Tag: business process modeling

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erwin Expert Blog Business Process

In Times of Rapid Change, Business Process Modeling Becomes a Critical Tool

With the help of business process modeling (BPM) organizations can visualize processes and all the associated information identifying the areas ripe for innovation, improvement or reorganization.

In the blink of an eye, COVID-19 has disrupted all industries and quickly accelerated their plans for digital transformation. As part of their transformations, businesses are moving quickly from on premise to the cloud and therefore need to create business process models available to everyone within the organization so they understand what data is tied to what applications and what processes are in place.

There’s a clear connection between business process modeling and digital transformation initiatives. With it, an organization can explore models to understand information assets within a business context, from internal operations to full customer experiences.

This practice identifies and drives digital transformation opportunities to increase revenue while limiting risks and avoiding regulatory and compliance gaffes.

Business Process Data Governance

Bringing IT and Business Together to Make More Informed Decisions

Developing a shared repository is key to aligning IT systems to accomplish business strategies, reducing the time it takes to make decisions and accelerating solution delivery.

It also serves to operationalize and govern mission-critical information by making it available to the wider enterprise at the right levels to identify synergies and ensure the appropriate collaboration.

One customer says his company realized early on that there’s a difference between business expertise and process expertise, and when you partner the two you really start to see the opportunities for success.

By bringing your business and IT together via BPM, you create a single point of truth within your organization — delivered to stakeholders within the context of their roles.

You then can understand where your data is, how you can find it, how you can monetize it, how you can report on it, and how you can visualize it. You are able to do it in an easy format that you can catalog, do mappings, lineage and focus on tying business and IT together to make more informed decisions.

BPM for Regulatory Compliance

Business process modeling is also critical for risk management and regulatory compliance. When thousands of employees need to know what compliance processes to follow, such as those associated with the European Union’s General Data Protection Regulation (GDPR), ensuring not only access to proper documentation but current, updated information is critical.

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 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).

This same customer says, “The biggest bang for the buck is having a single platform, a one-stop shop, for when you’re working with auditors.” You go to one place that is your source of truth: Here are processes; here’s how we have implemented these controls; here are the list of our controls and where they’re implemented in our business.”

He also notes that a single BPM platform “helps cut through a lot of questions and get right to the heart of the matter.” As a result, the company has had positive audit findings and results because they have a structure, a plan, and it’s easy to see the connection between how they’re ensuring their controls are adhered to and where those results are in their business processes.

Change Is Constant

Heraclitus, the Greek philosopher said, “The only constant in life is change.” This applies to business, as well. Today things are changing quite quickly. And with our current landscape, executives are not going to wait around for months as impact analyses are being formulated. They want actionable intelligence – fast.

For business process architects, being able to manage change and address key issues is what keeps the job function highly relevant to stakeholders. The key point is that useful change comes from routinely looking at process models and spotting a sub-optimality. Business process modeling supports many beneficial use cases and transformation projects used to empower employees and therefore better serve customers.

Organizational success depends on agility and adaptability in responding to change across the enterprise, both planned and unplanned. To be agile and responsive to changes in markets and consumer demands, you need a visual representation of what your business does and how it does it.

Companies that maintain accurate business process models also are well-positioned to analyze and optimize end-to-end process threads—lead-to-cash, problem-to-resolution or hire-to-retire, for example—that contribute to strategic business objectives, such as improving customer journeys or maximizing employee retention.

They also can slice and dice their models in multiple other ways, such as by functional hierarchies to understand what business groups organize or participate in processes as a step in driving better collaboration or greater efficiencies.

erwin Evolve enables communication and collaboration across the enterprise with reliable tools that make it possible to quickly and accurately gather information, make decisions, and then ensure consistent standards, policies and processes are established and available for consumption internally and externally as required.

Try erwin Evolve for yourself in a no-cost, risk-free trial.

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Business Process Modeling Use Case: Disaster Recovery

In these challenging times, many of our customers are focused on disaster recovery and business contingency planning.

Disaster recovery is not just an event but an entire process defined as identifying, preventing and restoring a loss of technology involving a high-availability, high-value asset in which services and data are in serious jeopardy.

Technical teams charged with maintaining and executing these processes require detailed tasks, and business process modeling is integral to their documentation.

erwin’s Evolve software is integral to modeling process flow requirements, but what about the technology side of the equation? What questions need answering regarding planning and executing disaster recovery measures?

  • Consumers and Dependencies: Who will be affected if an asset goes offline and for how long? How will consumer downtime adversely affect finances? What are the effects on systems if a dependent system crashes?
  • Interconnectivity: How are systems within the same ecosystem tied together, and what happens if one fails?
  • Hardware and Software: Which assets are at risk in the event of an outage? How does everything tie together if there is a break point?
  • Responsibility: Who are the technical and business owners of servers and enterprise applications? What are their roles in the case of a disastrous event?
  • Fail-Over: What exactly happens when a device fails? How long before the fail-over occurs, and which assets will activate in its place?

