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June 22, 2018
By Trey Johnson
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Here are 7 key ways data management helps in acquisitions:
To begin with the basics, acquisitions occur for a variety of reasons. These can include:
Regardless of the reasons – many of which are examined in great depth by the likes of Forbes or by prominent authors – the varieties of acquisition and the various frequencies with which a company engages in the process, there are a still a set of common factors that everyone will recognize:
While there are rarely “quick wins” around points 1 and 2, if you need to deliver the C-suite with “an expanded view of the new companies” – and before you pick up Tableau, Power BI or your favorite data visualization tool – take a read of how data management technology can really help.
I always describe data as being comprised of ‘nouns’ and ‘verbs’. The business processes are generally the ‘verbs’, such as:
And what, from a data perspective, I call the nouns are — when looking across one or more companies – the likes of
By looking at the common nouns, even if they don’t 100% line up, you can create some unified results. Like in this scenario, that I’ve seen come up on the boardroom on more than one occasion:
‘Parent Company A’ acquires ‘Company B’ and ‘Company C’. Each company has their own ERP, perhaps a combination of Sage ERPs and Microsoft Dynamics ERPs. ‘Parent Company A’s CFO wants to look across all these ERPs to see the basic components of a P&L, a balance sheet or maybe even just some key revenue elements around sales and profitability.
Data management helps immensely in this scenario. With almost 100% certainty, each company is going to be using different account numbers or ranges to define common finance items like “Revenue”, “Expense”, “Sales”, and “Cost of Goods Sold”.
A good data management toolset will allow for the importation of a mapping mechanism. Perhaps the most popular mapping mechanism with the finance crowd? Microsoft Excel, of course! So we can translate ‘Company B’s use of accounts 2000-2100, ‘Company C’s use of accounts 400, 410 and 440 all to an agreed sales account used by ‘Parent Company A’ (say Account 3100).
Now, not only can we translate the ledger transactions to one common COA (Chart of Accounts) but we can, with data management, create a resulting view which combines – or allows – for the comparison of companies A, B and C side-by-side.
This same technique can be performed for other ‘nouns’ and is generally performed by people outside of IT who have the financial or operational domain knowledge to support this.
There will be scenarios where it might be challenging to arrive at the perfect common ‘noun’ across every business. This is particularly true of corporates, where there are many “Doing Business As” types of entries. A good data management platform should open the door to external enrichment whether by leveraging intelligent matching services or simply supporting some AI/ML-based matching. It’s not full-blown Master Data Management but getting closer to providing answers using these external services starts with a good data management platform.
A simple but highly effective way to get insight quickly is to come up with some new common adjectives which can be applied across ‘nouns’ like “Customer,” or “Supplier,”. If Companies A, B, and C each do business globally, then overlap is possible. As soon as they decide to gain maximum immediate insight, then they’re going to add a few new adjectives to each customer on their new ‘Master List’ of customers. One will be based on customer size, one will be based on the frequency of transactions, and one will be the geographic placement of the customer. All with basic agreed rules that the data management process can apply to assign these adjectives.
As a result of this data management, the business becomes able to ask many ROI-focused questions using the combination of common ledger characteristics and these new data ‘adjectives’:
With a new composite of three companies – who all do business globally – rolling up the details requires some careful consideration for things like currency conversion. Where data management helps here is being able to source common data, like exchange rates.
As we align to common account definitions, find common ‘nouns’ and arrive at some common ‘adjectives’, using an external source to ensure consistent translation of currencies is the final step in the data and IT teams being able to quickly deliver the C-suite with an expanded view of their new combination of companies.
Indeed, I’ve seen this – both the reports and the ROI – become realized very quickly for companies and having a sound data management platform is always the common denominator.
Of course, all the things described here apply equally well if your company finds itself in the position of moving from one application platform to the other, rather than acquiring another entity. In your case, ‘Company A’ might be your current company, and ‘Company B’ might be the next ERP you’re migrating to soon. If that’s indeed the case, the above suggestions apply to you, too.
Trey Johnson is ZAP’s Chief Evangelist. Based out of Jacksonville, Florida, he joined the company in 2008 bringing experience from leading various boutique BI software and national consulting companies. A published author, speaker, and consultant, Trey sat on the PASS Board of Directors over multiple terms, concluding as their Executive Vice President. He was a long-term member of Microsoft’s BI Partner Advisory Council and has spent the last 25 years delivering business intelligence, data warehousing, and data management solutions to businesses of all shapes, sizes and “data challenges.” Follow Trey on Twitter and LinkedIn.
#Excel | #Tableau | #PowerBI | #Acquisition | #DataManagement | #DataViz | #Financials | #ERP | #Sage | #MicrosoftDynamics
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