Over the past few weeks several huge mergers and acquisitions (M&A) have been announced, including Raytheon and United Technologies, the Salesforce acquisition of Tableau and the Merck acquisition of Tilos Therapeutics.
According to collated research and a Harvard Business Review report, the M&A failure rate sits between 70 and 90 percent. Additionally, McKinsey estimates that around 70 percent of mergers do not achieve their expected “revenue synergies.”
Combining two organizations into one is complicated. And following a merger or acquisition, businesses typically find themselves with duplicate applications and business capabilities that are costly and obviously redundant, making alignment difficult.
Enterprise architecture is essential to successful mergers and acquisitions. It helps alignment by providing a business- outcome perspective for IT and guiding transformation. It also helps define strategy and models, improving interdepartmental cohesion and communication. Roadmaps can be used to provide a common focus throughout the new company, and if existing roadmaps are in place, they can be modified to fit the new landscape.
Additionally, an organization must understand both sets of processes being brought to the table. Without business process modeling, this is near impossible.
In an M&A scenario, businesses need to ensure their systems are fully documented and rationalized. This way, they can comb through their inventories to make more informed decisions about which systems to cut or phase out to operate more efficiently and then deliver the roadmap to enable those changes.
Mergers and acquisitions are daunting. Depending on the size of the businesses, hundreds of systems and processes need to be accounted for, which can be difficult, and even impossible to do in advance.
Enterprise architecture aids in rooting out process and operational duplications, making the new entity more cost efficient. Needless to say, the behind-the-scenes complexities are many and can include discovering that the merging enterprises use the same solution but under different names in different parts of the organizations, for example.
Determinations also may need to be made about whether particular functions, that are expected to become business-critical, have a solid, scalable base to build upon. If an existing application won’t be able to handle the increased data load and processing, then those previously planned investments don’t need to be made.
Gaining business-wide visibility of data and enterprise architecture all within a central repository enables relevant parties across merging companies to work from a single source of information. This provides insights to help determine whether, for example, two equally adept applications of the same nature can continue to be used as the companies merge, because they share common underlying data infrastructures that make it possible for them to interoperate across a single source of synched information.
Or, in another scenario, it may be obvious that it is better to keep only one of the applications because it alone serves as the system of record for what the organization has determined are valuable conceptual data entities in its data model.
At the same time, it can reveal the location of data that might otherwise have been unwittingly discharged with the elimination of an application, enabling it to be moved to a lower-cost storage tier for potential future use.
When employees come and go, as they tend to during mergers and acquisitions, they take critical institutional knowledge with them.
Unlocking knowledge and then putting systems in place to retain that knowledge is one key benefit of business process modeling. Knowledge retention and training has become a pivotal area in which businesses will either succeed or fail.
Different organizations tend to speak different languages. For instance, one company might refer to a customer as “customer,” while another might refer to them as a “client.” Business process modeling is a great way to get everybody in the organization using the same language, referring to things in the same way.
Drawing out this knowledge then allows a centralized and uniform process to be adopted across the company. In any department within any company, individuals and teams develop processes for doing things. Business process modeling extracts all these pieces of information from individuals and teams so they can be turned into centrally adopted processes.
Industry and government regulations affect businesses that work in or do business with any number of industries or in specific geographies. Industry-specific regulations in areas like healthcare, pharmaceuticals and financial services have been in place for some time.
Now, broader mandates like the European Union’s Generation Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) require businesses across industries to think about their compliance efforts. Business process modeling helps organizations prove what they are doing to meet compliance requirements and understand how changes to their processes impact compliance efforts (and vice versa).
In highly regulated industries like financial services and pharmaceuticals, where mergers and acquisitions activity is frequent, identifying and standardizing business processes meets the scrutiny of regulatory compliance.
Business process modeling makes it easier to document processes, align documentation within document control and learning management systems, and give R&D employees easy access and intuitive navigation so they can find the information they need.
Organizations often interchange the terms “business process” and “enterprise architecture” because both are strategic functions with many interdependencies.
However, business process architecture defines the elements of a business and how they interact with the aim of aligning people, processes, data, technologies and applications. Enterprise architecture defines the structure and operation of an organization with the purpose of determining how it can achieve its current and future objectives most effectively, translating those goals into a blueprint of IT capabilities.
Although both disciplines seek to achieve the organization’s desired outcomes, both have largely operated in silos.
To learn more about how erwin provides modeling and analysis software to support both business process and enterprise architecture practices and enable their broader collaboration, click here.