The erwin disaster recovery model answers these questions by capturing and displaying the relevant data. That data is then used to automatically render simple drawings that display either a current or target state for disaster recovery analysis.

Reports can be generated to gather more in-depth information. Other drawings can be rendered to show flow, plus how a break in the flow will affect other systems.

erwin Rapid Response Resource Center (ERRRC)

So what does an erwin disaster recovery model show?

The erwin model uses a layered ecosystem approach. We first define a company’s logical application ecosystems, which house tightly-coupled technologies and software.

  • For example, a company may have an erwin ecosystem deployed, which consists of various layers. A presentation layer will include web-based products, application layers holding the client software, data layers hosting the databases, etc.
  • Each layer is home to a deployment node, which is home to servers, datastores and software. Each node typically will contain a software component and its hosting server.
  • There are both production nodes and disaster recovery nodes.

Our diagrams and data provide answers such as:

  • Which production servers fail over to which disaster recovery servers
  • What effects an outage will have on dependent systems
  • Downtime metrics, including lost revenue and resources required for restoration
  • Hosting information that provides a detailed view of exactly what software is installed on which servers
  • Technology ownership, including both business and technology owners

The attached diagram is a server-to-server view designed to verify that the correct production to disaster recovery relationships exist (example: “prod fails over to DR”).  It also is used to identify gaps in case there are no DR servers in deployment (example: we filter for “deployed” servers only).

Other views can be generated to show business and technology owners, software, databases, etc.  They all are tied to the deployment nodes, which can be configured for various views. Detailed reports with server IP addresses, technical owners, software instances, and internal and external dependencies also can be generated.

You can try erwin Evolve for yourself and keep any content you produce should you decide to buy.

Our solution strategists and business process consultants also are available to help answer questions about your disaster recovery process modeling needs.

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Enterprise Architecture and Business Process Modeling Tools Have Evolved

Enterprise architecture (EA) and business process (BP) modeling tools are evolving at a rapid pace. They are being employed more strategically across the wider organization to transform some of business’s most important value streams.

Recently, Glassdoor named enterprise architecture the top tech job in the UK, indicating its increasing importance to the enterprise in the tech and data-driven world.

Whether documenting systems and technology, designing processes and value streams, or managing innovation and change, organizations need flexible but powerful EA and BP tools they can rely on for collecting relevant information for decision-making.

It’s like constructing a building or even a city – you need a blueprint to understand what goes where, how everything fits together to support the structure, where you have room to grow, and if it will be feasible to knock down any walls if you need to.

 

Data-Driven Enterprise Architecture

 

Without a picture of what’s what and the interdependencies, your enterprise can’t make changes at speed and scale to serve its needs.

Recognizing this evolution, erwin has enhanced and repackaged its EA/BP platform as erwin Evolve.

The combined solution enables organizations to map IT capabilities to the business functions they support and determine how people, processes, data, technologies and applications interact to ensure alignment in achieving enterprise objectives.

These initiatives can include digital transformation, cloud migration, portfolio and infrastructure rationalization, regulatory compliance, mergers and acquisitions, and innovation management.

Regulatory Compliance Through Enterprise Architecture & Business Process Modeling Software

A North American banking group is using erwin Evolve to integrate information across the organization and provide better governance to boost business agility. Developing a shared repository was key to aligning IT systems to accomplish business strategies, reducing the time it takes to make decisions, and accelerating solution delivery.

It also operationalizes and governs mission-critical information by making it available to the wider enterprise at the right levels to identify synergies and ensure the appropriate collaboration.

EA and BP modeling are both critical for risk management and regulatory compliance, a major concern for financial services customers like the one above when it comes to ever-changing regulations on money laundering, fraud and more. erwin helps model, manage and transform mission-critical value streams across industries, as well as identify sensitive information.

Additionally, when thousands of employees need to know what compliance processes to follow, such as those associated with regulations like the General Data Protection Regulation (GDPR), ensuring not only access to proper documentation but current, updated information is critical.

