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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Why online learning must be part of an end-to-end M&A process management tool
REQUIREMENT: M&A PROCESS TOOLS MUST CONTAIN ONLINE LEARNING FOR M&A AND POST MERGER INTEGRATION
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
M&A Digitalization: where should data reside?
REQUIREMENT: M&A DATA HAVE TO BE STORED WHEREVER THE CUSTOMER WANTS IT: ON PREMISE, IN THE CLOUD OR HYBRID.
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.
How machine learning can help in digitalization of M&A processes!
REQUIREMENT: MACHINE LEARNING HAS TO BE AVAILABLE IN ALL PHASES OF THE M&A PROCESS.
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!
Nouveau livre : Bases méthodiques pour l'automatisation des M&A
Les praticiens des fusions et acquisitions ont besoin de solutions aux problèmes suivants liés à la numérisation des processus de fusion et d'acquisition :
Il n'est pas clair ce qui doit être numérisé exactement. Quelles sont les tâches, peuvent-elles être automatisées et comment peuvent-elles être numérisées ?
Le potentiel de numérisation dans le cadre du processus de fusion et d'acquisition n'est pas clair. Quelles sont les tâches qui peuvent être numérisées ? Le potentiel de numérisation réside dans l'automatisation (partielle) de tâches qui ne sont pas automatisées aujourd'hui.
Les possibilités de numérisation ne sont pas transparentes. Quels sont les outils disponibles pour numériser les tâches individuelles ?
Ces problèmes sont abordés et des solutions sont présentées dans le nouveau livre présenté ici. Il contient les bases essentielles de la numérisation des fusions et acquisitions.
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Ce qui est fondamentalement nouveau dans ce livre
Un contrôle préalable du modèle commercial est introduit, qui porte sur le modèle commercial de la cible et sa compatibilité avec le modèle commercial de l'acheteur.
Un modèle opérationnel de diligence raisonnable est introduit, qui examine la mise en œuvre du modèle commercial à l'aide des ressources d'une organisation. Les ressources peuvent être des employés, des machines ou des ordinateurs.
Une nouvelle forme de diligence raisonnable stratégique est introduite, qui porte sur la stratégie de la cible et sa compatibilité avec la stratégie de l'acheteur.
Déjà dans le cadre de la diligence raisonnable, les projets d'intégration des fusions sont soumis à un examen sous la forme d'une diligence raisonnable d'intégration des fusions.
Des objectifs factuels et formels sont définis pour toutes les tâches.
Inclusion des applications dans la diligence fonctionnelle au lieu de la seule diligence informatique
Pour la première fois, on tente de décrire un modèle de données complet pour la diligence raisonnable.
Ainsi, vous avez toutes les bases de la numérisation des fusions et acquisitions dans un seul livre.
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Neues Buch: Methodische Grundlagen für die Automatisierung von M & A
M&A-Praktiker brauchen Lösungen für folgende Probleme in Bezug auf die Digitalisierung von M&A-Prozessen:
Es ist unklar, was genau zu digitalisieren ist. Welche Aufgaben gibt es, sind diese automatisierbar und auf welche Weise sind diese zu digitalisieren?
Das Digitalisierungspotenzial im M&A-Prozess ist unklar. Welche Aufgaben kann man digitalisieren? Das Digitalisierungspotenzial besteht in der (Teil-) Automatisierung von Aufgaben, die heute nicht automatisiert sind.
Die Digitalisierungsmöglichkeiten sind intransparent. Welche Tools sind verfügbar, um einzelne Aufgaben zu digitalisieren?
Diese Problemfelder werden im hier vorgestellten, neuen Buch adressiert und Lösungen aufgezeigt. Es enthält die wesentlichen Grundlagen der Digitalisierung von Mergers und Acquisitions.
Was ist grundlegend neu in diesem Buch
Es wird eine Geschäftsmodell Due-Diligence eingeführt, welche sich mit dem Geschäftsmodell des Targets und dessen Verträglichkeit mit dem Geschäftsmodell des Käufers beschäftigt.
Es wird eine Operationsmodell Due-Diligence eingeführt, welche die Umsetzung des Geschäftsmodells mit Hilfe von Ressourcen in einer Organisation betrachtet. Ressourcen können Mitarbeiter, Maschinen oder Rechner sein.
Es wird eine neue Form der Strategie Due-Diligence eingeführt, die sich mit der Strategie des Targets und seiner Verträglichkeit mit der Strategie des Käufers beschäftigt.
Bereits in der Due-Diligence werden Pläne für die Merger Integration einer Prüfung in Form einer Merger Integration Due-Diligence unterzogen.
Sach- und Formalziele für alle Aufgaben werden definiert.
Einbeziehung von Anwendungen in die fachliche Due-Diligence statt nur in die IT Due-Diligence
Zum ersten Mal wird der Versuch unternommen, ein vollständiges Datenmodell für die Due-Diligence zu beschreiben.
Somit haben Sie alle Grundlagen der Digitalisierung von Mergers und Acquisitions in einem Buch.
Klicken Sie, nennen Sie Ihre Adresse und ich schicke Ihnen das Buch versandkostenfrei für 49 Euro zu.
