Simon Jeffery and Nick Mina
by Simon Jeffery and Nick Mina
Introduction
Big data is no longer only whispered about in the hallways of the big tech giants. It is now something that every business has, and every business must deal with. Yet the majority of deal advisors have yet to deploy analytics within their M&A activities. This article will explore how data analytics can be used to enhance deal value;
Unlocking efficiencies during execution; and
Driving deeper insights.
This article will go through each of the three key areas of the deal cycle, and how analytics can be leveraged at each of the following steps:
Deal Readiness;
Diligence & Execution; and
Buy to Build.
Firstly a brief word on the background to the changing data analytics and tools landscape in the deal marketplace:
The cost of employing data analytics technologies in the deals landscape and by deal advisors has plummeted over the past few years:
Data analytics tools are now affordable for every size of deal;
Low code, and no code platforms have dramatically lowered the barriers to operate in this space; and
Data storage in the cloud is now secure and cheap.
Yet a report by Forrester Consulting in 2021 found that only 33% of businesses used business intelligence tools to assist them in their M&A / divestment activities.
Benefits of leveraging data analytics and modelling during deals
When a deal is in progress and the pressure is on, deal advisors, the targets, and acquirors often struggle with a surge in workload, and specifically data issues such as:
Trying to cope with and process large amounts of ad hoc, unstructured, and siloed data;
Struggling to discern the signal from the noise;
The acquiree unable to provide the required reports; and
Parties finding it difficult to meet deadlines.
Bringing in a skilled ‘deals data analytics’ capability will transform the M&A process by being able to:
Generate real, tangible deal value through data-insights;
Empower participants to gain crucial business insights through visualisation and data discovery;
Leverage scripting languages to identify, extract, and efficiently unify data;
Unlock efficiencies by shifting workload to automated engines;
Transforming the deal experience for your clients by giving them added visibility and extended capability;
Reduce the risk of errors, and increase quality of financial models, allowing crucial decisions to be made with confidence; and
Extending the product offering to include process automation, risk assessment and monitoring, data integration, and showcasing the value of untapped synergistic areas.
Key deal areas to leverage data analytics and modelling:
1) Deal Readiness
Preparing data and reports
Building reliable business plans, forecasts and preparing data and reports to ready a client for a deal can be a challenging task. However even readily accessible tools (such as Microsoft Excel) can be unleashed using analytics modules and techniques to effectively extract, clean, and present this data in an automated fashion.
During a merger or acquisition, time is of the essence, yet deal advisors and clients must go through volumes of data to make good decisions. By leveraging analytics techniques such as visualisation or automation, advisors are able to cut through the noise, identify areas of interest, and execute in a rapid efficient manner.
Identifying targets and analysing marketsWord of mouth, referrals, and discussions with networks still remain crucial for identifying and initiating deal opportunities. However the collection of industry data into commercial databases, and the adoption of machine workable formats (such as XBRL) provides a key opportunity to take a data driven approach to identifying opportunities. Much of this data is directly accessible and waiting to be leveraged.
The collection and analysis of this data can be accomplished efficiently and effectively with analytics tools (Python, SQL, Alteryx), and allows for professionals to develop robust, reliable insights into targets, markets and potential clients even before they have been approached.
2) Diligence and execution
With any deal comes the inevitable crunch time of execution. By leveraging analytics, advisors are able to transform their engagements by:
Building powerful datasets that enable comprehensive, timely due diligence to be carried out;
Leveraging statistics and data science to identify areas of value the target might not even be aware of;
E.g. Identifying key revenue drivers that can be exploited post acquisition
Assigning value to key components of the transaction, e.g. brands, or developed software;
Exploiting visualisation techniques to quickly identify and explore areas of concern or value;
Embedding modelling best practice into work, improving valuation quality and accuracy. Thus allowing crucial decisions to be made with confidence; and
Preparing dynamic, reliable models to take to roadshow.
3) Buy To Build
Mergers and acquisitions can create real, on-going value for the parties involved, however the work doesn’t stop when the deal ends.
All relationships are about communication, and data is the language of businesses. Effective transition from standalone businesses to an effective group needs to ensure that the data is getting from point of origin to the crucial decision-making teams by:
Building automated data pipelines to ensure reliable, compatible data flow;
Visualization which will allow for real time risk monitoring and identification; and
Analytics, business intelligence, and data science techniques which will help look into the past and lift the veil on the future. Allowing the business to take advantage of synergies and stimulate growth.
However focussing on the data is not enough, effective processes are made up of both computer systems and people. The skill is in identifying where to target the automation, or introduce analytics capabilities, and where human thought and decision making is required.
By ensuring a successful integration and growth future deals become more likely, and the circle continues.
Final thought
Being able to efficiently harmonise and analyse large sets of unstructured and disparate data does not only generate insight into the “the story’ of a business” it allows decision makers to take control of that story, make assertive decisions, and add real value to their client.
Be bold, step out of the 33% and harness analytics in your engagements.
Sources
Amount of data created – Statista 202333% of businesses use business intelligence in deals - Successful M&A is Data Driven, A Forrester Consulting Thought Leadership Paper Commissioned by LeanIX, July 2021
GGI member firm Theta Insights + ModellingLondon, UKT: +44 20 3918 5941
Auditing & Accounting, Corporate Finance, Advisory
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