The Advantages of Enterprise Architecture & Business Process Modeling from erwin

The power to adapt the EA/BP platform leads global giants in critical infrastructure, financial services, healthcare, manufacturing and pharmaceuticals to deploy what is now erwin Evolve for both EA and BP use cases. Its unique advantages are:

  • Integrated, Web-Based Modeling & Diagramming: Harmonize EA/BP capabilities with a robust, flexible and web-based modeling and diagramming interface easy for all stakeholders to use.
  • High-Performance, Scalable & Centralized Repository: See an integrated set of views for EA and BP content in a central, enterprise-strength repository capable of supporting thousands of global users.
  • Configurable Platform with Role-Based Views: Configure the metamodel, frameworks and user interface for an integrated, single source of truth with different views for different stakeholders based on their roles and information needs.
  • Visualizations & Dashboards: View mission-critical data in the central repository in the form of user-friendly automated visualizations, dashboards and diagrams.
  • Third-Party Integrations: Synchronize data with such enterprise applications as CAST, Cloud Health, RSA Archer, ServiceNow and Zendesk.
  • Professional Services: Tap into the knowledge of our veteran EA and BP consultants for help with customizations and integrations, including support for ArchiMate.

erwin Evolve 2020’s specific enhancements include web-based diagramming for non-IT users, stronger document generation and analytics, TOGAF support, improved modeling and navigation through inferred relationships, new API extensions, and modular packaging so customers can choose the components that best meet their needs.

erwin Evolve is also part of the erwin EDGE with data modeling, data catalog and data literacy capabilities for overall data intelligence.

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Business Process Can Make or Break Data Governance

Data governance isn’t a one-off project with a defined endpoint. It’s an on-going initiative that requires active engagement from executives and business leaders.

Data governance, today, comes back to the ability to understand critical enterprise data within a business context, track its physical existence and lineage, and maximize its value while ensuring quality and security.

Free Data Modeling Best Practice Guide

Historically, little attention has focused on what can literally make or break any data governance initiative — turning it from a launchpad for competitive advantage to a recipe for disaster. Data governance success hinges on business process modeling and enterprise architecture.

To put it even more bluntly, successful data governance* must start with business process modeling and analysis.

*See: Three Steps to Successful & Sustainable Data Governance Implementation

Business Process Data Governance

Passing the Data Governance Ball

For years, data governance was the volleyball passed back and forth over the net between IT and the business, with neither side truly owning it. However, once an organization understands that IT and the business are both responsible for data, it needs to develop a comprehensive, holistic strategy for data governance that is capable of four things:

  1. Reaching every stakeholder in the process
  2. Providing a platform for understanding and governing trusted data assets
  3. Delivering the greatest benefit from data wherever it lives, while minimizing risk
  4. Helping users understand the impact of changes made to a specific data element across the enterprise.

To accomplish this, a modern data governance strategy needs to be interdisciplinary to break down traditional silos. Enterprise architecture is important because it aligns IT and the business, mapping a company’s applications and the associated technologies and data to the business functions and value streams they enable.

Ovum Market Radar: Enterprise Architecture

The business process and analysis component is vital because it defines how the business operates and ensures employees understand and are accountable for carrying out the processes for which they are responsible. Enterprises can clearly define, map and analyze workflows and build models to drive process improvement, as well as identify business practices susceptible to the greatest security, compliance or other risks and where controls are most needed to mitigate exposures.

Slow Down, Ask Questions

In a rush to implement a data governance methodology and system, organizations can forget that a system must serve a process – and be governed/controlled by one.

To choose the correct system and implement it effectively and efficiently, you must know – in every detail – all the processes it will impact. You need to ask these important questions:

  1. How will it impact them?
  2. Who needs to be involved?
  3. When do they need to be involved?

These questions are the same ones we ask in data governance. They involve impact analysis, ownership and accountability, control and traceability – all of which effectively documented and managed business processes enable.

Data sets are not important in and of themselves. Data sets become important in terms of how they are used, who uses them and what their use is – and all this information is described in the processes that generate, manipulate and use them. So unless we know what those processes are, how can any data governance implementation be complete or successful?

Processes need to be open and shared in a concise, consistent way so all parts of the organization can investigate, ask questions, and then add their feedback and information layers. In other words, processes need to be alive and central to the organization because only then will the use of data and data governance be truly effective.

A Failure to Communicate

Consider this scenario: We’ve perfectly captured our data lineage, so we know what our data sets mean, how they’re connected, and who’s responsible for them – not a simple task but a massive win for any organization. Now a breach occurs. Will any of the above information tell us why it happened? Or where? No! It will tell us what else is affected and who can manage the data layer(s), but unless we find and address the process failure that led to the breach, it is guaranteed to happen again.

By knowing where data is used – the processes that use and manage it – we can quickly, even instantly, identify where a failure occurs. Starting with data lineage (meaning our forensic analysis starts from our data governance system), we can identify the source and destination processes and the associated impacts throughout the organization.

We can know which processes need to change and how. We can anticipate the pending disruptions to our operations and, more to the point, the costs involved in mitigating and/or addressing them.

But knowing all the above requires that our processes – our essential and operational business architecture – be accurately captured and modelled. Instituting data governance without processes is like building a castle on sand.

Rethinking Business Process Modeling and Analysis

Modern organizations need a business process modeling and analysis tool with easy access to all the operational layers across the organization – from high-level business architecture all the way down to data.

