M&A, Business Models and Ecosystems in the Software Industry

Karl´s blog

Posts tagged digitalmanda
Denkfabrik Wirtschaft

M&A Aktivitäten sind für viele Unternehmen nach wie vor eine wichtige strategische Option zur Steigerung des Unternehmenswertes und des Unternehmenswachstums. Nichtsdestotrotz ist ein Unternehmenskauf aber oftmals eine große und risikoreiche Investition und stellt insbesondere in der Post Merger Integration eine große Herausforderung für Unternehmen dar.

Es lohnt sich, dieser Phase ein hohes Maß an Management-Aufmerksamkeit zu widmen, denn nachhaltige Wertschöpfung erfolgt nicht durch den Kauf an sich, sondern durch erfolgreiche gemeinsame Integrationsarbeit.

Der Jahreskongress PMI des Bundesverbandes M&A und der angegliederte interaktive Design Thinking-Workshop „Denkfabrik Wirtschaft“ beleuchten die kritischen Erfolgsfaktoren und typische Vorgehensweisen bei der Unternehmensintegration:

  • Standardisierung und Best-Practices für den Integrations- und M&A-Prozess

  • Transformation des Integrations- und M&A-Prozesses durch Digitalisierung und
    digitale Tools

  • Kulturelle Integration im M&A-Prozess

  • aktuellste Erkenntnisse aus der internationalen wissenschaftlichen Forschung und Beratung im Bereich M&A und PMI aus europäischer und amerikanischer Perspektive


Die Teilnehmer des Workshops können Ihre Themen und Fragen aktiv einbringen und zusammen mit anderen Teilnehmern Lösungen erarbeiten und haben so die Möglichkeit, von den praktischen Erfahrungen anderer Unternehmen zu lernen und diese für sich zu nutzen.

Zwei kurze Keynotes runden das Programm ab. Dieses Format gibt es seit drei Jahren und es hat hervorragende Bewertungen der Teilnehmer erhalten.

Und das Erlebnis endet nicht beim Workshop, die Teilnehmer können in dem Arbeitskreis PMI des Bundesverbandes M&A weiter mit den anderen Experten zusammen arbeiten und sich austauschen.

Agenda und weitere Informationen finden Sie unter www.mergerintegration.events

 

M&A digitization: Imagine you can easily review existing tools to automate M&A...

Everybody feels the pressure to digitize. How can you best handle it when you are responsible for the M&A process? Say, you would like to get information which tools are available to automate this task. You could start searching, find some tool vendors, look at a few in more details by coordinating meetings. A tedious process.

Domain model can help

I am working on a domain model, which will be available in an online tool, that does two things: first, define all tasks in the M&A process. Second, it allows to map existing tools to this model, showing which tools are available for which tasks.

What would it look like?

Let us have a look at an example. In the early phase of the M&A process there is a task called pipelining. You want to automate it. This task aims at providing a long list of potential targets and ways to select a subset of targets resulting in a shortlist. So, how would the information about a tool look like? See the information below on a single tool that partially automates this task.

Tool/Service: EY Embryonic
Provider: EY
USP: EY has licensed all expensive databases like CapIQ, CBInsights, ThomsonReuters and has an impressive user experience.
EY Embryonic is offered as a consulting service. 

Great information right? This is just a snippet of the available information. The plan is to list several tools to enable you to select the right tooling to digitize the M&A process.

Stay tuned for more news about the domain model and its many uses. Like what you read? Click on one of the topics or buy one of my recommended books below.

M&A digitalization: We need a domain model for M&A

A domain model for mergers and acquisitions will save us.

The clash of domains

Two companies shall be merged. Two workforces and two administrations have to be aligned, changed and integrated. The first problem that comes up is corporate language and a missing joint domain model and integration plan for people involved but also for applications, companies, locations and countries.

Domain models

Domain models are semantic models that show objects and their relationship in a specific domain. For the M&A domain there will be representations of the M&A strategy, the business case, the integration plan and of course, of both companies to be merged. In addition we need a model of the integration project and all the tasks to be carried out in the different phases of the M&A process. The domain model does not only cover company data, but also data about the M&A process, the involved people and other attributes of the integration like goals and objectives and how they are measured.

Mapping out phases and tasks in the M&A process

Soon , the PMI workgroup of the German M&A association will publish a reference model for all tasks in the M&A process. Here is a short preview of what will be included:

  • Phases: are part of the M&A process like a due diligence phase or the phase between sign and close.