Digitalization of M&A: how the job to be done forces a new generation of tools
REQUIREMENT: M&A PROCESS TOOLS HAVE TO BE NON-INVASIVE AND HAVE TO RESPECT THE WORK ENVIRONMENT OF THE M&A PROFESSIONAL.
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.
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.
Program of the European workshop on software ecosystems as part of the Platform Economy Summit
The European Workshop on software ecosystems will be held as part of the Platform Economy Summit in Berlin, we will have two sessions on the second day of the European Platform Economy summit.
November 21st
11:15am Challenges and success factors for creating digital platforms
14:30 Network Effects & APIs: Their role in driving platform value
The first session is called “Challenges and success factors for creating digital platforms”, moderated by me: Insights from studies, real life projects and Uberization“ and will feature three short motivating presentations by Peter Buxmann, Thomas Curran and Sebastien Dupre followed by topic-bases workshops.
Peter Buxmann, Head of Software & Digital Business Group at Technical University of Darmstadt, will present the topic “Data Economy, Platforms, and Privacy: Insights from multiple empirical studies“. He will provide insights into challenges and success factors for software platform providers regarding the value of customer data, customer privacy and tradeoffs between data privacy and data farming by platform providers.
Thomas Curran will present the transformation of a financial industry heavyweight to becoming an open, digital platform. In a traditionally closed industry, what do you do to turn a company into a digital, open platform. Thomas has done just that in a three year project and will talk about how to do that successfully.
Sebastien Dupre from Coresystems (now SAP) will present the topic “Uberization of field service: a software platform for crowdsourcing service technicians and show how companies can build an ecosystem connecting field service technicians, partners, own employees and customers to scale their field service operations, increase revenue and provide unmatched customer experience.
The second session in the afternoon is called “Network Effects & APIs: Their role in driving platform value “ and will be moderated by Slinger Jansen - Software Ecosystems Research Lab, Utrecht University. It will focus on questions like “What is the role of APIs for platforms? How do you build API-based platforms? What are the success factors and pitfalls when building API-based platforms? How to explain their power to non-technical executives and shareholders?”
The session will start with a short introduction about APIs in general by John Nethans from Google. Then Slinger will present the essence of latest research on API approaches. After that, the panel will focus on pragmatic aspects of creating successful API platforms. After a short while, the panel will open up and take questions from the audience.
This session will feature the following speakers:
Slinger Jansen - Software Ecosystems Research Lab, Utrecht University
John Rethans - Head of Digital Transformation Strategy, Apigee, Google
Nik Willetts - President & CEO, TM Forum
Andreas von Oettingen - CTO Factor10
This session will start with short statements from the panel and will transition to a discussion with questions from the audience.
hope to see you there. please make use of discounted tickets as of below.
Dr. Karl Popp
Join now and you get a special 15% discount off the booking fee. Just quote the discount VIP Code: FKN2652EWOSEL to claim your discount.
For more information or to register for the Platform Economy Summit Europe, please contact the KNect365 team on: Tel: +44 (0) 20 3377 3279 | Email: gf-registrations@knect365.com | Register here.
Remember to quote the VIP code: FKN2652EWOSEL to claim your 15% discount.
Digitalization of M&A: robots are boosting M&A process performance
REQUIREMENT: ROBOTIC PROCESS AUTOMATION HAS TO BE AVAILABLE FOR ALL ACTIVITIES IN THE M&A PROCESS.
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: See what is possible today in just one afternoon
See what is possible today in just one afternoon with pitches of innovative solutions for M&A
Corporate M&A teams don´t have the time and bandwidth to research and follow up with a number of vendors and service providers to get an overview of the latest and greatest innovations for M&A processes.
To solve this issue within one afternoon, Xperience Connect organized an event at Frankfurt School of Finance last week providing several pitches of innovative products and services for next generation M&A processes.
So twenty-two corporates met to have a look at ten vendors, 15 minute pitches by the vendors helped getting an overview within an afternoon, followed by a joint dinner to discuss.
Here are my four highlights of the afternoon:
Target screening
an interesting presentation from a researcher how to reduce the number of potential targets based on acquisition goals, they also use an augmented set of company data. This is a startup in stealth mode but they presented anyway…
Automatic contract analysis
RR Donnelley, a vendor of data room called Venue, showed their product eBrevia, which is a tool to automatically analyze contracts in many different languages based on machine learning.
eBrevia contains about 150 provisions it is able to find and analyze, customers can build AND share new provisions with other customers if they like to.
eBrevia can be used with Venue, but also with other data rooms.
Digital valuation
PWC has an open platform for valuation of startups, https://www.pwc-evaluation.com/
Smart M&A
Midaxo did a very interesting presentation of their innovative, cloud-based, end-to-end M&A process platform.
With this platform, all parties collaborate seamlessly following repeatable, systematic processes based on their specific, corporate playbooks.
Several large corporates, including Daimler and Philipsh have adopted this solution.
Thank you, Stefan Gerhard Schneider for organizing this event. He offered to have follow-up meetings with deep dives, which was well received by the corporates.
If you like this content, please also have a look at www.digitalmergers.com
Digitalization of M&A processes: let´s talk about the data
REQUIREMENT: COMBINE STRUCTURED AND UNSTRUCTURED DATA FOR UNIMAGINED INSIGHTS.
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
REQUIREMENT: A UNIFIED DATA LAKE FOR ALL DEALS.
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!
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.