Such a system should be flexible, adjustable, easy-to-use and capable of supporting multiple layers simultaneously, allowing users to start in their comfort zones and mature as they work toward their organization’s goals.

The erwin EDGE is one of the most comprehensive software platforms for managing an organization’s data governance and business process initiatives, as well as the whole data architecture. It allows natural, organic growth throughout the organization and the assimilation of data governance and business process management under the same platform provides a unique data governance experience because of its integrated, collaborative approach.

Start your free, cloud-based trial of erwin Business Process and see how some of the world’s largest enterprises have benefited from its centralized repository and integrated, role-based views.

We’d also be happy to show you our data governance software, which includes data cataloging and data literacy capabilities.

Enterprise Architecture Business Process Trial

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Internal Business Process Modeling: The Secret Behind Exponential Organizations

Strong internal business process modeling and management helps data-driven organizations compete and lead

In short, an internal business process is a documented account of how things should be done to maximize efficiency and achieve a particular goal.

In the book “Exponential Organizations” by Salim Ismail, Michael S. Malone and Yuri van Geest, the authors, examine how every company is or will evolve into an information-based entity in which costs fall to nearly zero, abundance replaces scarcity and only “exponential organizations” survive.

It’s not news that exponential organizations like Uber, Airbnb and Netflix have flipped the script on disrupting traditional industries like taxis, hotels and video rentals/TV viewing.

But now, even traditional industries like healthcare and financial services, which were historically slow to innovate, are transforming at breakneck speed.

Let’s face it, in today’s hyper-competitive markets, the traditional approach of relying on legacy strengths or inertia for survival just simply won’t work.

The days of enterprises focusing almost exclusively on rigid structures, centralized management and accountability; concentrated knowledge; service mainly to external customers; and reactive, short-term strategy alignment driven mainly by massive-scale projects are antiquated.

The information within your organization’s internal business processes is where the data your company collects, creates, stores and analyzes actually transforms into something that makes your company go, hopefully for the long haul.

Internal Business Process Modeling - Exponential Organizations

The Value of Internal Business Process Modeling

Organizations are built on a series of internal business processes. The complexity of modern data-driven organizations requires processes to work in tandem to create and sustain value.

The degree to which any individual internal business process drives value can vary, but even the most seemingly mundane processes are part of a collective sum, greater than its parts.

Therefore, it’s critical for organizations to map their internal business processes to understand how a given action relates to the organizations’ overall strategy and goals.

Such knowledge is at the core of exponential organizations. They understand how any given internal business process relates to value creation, making it far easier to assess what’s currently working but also identify areas for improvement as well as the potential for competitive differentiation.

Exponential organizations also are better positioned to respond and adapt to disruptive forces, such as 5G. This is because understanding what and how you do things now makes it easier to implement change in an agile manner.

5G Roadmap: Preparing Your Enterprise Architecture

How do you join the ranks of exponential organizations? And where do you begin your journey to becoming an information-based entity?

Attitude Adjustment

More and more organizations are realizing they need to adjust their traditional thinking and subsequent actions, even if just a bit, to gain strategic advantage, reduce costs and retain market dominance. For example:

  1. Structures are becoming more adaptable, allowing for greater flexibility and cost management. How is this possible and why now? Organizations are grasping that effective, well-managed and documented internal business processes should form their operational backbones.
  2. Business units and the departments within them are becoming accountable not only for their own budgets but also on how well they achieve their goals. This is possible because their responsibilities and processes can be clearly defined, documented and then monitored to ensure their work is executed in a repeatable, predictable and measurable way.
  3. Knowledge is now both centralized and distributed thanks to modern knowledge management systems. Central repositories and collaborative portals give everyone within the organization equal access to the data they need to do their jobs more effectively and efficiently.
  4. And thanks to all the above, organizations can expand their focus from external customers to internal ones as well. By clearly identifying individual processes (and their cross-business handover points) and customer touchpoints, organizations can interact with any customer at the right point with the most appropriate resources.

Benefits of Internal Business Process Modeling and Management

One of the main benefits of a process-based organizational engine is that it should be able to better handle outside pressures, such as new regulations, if they are – or are becoming – truly process-based. Because once processes (and their encompassing business architecture) become central to the organization, a wide array of things become simpler, faster and cheaper.

Another benefit is application design – the holy grail or black hole of budgetary spending and project management, depending on your point of view – is streamlined, with requirements clearly gathered and managed in perfect correspondence to the processes they serve and with the data they manage clearly documented and communicated to the developers.

Testing occurs against real-life scenarios by the responsible parties as documented by the process owners – a drastic departure from the more traditional approaches in which the responsibility fell to designated, usually technical application owners.