  • Tasks: describe the activities to be carried out during the M&A process. Plus there will be goals and objectives for each task that steer the execution of the tasks and measure success.

  • Concepts: Describe the domain data of the different companies, like companies, departments, the project management domain

Wow, that might be a lot of data types to be modeled, how can you ensure consistency? It all comes together on a task level. Tasks are executed to transform companies to reach an end state, called goal. Goals and objectives will be different by merger and companies involved.

In our case the goal is that the organizations are integrated. Success is measured with two objectives: integration success is maximized and risk is minimized.

task:             execute_merger_integration_project
phase:            merger integration
goal:             buyer and target organizations are integrated.
objectives:       integration success is maximized, risk is minimized.
task description: Resources for the project will be allocated.
                  and the integration project will be executed.
concepts:         target, buyer, organization, budget, project plan, resources

Domain model APIs foster integration of tool vendors

Domain models can be used to drive transparency in the heterogenous world of M&A tools. Tool vendors can easily show the coverage of tasks within the domain model

The description of phases, tasks, concepts, goals etc. will be formalized and can be easily used to generate API descriptions that could be used to integrate different tools in the M&A process like data rooms, project management tools etc. So stay tuned for more progress.


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.

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.

Why online learning must be part of an end-to-end M&A process management tool

Let us have a look at the situation for mergers in most companies. How are people working esp. in merger integration prepared for sucess?

Which people work in post merger integration?

An acquirer has a large project team for post-merger integration and so does the target. How do you make sure that all members of the integration team have sufficient knowledge to perform best? The answer is that all project members, not only the managers and project managers, need background knowledge on merger integration as well as lessons learned and best practices from other merger integration projects

What information is needed?

You need to expand the experience horizon of all involved managers into the realm of merger integration specific topics and decisions. According to Kahneman, what-you-see-is-all-there-is might be a problem, which means that people only can cope with situations that are within their horizon. So you have to expand it with content about merger integration theory but also about situations and pragmatics of merger integration.

How to make training work

Many mergers are cross-border mergers with many people in many countries involved. So due to geographic diversity, timezones etc. onsite training does not make sense. Go online.

The solution

Therefore, a group of seasoned merger integration managers created an online training called PMI2go that provides that knowledge as well as experiences and lessons learned from over 250 successful merger integration projects. The solution is an on demand, online training with just the right mix of theory and hands-on situations explaining how to successfully integrate companies. Together with SAP, Bertelsmann, Qiagen and Stada we created an online training for merger integration that fits multiple different industries and is targeted to managers acting in a merger integration situation.

The training has content for managers and project members and covers in detail topics like HR integration, Finance integration, Production integration and Research and Development integration. Find more information here: http://mergerintegration.eu/mergerintegrationtraining.html

Modules of the online training

Modules of the online training

M&A Digitalization: where should data reside?

In past years, there always was a dichotomy: either companies were only on premise, storing their crown jewel data on site, or companies ran certain applications in the cloud. Now, hybrid clouds are on the rise.  This means there are three options now.  

In M&A, data rooms are typically private cloud based storage of highly confidential data during due diligence. Data from other phases are usually stored on site. With all these changes happening and the clear need to manage M&A processes,  where should company store their data about  all phases of the M&A process ?

On premise?

The safest way to store mission critical data is to store them on premise.  locked up.  This is perfect for a the early phases. As soon as more people get involved from inside and outside the company, during due diligence and post merger integration, this approach is not perfect. 

in the cloud? 

Cloud storage makes perfect sense for trustfully giving restricted access to people from different companies. For most companies, this is needed during due diligence and following phases. But many companies also interact with third party companies even before due diligence. 

Requirements for M&A process tools

Customers rule. An end-to-end process tool must respect that. No matter if  customers choose on site, private cloud or public cloud, vendors of end-to-end process tools should give customers a choice. The customer should decide where to store data. 

Digitalization of M&A: how the job to be done forces a new generation of tools

What is the job to be done? The job to be done is a concept invented by Clayton Christensen in his book "Competing Against Luck: The Story of Innovation and Customer Choice". It is a new way to look at the needs of customers and why they are "hiring" a product to fulfill their needs. The key concept is to focus on the customer and to avoid the viewpoint of the product. By doing so, you get a wider view what the needs of the customers are, what the customer should hire to help him and who your real competitors are.

