete data.
• Lack of 访问 to an older/previous ERP system and/or a system transition (could be a case that results from the company engaging in a recent add-on acquisition).

What About “Unusable” Data or “Missing” Data?

It’s not often that a company’s data is truly unusable or missing. 在很多情况下, “missing” data might be due to assumptions that it does not exist because there are no KPI’s established that would leverage specific data sets. 通常, this assumption exists because the data was never looked for in the first place or pulled out and used as a measurement tool—and therefore leadership assumes the data is nonexistent.

Even data considered “unusable” may just need a little more work to mine the information that is there. Even incomplete data can help tell a story and highlight what’s going on in the business. It might just take a little more work to extract those specific nuggets that management can speak to in the transaction process.

How Do Companies Get at KPIs Within the Data Set?

If management doesn’t have the time, 资源, or data to invest in integration or dashboard creation, the organization helping mine the data will focus on the “nice to have” KPIs. This includes leveraging the input of other transaction advisors (such as bankers) to understand what buyers are paying the most attention to and to get at KPIs that matter most for the business or industry.

Sometimes the process includes taking data from different systems and marrying them together to normalize the data set. But no system is perfect and there are typically always gaps in data. The goal when extracting data is to add structure to the data and provide explanations to ensure the analytics are still meaningful.

Be Ready for the Data Request

It’s getting more and more common for more granular data to be requested, especially on the buy-side. Teams should be prepared for those requests by addressing them effectively and in a timely manner—which can help give more comfort to the buyer.

Final Thoughts From Aaron Yentz:

• Understand the value that data can have on the sell-side.
• Tools and technology to leverage data will become more efficient and cost-effective and they will continue to make their way to the lower end of the middle market. Leadership teams will no longer have a reason to not be prepared to leverage data and analytics to tell their company’s story in a transaction.