Finally – and most important – data governance is no longer the isolated domain of data architects but central to the everyday processes that make an organization tick. As processes have stakeholders who use information – data – the roles of technical owners and data stewards become integral to ensuring processes operate efficiently, effectively and – above all – without interruptions. On the other side of this coin, data owners and data stewards no longer operate in their own worlds, distant from the processes their data supports.

Carpe Process

All modern organizations should seize business process as a central component to their operations. Data governance as well, and cost management becoming a third driver for the enterprise machine. But as we all know, it takes more than stable connecting rods to make an engine work – it needs cogs and wheels, belts and multiple power sources, all working together.

In the traditional organization, people are the internal mechanics. These days, powerful and flexible workflow engines provide much-needed automation for greater visibility plus more power, stability and quality – all the things a machine needs to operate as required/designed.

Advanced process management systems are becoming essential, not optional. And while not as sexy or attention-grabbing as other technologies, they provide the power to drive an organization toward its goals quickly, cost-effectively and efficiently.

To learn how erwin can empower a modern, process-based organization, please click here.

Enterprise Architecture Business Process Trial

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Constructing a Digital Transformation Strategy: Putting the Data in Digital Transformation

Having a clearly defined digital transformation strategy is an essential best practice for successful digital transformation. But what makes a digital transformation strategy viable?

Part Two of the Digital Transformation Journey …

In our last blog on driving digital transformation, we explored how business architecture and process (BP) modeling are pivotal factors in a viable digital transformation strategy.

EA and BP modeling squeeze risk out of the digital transformation process by helping organizations really understand their businesses as they are today. It gives them the ability to identify what challenges and opportunities exist, and provides a low-cost, low-risk environment to model new options and collaborate with key stakeholders to figure out what needs to change, what shouldn’t change, and what’s the most important changes are.

Once you’ve determined what part(s) of your business you’ll be innovating — the next step in a digital transformation strategy is using data to get there.

Digital Transformation Examples

Constructing a Digital Transformation Strategy: Data Enablement

Many organizations prioritize data collection as part of their digital transformation strategy. However, few organizations truly understand their data or know how to consistently maximize its value.

If your business is like most, you collect and analyze some data from a subset of sources to make product improvements, enhance customer service, reduce expenses and inform other, mostly tactical decisions.

The real question is: are you reaping all the value you can from all your data? Probably not.

Most organizations don’t use all the data they’re flooded with to reach deeper conclusions or make other strategic decisions. They don’t know exactly what data they have or even where some of it is, and they struggle to integrate known data in various formats and from numerous systems—especially if they don’t have a way to automate those processes.

How does your business become more adept at wringing all the value it can from its data?

The reality is there’s not enough time, people and money for true data management using manual processes. Therefore, an automation framework for data management has to be part of the foundations of a digital transformation strategy.

Your organization won’t be able to take complete advantage of analytics tools to become data-driven unless you establish a foundation for agile and complete data management.

You need automated data mapping and cataloging through the integration lifecycle process, inclusive of data at rest and data in motion.

An automated, metadata-driven framework for cataloging data assets and their flows across the business provides an efficient, agile and dynamic way to generate data lineage from operational source systems (databases, data models, file-based systems, unstructured files and more) across the information management architecture; construct business glossaries; assess what data aligns with specific business rules and policies; and inform how that data is transformed, integrated and federated throughout business processes—complete with full documentation.

Without this framework and the ability to automate many of its processes, business transformation will be stymied. Companies, especially large ones with thousands of systems, files and processes, will be particularly challenged by taking a manual approach. Outsourcing these data management efforts to professional services firms only delays schedules and increases costs.

With automation, data quality is systemically assured. The data pipeline is seamlessly governed and operationalized to the benefit of all stakeholders.

Constructing a Digital Transformation Strategy: Smarter Data

Ultimately, data is the foundation of the new digital business model. Companies that have the ability to harness, secure and leverage information effectively may be better equipped than others to promote digital transformation and gain a competitive advantage.

While data collection and storage continues to happen at a dramatic clip, organizations typically analyze and use less than 0.5 percent of the information they take in – that’s a huge loss of potential. Companies have to know what data they have and understand what it means in common, standardized terms so they can act on it to the benefit of the organization.

Unfortunately, organizations spend a lot more time searching for data rather than actually putting it to work. In fact, data professionals spend 80 percent of their time looking for and preparing data and only 20 percent of their time on analysis, according to IDC.

The solution is data intelligence. It improves IT and business data literacy and knowledge, supporting enterprise data governance and business enablement.

It helps solve the lack of visibility and control over “data at rest” in databases, data lakes and data warehouses and “data in motion” as it is integrated with and used by key applications.

