M&A thought leadership: Integration of new business models: dimensions of similarity
Similarity of business models impact merger integration speed
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No matter if you integrate a target running a business model that is new to your company or if you want to disrupt your business model or if you ask intrapreneurs to come up with new business models; you will face one big issue: how to integrate the business model that is new to your company. So, “new” means that the acquirer is not capable of running the processes that support such business model (yet).
Business models and operations models
I would like to separate two dimensions here: business models and operations models. A business model tells which goods or services are provided by a company and how the company is compensated for the goods and services. It is a model on a type level, like a company running field service management solutions in the cloud for a monthly license fee. It already describes on a general level what a company is doing. On this level of granularity, companies can easily be similar.
A business model can be implemented in an operations model. The operations model shows how the business is run and how the resources of the business run the corresponding business processes in the company. This model is very concrete, detailed and more complex and involves resources running and used in the business processes like employees or application systems. On this level of granularity, it is harder to tell if two operations models are similar.
In the following, I would like to share insights from integration acquired software companies about the impact of the similarity on merger integrations.
Similarity of business models
The more similar business models are, the better the operations of these business models can be integrated. The operations might be similar; sales and accounting processes might only need small changes to be adapted. But there might be issues with overlaps in organizations.
For software companies, this means easier integration in development and support but also in administrative functions. So you should look for similarities and differences by listing/modeling the business models of target and acquirer already in due diligence.
In contrast, if business models are very different, this might pose a challenge for integration. You would have to decide if you want to continue the different business models and if so, changes needed to continue both business models have to be executed in merger integration. For merger integrations targeting absorption, this might mean that the acquiring organization would have to adapt to a diverging business model of the target.
Similarity of business models enables higher speed of integration: The more similar business models are, the better the operations of these business models can be integrated. This enables higher speed. The reverse is also true. If business models are significantly different, this might impose slower speed of integration.
Similarity of operations models
Operations models are implementing business models. How a business operates is a key thing to understand for integrating a business. The closer two operational models are, the easier it is to integrate both businesses with each other. You may use operations maturity models to determine the current and desired state of target and acquirer operations.
An example for similar operations models is having the same objectives for procurement at the acquirer and the target. If both companies look for maximum quality of supplies in procurement it might be a lot easier to integrate procurement processes, to align demands, to analyze and plan cost synergies.
Similarity of operations models enable higher speed of integration. How a business operates is a key thing to understand and to integrate a business. The closer the operational models of acquirer and target are, the higher the speed of integration can be. There also i a higher likelihood of economies of scale effects and cost synergies in such cases.
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For more insights, please refer to the books "Mergers and Acquisitions in the software industry: Foundations of due diligence" and Automation of M&A strategy
M&A digitalization: Forget data rooms for M&A: what we need is a data lake and a data warehouse during due diligence and PMI
In M&A processes, data rooms are all over the place. They are a storage for unstructured and structured data. But these structured and unstructured data are not up-to-date, not complete and they might even be contradicting each other. They might even be aggregated in a way we don´t know and cannot reproduce and we don´t know the underlying data at all. Not a perfect situation to judge based on the numbers and documents. Making sense of this information is tedious and making decision based on this information is very risky. So, what can we do about it? Let me brainstorm a little about that….
Big data is a no-brainer
There are solutions out there who can easily and quickly analyze wast amounts of structured and unstructured data. They can analyze and interpret contracts and other documents, they can find critical clauses in business documents and find e.g. indications of fraught. They can relate information to get analytics about outlyers in financial data, from which business transactions this outlyer originates and by the way, which employee is responsible and accountable for this business transaction. In seconds. This is not a vision, the technology to do this is there and can be used that way. So we should make use of it.
What is possible today?
No matter if you do the analysis during due diligence (with limited information) or post close (with access to all information), you are able to do automated scans that provide you with the following information:
Technical IT landscape: which servers run where and how are they connected, which software runs on which servers
Business system information: which ERP systems are running, what is the business structure, through which APIs are the different business systems communicating, which companies are there, how are they interacting, which business models are implemented. You can compare different systems with each other or with a best practice template or to-be system easily.
Business status information: which processes are being run, how often and in which speed are they executed, how do they perform and how often are process exception handling activities executed.
To summarize, using these automated tools can increase the level of detail and precision of IT and business due diligence and provide a sound basis for a joint IT and business integration planning as early as possible in the M&A process.