How does it influence tool design? As soon as you know the job to be done and the context of the customer, you are able to design a product or service that has maximum value for the customer. As mentioned in an earlier blog, the context of an M&A professional is his office, the work environment on his desk, his smartphone, desk phone and computer. An M&A process platform must respect and enhance this work environment, not add another tool. So let us use this approach to define two requirements for M&A process tools.

From tool to pain reliever: One pain i heard most from fellow M&A professionals is to fill the same data like target valuation data into several different Powerpoint presentations which have different formatting but basically should reflect the same data. So an M&A platform must store the financial data of a business case and generate data into different powerpoint templates. An end-to-end M&A process platform should have a data management component for the financial data of the transaction that can intelligently export parts of the financial model into presentation formats.

From tool to productivity boost: assistive technology helps you to perform better. The pain of the M&A professional is that he has to research market and company data, bring them together and evaluate the opportunities. How can an end-to-end M&A platform help here? Market data feeds are provided automatically for business case creation. The platform offers research as a service data feeds to accomplish that.

Summary

End-to-end platforms supporting M&A processes are the basis for the digital future of M&A processes. The job-to-be-done approach helps to define service of these platforms. These value creating services, which are built on top of this platform, help M&A professionals to get their job done. Stay tuned for more or meet me at Platform Economy Summit in Berlin in November.

Digitalization of M&A processes: How to integrate best of breed solutions into one M&A process platform

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.

How machine learning can help in digitalization of M&A processes!

Machine learning is everywhere - except in M&A processes. Let´s change that. Let us imagine the impact of machine learning in different steps of a typical M&A process. Let us start by sharing some of my ideas to trigger your imagination. I am convinced that the technologies needed to achieve this vision are in place today, they are just not being used in this context.

Early phases of the M&A process, shortlisting phases

Let´s say you have five companies in your shortlist. Machine learning can help finding and selecting potential targets e.g. by predicting which of the companies considered will be the unicorn, i.e. the most successful company in the list. Approaches for doing that exist, e.g. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3159123

Preparing the Letter of Intent

Based on past projects, machine learning can help to predict deal breakers, find missing or potentially wrong data in the financial valuation of the target and propose deal structure and clauses for the letter of intent based on the existing, available data about the target and the acquirer.

Due diligence

A vital part of the job to be done in due diligence is that you are looking for missing data, for deal breakers and risks in documents in the data room BUT you only have limited time and a huge data lake in the data room. So let us see how automation and machine learning could help us here.

Day one of due diligence: the data room is available. Day 2 of due diligence: Information about missing data, deal breakers and risks is already available.

How is that possible? Using automated document/contract analysis based on machine learning as well as data about deal breakers and historic projects, a machine learning application can provide this information. There is a huge value in this: you get more time in due diligence to work on missing data, for deal breakers and risks, so quality of due diligence results will massively increase.

No more reporting: During due diligence, digital assistants will automatically keep the lists of tasks, risks, issues and results, will create automatic reporting from that and propose next steps.

Merger integration

Results from the due diligence are automatically distributed digitally to all integration team members. Machine learning based digital assistants propose the integration plan, the integration timeline and which next steps should be taken. They analyze due diligence data and propose the set of data that should be doublechecked and validated. They validate that data by extracting information from the target´s ERP systems automatically and present deviations in digital dashboards and propose next steps.

Learning assistants analyze the learning needed by the involved integration managers based on their CV and proposes digital learning lessons based on PMI2GO.

No more reporting: During due diligence, digital assistants will automatically keep the lists of tasks, risks, issues and results, will create automatic reporting from that and propose next steps.

Let us imagine the impossible - and make it work

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. Like this article to get more inspiration!

Digitalization of M&A: robots are boosting M&A process performance

While we are used to physical robots vacuuming our homes, software robots are not in widespread use yet. The term used for software robots is robotic process automation. (RPA)

What is RPA? 

RPA is defined as tools to build automation for everyday tasks and processes  on a computer screen using Software Robots.   This can start with a simple sequence of clicks on the screen that you can replay automatically. But RPA can also cover more complex workflows with decision points. RPA  tools usually contain a recorder that tracks  certain work sequences on your computer screen and can replay it this sequence later.

What is RPA combined with machine learning? 

Recording workflows with current RPA tools is a manual process. If combined with machine learning, a digital assistant will track your online work and will propose automation of routine processes you do every day. This will lead to a step by step increase of the level of automation in processes.