Organizations need a real-time, accurate picture of the metadata landscape to:

  • Discover data – Identify and interrogate metadata from various data management silos.
  • Harvest data – Automate metadata collection from various data management silos and consolidate it into a single source.
  • Structure and deploy data sources – Connect physical metadata to specific data models, business terms, definitions and reusable design standards.
  • Analyze metadata – Understand how data relates to the business and what attributes it has.
  • Map data flows – Identify where to integrate data and track how it moves and transforms.
  • Govern data – Develop a governance model to manage standards, policies and best practices and associate them with physical assets.
  • Socialize data – Empower stakeholders to see data in one place and in the context of their roles.

The Right Tools

When it comes to digital transformation (like most things), organizations want to do it right. Do it faster. Do it cheaper. And do it without the risk of breaking everything. To accomplish all of this, you need the right tools.

The erwin Data Intelligence (DI) Suite is the heart of the erwin EDGE platform for creating an “enterprise data governance experience.” erwin DI combines data cataloging and data literacy capabilities to provide greater awareness of and access to available data assets, guidance on how to use them, and guardrails to ensure data policies and best practices are followed.

erwin Data Catalog automates enterprise metadata management, data mapping, reference data management, code generation, data lineage and impact analysis. It efficiently integrates and activates data in a single, unified catalog in accordance with business requirements. With it, you can:

  • Schedule ongoing scans of metadata from the widest array of data sources.
  • Keep metadata current with full versioning and change management.
  • Easily map data elements from source to target, including data in motion, and harmonize data integration across platforms.

erwin Data Literacy provides self-service, role-based, contextual data views. It also provides a business glossary for the collaborative definition of enterprise data in business terms, complete with built-in accountability and workflows. With it, you can:

  • Enable data consumers to define and discover data relevant to their roles.
  • Facilitate the understanding and use of data within a business context.
  • Ensure the organization is fluent in the language of data.

With data governance and intelligence, enterprises can discover, understand, govern and socialize mission-critical information. And because many of the associated processes can be automated, you reduce errors and reliance on technical resources while increasing the speed and quality of your data pipeline to accomplish whatever your strategic objectives are, including digital transformation.

Check out our latest whitepaper, Data Intelligence: Empowering the Citizen Analyst with Democratized Data.

Data Intelligence: Empowering the Citizen Analyst with Democratized Data

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Business Architecture and Process Modeling for Digital Transformation

At a fundamental level, digital transformation is about further synthesizing an organization’s operations and technology, so involving business architecture and process modeling is a best practice organizations cannot ignore.

This post outlines how business architecture and process modeling come together to facilitate efficient and successful digital transformation efforts.

Business Process Modeling: The First Step to Giving Customers What They Expect

Salesforce recently released the State of the Connected Customer report, with 75 percent of customers saying they expect companies to use new technologies to create better experiences. So the business and digital transformation playbook has to be updated.

These efforts must be carried out with continuous improvement in mind. Today’s constantly evolving business environment totally reinforces the old adage that change is the only constant.

Even historically reluctant-to-change banks now realize they need to innovate, adopting digital transformation to acquire and retain customers. Innovate or die is another adage that holds truer than ever before.

Fidelity International is an example of a successful digital transformation adopter and innovator. The company realized that different generations want different information and have distinct communication preferences.

For instance, millennials are adept at using digital channels, and they are the fastest-growing customer base for financial services companies. Fidelity knew it needed to understand customer needs and adapt its processes around key customer touch points and build centers of excellence to support them.

Business architecture and process modeling

Business Architecture and Process Modeling

Planning and working toward a flexible, responsive and adaptable future is no longer enough – the modern organization must be able to visualize not only the end state (the infamous and so-elusive “to-be”) but also perform detailed and comprehensive impact analysis on each scenario, often in real time. This analysis also needs to span multiple departments, extending beyond business and process architecture to IT, compliance and even HR and legal.

The ability of process owners to provide this information to management is central to ensuring the success of any transformation initiative. And new requirements and initiatives need to be managed in new ways. Digital and business transformation is about being able to do three things at the same time, all working toward the same goals:

  • Collect, document and analyze requirements
  • Establish all information layers impacted by the requirements
  • Develop and test the impact of multiple alternative scenarios

Comprehensive business process modeling underpins all of the above, providing the central information axis around which initiatives are scoped, evaluated, planned, implemented and ultimately managed.

Because of its central role, business process modeling must expand to modeling information from other layers within the organization, including:

  • System and application usage information
  • Supporting and reference documentation
  • Compliance, project and initiative information
  • Data usage

All these information layers must be captured and modeled at the appropriate levels, then connected to form a comprehensive information ecosystem that enables parts of the organization running transformation and other initiatives to instantly access and leverage it for decision-making, simulation and scenario evaluation, and planning, management and maintenance.

No Longer a Necessary Evil

Traditionally, digital and business transformation initiatives relied almost exclusively on human knowledge and experience regarding processes, procedures, how things worked, and how they fit together to provide a comprehensive and accurate framework. Today, technology can aggregate and manage all this information – and more – in a structured, organized and easily accessible way.

