Getting your data and analytics house in order pre-acquisition - as a buying company

I've been through a few post merger integrations in my 25 years in the data industry and I haven't seen many companies get it right. And in my experience they get it wrong before even starting the purchase process.

I've spent 25 years in the data industry, and one thing stands out: companies rarely get post-merger integration right. The problem often starts well before the purchase process even begins.

While organizations focus on business synergies, headcount, roles, process integration, and system compatibility, they nearly always forget to plan what they are going to do with their data and non-financial metrics.

Of course, you'll have massaged and polished your financial metrics until they shine, but its not the financial, outcome based metrics I mean. I'm talking about your operational data and input metrics - the ones that emerge from your day-to-day business processes. These metrics are the true language of your organization. They're what people think about, what they measure, and what they're measured on.

Going into a post-merger integration without aligning these metrics is like trying to merge two teams that speak different dialects of what should be the same language. Take the classic example: finance and marketing's completely different views on what constitutes a 'sale'.

Ever heard of 'false friends' when learning a language? Post-merger integrations are full of them, and those dueling spreadsheets are only going to multiply.

Here's 6 steps to get it right.

1) Define your metrics clearly, not just the financials

• Document definitions for all metrics that matter, not just financials

• Establish what good/bad performance looks like

• Set acceptable ranges for each metric

2) Create a baseline

• Establish a clear pre-merger baseline of operational performance

• Document how you measure this performance

3) Understand their metrics

• Determine how the acquisition target views and measures the same metrics

• Identify any gaps or differences in measurement approaches

4) Clean up your house

• Start cleaning up your reference data and hierarchies and process data

• You'll need to do it post-merger anyway when you start looking for efficiencies - why not get ahead?

5) Map their world to yours

• Begin mapping their reference data and hierarchies to your systems

• Identify potential integration challenges early

6) Integrate Early

• Get their data into your cloud data warehouse as early as possible, keep it separate initially (if either of you’re using Snowflake, this is perfect use case for data sharing)

• Use this time to adapt your management systems and reports

• Aim for trusted, integrated reports by Day 1

What this will give you is the opportunity to get your management systems and reports up to speed. You may even have the possibility of getting some integrated reports that you can trust and compare out by day 1.

What's your view? - comment in the below , follow me here, on www.nathanjones.online for more of this, or get in touch via our website www.calonanalytics.com for more of this