How does RPA help in M&A processes?

 It frees up time to focus on the really important topics instead of routine tasks  and sequences of clicks on a computer screen.

Digitalization of M&A processes: let´s talk about the data

Digitalization of M&A is about data and data analytics, but also about confidentiality, authorizations and access rights.

  • Establishing a clearly defined, phased, end-to-end M&A process with clearly defined tasks and roles in the different phases (seems obvious, but is not yet implemented, esp. in small and medium countries);

  • establishing a higher degree of automation of tasks (like automated analysis of contracts which needs all contracts to machine-readable), an important prerequisite is to have digital data as much as possible;

  • have one large data set along the end-to-end M&A process (to leverage big data analytics) and clear rules which data are safe to be accessed from the following phase.

So what can you achieve if all these prerequisites are fulfilled, here is my vision:

  • combine structured and unstructured data for unimagined insights : you have financial data, but are they solid and trustable? do the revenue numbers projected reflect the existing contracts with customers? In due diligene, by combining structured information (revenue forecast) with unstructured information (text in contracts, information about pipelines in the data room) you can easily compare both to establish additional trust or to ask tough questions.

  • leverage data across phases of the M&A process: there are restrictions which data from due diligence can be used in later phases. But the data that you can use from target screening and due diligence can be combined and compared with data. Current data you are looking at could be augmented with historical data automatically.

  • actionable insights across M&A projects: the data from all phases and all M&A projects can be used to determine actions in a specific situation. Based on machine learning, an automated assistant could propose what to do, what has been done in other projects in similar situations, could propose who to talk to to leverage the lessons learned from other projects.

So the call to action is: Unite your data on and end-to-end platform to build the foundation to leverage the data for better insights, better execution and more success in M&A processes.

Digitalization of M&A processes: Advantages of an end-to-end, unified platform
blocks_Small.gif

An end-to-end, unified platform builds the foundation of M&A success. End-to-end means that the platform covers all phases of the M&A process from early strategizing to deal sourcing to due diligence, signing, closing and integration. All data are combined to one single source of truth, no data are lost between phases, better and well documented handovers are possible between phases.

Unified platform means no more jumping between different solutions and tools. t eases the pain of processing massive amounts of data, be it the data room or planning data for integration planning. For due diligence, this includes combining collaborative due diligence management with virtual data room capabilities.

While there are many advantages of such a platform, let´s just look at three key advantages.

Advantage 1: A unified data lake for all deals

The data lake covers all process phases and all deals allowing e.g. cross-deal analytics, large training sets for machine learning, proposals of next steps based on best practices from all deals. The data lake contains massive amounts of information, but all information used in the process, information about the process steps and decisions taken is stored in one place.

The load of information in M&A processes is already overwhelming? So how can i leverage this large amount of data? Modern information system technologies like predictive analytics, finding outliers within data, semantic analytics and forensic tool to analyse and navigate large data sets as well as providing the right information for your current work context will enable you to leverage the data collected.

Advantage 2: Better decision are being taken and documented

There are two aspects of this advantage: decision journey and augmentation. For each decision taken, you can always recall the decision journey. How was the decision prepared, who took it, what were the consequences, were the goals of the decision reached?

The second aspect is augmentation of decision tasks: if you are the decision maker, augmentation provides you with similar decision taken in other deals including their impact on results in the integration phase, so you can make the best decision. The augmentation in the deal sourcing phase e.g. includes market data, financial data about all targets and predictive analytics about the future success of the target companies.

Advantage 3: Less documentation and reporting: More productivity

Massively increased productivity and less errors due to robotic process automation. No more learning of process models, they will naturally be followed. No more thinking about what the next step is or what your project status is, all information is augmented in your usual workplace. Reporting annoys you? The platform will autmatically propose the content for the next status update, so you spend less hours on reporting, more on quality work and problem solving.

Outlook: where´s the platform?

So, now we know some of the advantages of the platform: one question remains: is the platform your work environment and do you have to learn a completely new work environment that does not naturally integrate with all the other productivity tools that you are using: email, teleconferencing etc.? The platform i envision will be invisible, you will work in your usual work environment, e.g. using a Windows tablet with Outlook and other tools you know. the platform will track your work and augment inforrmation as you work, no separate login, no missing integrations that get on your nerves.

If you liked this article, you will like my book about due diligence.

Let us cover the final frontier of digitalization: M&A processes!
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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.