Business architecture extends beyond simple modeling; it also incorporates automation to reduce manual effort, remove potential for error, and guarantee effective data governance – with visibility from strategy all the way down to data entry and the ability to trace and manage data lineage. It requires robotics to cross-reference mass amounts of information, never before integrated to support effective decision-making.

The above are not options that are “nice to have,” but rather necessary gateways to taking business process management into the future. And the only way to leverage them is through systemic, organized and comprehensive business architecture modeling and analysis.

Therefore, business architecture and process modeling are no longer a necessary evil. They are critical success factors to any digital or business transformation journey.

A Competitive Weapon

Experts confirm the need to rethink and revise business processes to incorporate more digital automation. Forrester notes in its report, The Growing Importance of Process to Digital Transformation, that the changes in how business is conducted are driving the push “to reframe organizational operational processes around digital transformation efforts.” In a dramatic illustration of the need to move in this direction, the research firm writes that “business leaders are looking to use process as a competitive weapon.”

If a company hasn’t done a good job of documenting its processes, it can’t realize a future in which digital transformation is part of everyday operations. It’s never too late to start, though. In a fast-moving and pressure cooker business environment, companies need to implement business process models that make it possible to visually and analytically represent the steps that will add value to the company – either around internal operations or external ones, such as product or service delivery.

erwin BP, part of the erwin EDGE Platform, enables effective business architecture and process modeling. With it, any transformation initiative becomes a simple, streamlined exercise to support distributed information capture and management, object-oriented modeling, simulation and collaboration.

To find out about how erwin can help in empowering your transformation initiatives, please click here.

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Enterprise Architect: A Role That Keeps Evolving

Enterprise architect is a common job title within IT organizations at large companies, but the term lacks any standard definition. Ask someone on the business side what their organization’s enterprise architects do, and you’ll likely get a response like, “They work with IT,” which is true, but also pretty vague.

What the enterprise architects at your organization do depends in large part on how the IT department is organized. At some organizations, enterprise architects work closely with the software applications in a role that some might refer to as a solution architect.

In other organizations, the role of enterprise architect might carry more traditional IT responsibilities around systems management. Other enterprise architects, especially at large organizations, might specialize in exploring how emerging technologies can be tested and later integrated into the business.

Technology research and advisory firm Gartner predicts that enterprise architects will increasingly move into an internal consultancy function within large organizations. While this use of the role is not currently widespread, it’s easy to see how it could make sense for some businesses.

If, for example, a business sets a goal to increase its website sales by 20 percent in one year’s time, meeting that goal will require that different IT and business functions work together.

The business side might tackle changes to the marketing plan and collect data about website visitors and shoppers, but ultimately they will need to collaborate with someone on the technology side to discuss how IT can help reach that goal. And that’s where an enterprise architect in the role of an internal consultant comes into play.

Each business is going to organize its enterprise architects in a way that best serves the organization and helps achieve its goals.

That’s one of the reasons the enterprise architect role has no standard definition. Most teams consist of members with broad IT experience, but each member will often have some role-specific knowledge. One team member might specialize in security, for example, and another in applications.

Like the tech industry in general, the only constant in enterprise architecture is change. Roles and titles will continue to evolve, and as the business and IT sides of the organization continue to come together in the face of digital transformation, how these teams are organized, where they report, and the types of projects they focus on are sure to change over time.

Enterprise integration architect is one role in enterprise architecture that’s on the rise. These architects specialize in integrating the various cloud and on-premise systems that are now common in the hybrid/multi-cloud infrastructures powering the modern enterprise.

Enterprise Architect: A Role That Keeps Evolving

For the Enterprise Architect, Business Experience Becomes a Valuable Commodity

Regardless of the specific title, enterprise architects need the ability to work with both their business and IT colleagues to help improve business outcomes. As enterprise architecture roles move closer to the business, those with business knowledge are becoming valuable assets. This is especially true for industry-specific business knowledge.

As industry and government compliance regulations, for example, become part of the business fabric in industries like financial services, healthcare and pharmaceuticals, many enterprise architects are developing specializations in these industries that demonstrate their understanding of the business and IT sides of these regulations.

This is important because compliance permeates every area of many of these organizations, from the enterprise architecture to the business processes, and today it’s all enabled by software. Compliance is another area where Gartner’s internal consultancy model for enterprise architects could benefit a number of organizations. The stakes are simply too high to do anything but guarantee all of your processes are compliant.

Enterprise architect is just one role in the modern organization that increasingly stands with one foot on the business side and the other in IT. As your organization navigates its digital transformation, it’s important to use tools that can do the same.

erwin, Inc.’s industry-leading tools for enterprise architecture and business process modeling use a common repository and role-based views, so business users, IT users and those who straddle the line have the visibility they need. When everyone uses the same tools and the same data, they can speak the same language, collaborate more effectively, and produce better business outcomes. That’s something the whole team can support, regardless of job title.