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Data analysis and interpretation is just the beginning
Life will be easier. Here´s my vision for next generation due diligence work based on data. Now that you found items that are interesting and you analyzed them in due diligence, you have to figure out what actions to take during due diligence and post merger integration. Machine learning is here to help. Based on a set of earlier acquisitions and the plans for the current acquisition, a machine-learning-based algorithm will propose which actions are required by the buyer or the target and/or proposed clauses in contracts to deal with this situation. Let´s imagine new ways of running due diligence and PMI
In due diligence: just give us access to a data lake of structured and unstructured information and give us access to your data warehouse structure and we can analyze the company structure, the business models and the steps needed to transform the business and to plan the integration of the business with the acquirer´s business.
In post merger integration: In addition to data lakes and data warehouses we have access to business systems details which allow to analyse, optimize, transform the acquired business and automatically get proposals which steps should be taken during the integration phase on a detailed level.
Follow me on twitter @karl_popp or stay tuned for more blog entries on innovations in the M&A process.
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Digitalization of M&A processes: How to integrate best of breed solutions into one M&A process platform
Requirement: We need a metamodel of end-to-end M&A processes and objects
We have to move forward quickly to disrupt existing M&A processes and get the best innovations to get to a digital M&A process. So here are my thoughts, some might be drafty, but i want to get my requirements out now to ensure we all are facing the right direction for digital M&A.
Requirement: we need several vendors to provide innovations
Can the best innovation for all phases of M&A come from one vendor only? Probably not. So how do companies get the best functionality in a unified, end-to-end M&A platform? The platform has to be open, has to have OData based APIs to allow integration with the best of breed functionality for the different phases of the M&A process.
Requirement: We need a metamodel of end-to-end M&A processes and objects
Thirty years of object modelling for businesses are paving the way to create a metamodel of M&A processes. This metamodel should contain the objects and relationships to be used in the M&A process like buyer, target, companies, which are contained in longlist, shortlist, have relationships with data rooms, documents like contracts, patents, financial data etc. etc. In addition we need
Requirement: Standardization is needed
Establishing a standard metamodel for end-to-end M&A processes is key to success. There are three ways to establish it: via the market or via standardization committees or by creating a winner takes it all market for the end-to-end M&A process platform. it will be interesting to see which vendor chooses which approach.
Requirement: An ecosystem of extensions of the end-to-end M&A process platform
Based on the standardization and the OData-based metamodel, M&A process platform vendors can start to foster an ecosystem of innovations for the M&A process. Today, we would need e.g. the following ecosystem of vendors to engage: end-to-end M&A process platform, data room vendor, company information providers, contract analysis providers, machine learning application providers etc.
Summary
With the listed requirements in place, we can move forward quickly to leverage innovations from different vendors. From my point of view, establishing a winner in the end-to-end M&A process platform market is paramount to provide massive innovation to many companies. Several large corporates in Germany are considering to choose such an M&A process platform today to streamline their operations. I will keep you posted if there is one vendor that wins the market or if there are several vendors fighting for larger marketshares at customers.
Like my way of thinking? So feel free to read my book about M&A: M&A due diligence in the software industry. Do also feel free to comment, happy to receive the feedback.
Let us cover the final frontier of digitalization: M&A processes!
REQUIREMENT: MASSIVE DIGITALIZATION OF THE M&A PROCESS.
While many business processes are automated, use big data analytics and digital assistants, we seem to run M&A processes like it is 1999. Imagining what is possible today, we are on the verge of disruption in M&A.
What is needed?
Here is the list of requirements to massively digitize the M&A process:
end-to-end process support from early phases to end of the integration project,
Digital learning for M&A knowledge,
Semantic analysis of available data of acquirer and target and then leverage the semantic data to navigate the data via assistive technologies, like automatic analysis of legal documents,
assistive technologies like chatbots, robotic process automation and digital assistants that help managers watch risks, ask the right questions and propose proper next steps,
big data analytics: data rooms are a large data set, so why dig through it manually?,
Use of forensic technologies for understanding and investigating data room content
Automate IT due diligence by using scanners for analysis of networks, applications and interfaces,
Automatically analyse content of existing ERP systems for due diligence, merger integration and migration of ERP systems.
What is already digital?
Learning: see PMI2GO: digital online learning for post merger integration
Data rooms: Trusted file stores for due diligence are digital. But is file store digitalization driven far enough? No. Not yet.
Process digitalization: There are M&A process tools that allow partial automation of management tasks. But do we get digitalization with chatbots, assistive technology based on machine learning? No. Not yet.
The opportunities are massive but are not yet leveraged. I think the M&A community has to provide guidance to vendors to achieve a vision i call the Digital M&A Manifesto. Stay tuned for more details.