Business Process Modeling Use Cases

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Enterprise Architecture and Business Process: Common Goals Require Common Tools

For decades now, the professional world has put a great deal of energy into discussing the gulf that exists between business and IT teams within organizations.

They speak different languages, it’s been said, and work toward different goals. Technology plans don’t seem to account for the reality of the business, and business plans don’t account for the capabilities of the technology.

Data governance is one area where business and IT never seemed to establish ownership. Early attempts at data governance treated the idea as a game of volleyball, passing ownership back and forth, with one team responsible for storing data and running applications, and one responsible for using the data for business outcomes.

Today, we see ample evidence this gap is closing at many organizations. Consider:

  • Many technology platforms and software applications now are designed for business users. Business intelligence is a prime example; it’s rare today to see IT pros have to run reports for business users thanks to self-service.
  • Many workers, especially those that came of age surrounded by technology, have a better understanding of both the business and technology that runs their organizations. Education programs also have evolved to help students develop a background in both business and technology.
  • There’s more portability in roles, with technology minds moving to business leadership positions and vice versa.

“The business domain has always existed in enterprise architecture,” says Manuel Ponchaux, director of product management at erwin, Inc. “However, enterprise architecture has traditionally been an IT function with a prime focus on IT. We are now seeing a shift with a greater focus on business outcomes.”

You can see evidence of this blended focus in some of the titles, like “business architect,” being bestowed upon what was traditionally at IT function. These titles demonstrate an understanding that technology cannot exist in the modern organization for the sake of technology alone – technology needs to support the business and its customers. This concept is also a major focus of the digital transformation wave that’s washing over the business world, and thus we see it reflected in job titles that simply didn’t exist a decade ago.

Job titles aside, enterprise architecture (EA) and business process (BP) teams still have different goals, though at many organizations they now work more closely together than they did in the past. Today, both EA and BP teams recognize that their common goal is better business outcomes. Along the way to that goal, each team conducts a number of similar tasks.

Enterprise Architecture and Business Process: Better Together

One prominent example is modeling. Both enterprise architecture and business process teams do modeling, but they do it in different ways at different levels, and they often use different data and tools. This lack of coordination and communication makes it difficult to develop a true sense of a process from the IT and business sides of the equation. It can also lead to duplication of efforts, which is inefficient and likely to add further confusion when trying to understand outcomes.

Building better business outcomes is like following a plan at a construction site. If different teams are making their own decisions about the materials they’re going to use and following their own blueprints, you’re unlikely to see the building you expect to see at the end of the job.

And that’s essentially what is missing at many organizations: A common repository with role-based views, interfaces and dashboard so that enterprise architecture and business process can truly work together using the same blueprint. When enterprise architecture and business process can use common tools that both aid collaboration and help them understand the elements most important to their roles, the result is greater accuracy, increased efficiency and improved outcomes.

erwin’s enterprise architecture and business process tools provide the common repository and role-based views that help these teams work collaboratively toward their common goals. Finally, enterprise architecture and business process can be on the same page.

Business Process Modeling Use Cases

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Business Process Modeling Use Cases and Definition

What is business process modeling (BPM)? A visual representation of what your business does and how it does it. Why is having this picture important?

According to Gartner, BPM links business strategy to IT systems development to ensure business value. It also combines process/ workflow, functional, organizational and data/resource views with underlying metrics such as costs, cycle times and responsibilities to provide a foundation for analyzing value chains, activity-based costs, bottlenecks, critical paths and inefficiencies.

Every organization—particularly those operating in industries where quality, regulatory, health, safety or environmental issues are a concern—must have a complete understanding of its processes. Equally important, employees must fully comprehend and be accountable for appropriately carrying out the processes for which they are responsible.

BPM allows organizations to benefit from an easily digestible visualization of its systems and the associated information. It makes it easier to be agile and responsive to changes in markets and consumer demands,

This is because the visualization process galvanizes an organization’s ability to identify areas of improvement, potential innovation and necessary reorganization.

But a theoretical understanding of business process modeling will only get you so far. The following use cases demonstrate the benefits of business process modeling in real life.

Business process modeling (BPM) is a practice that helps organizations understand how their strategy relates to their IT systems and system development.

Business Process Modeling Use Cases

Compliance:

Regulations like the E.U.’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) are requiring 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).

The visualization process can aid in an organization’s ability to understand the security risks associated with a particular process. It also means that should a breach occur, the organization’s greater understanding of its processes and related systems means they can respond with greater agility, mitigate the damage and quickly inform affected parties as required specifically by GDPR.

In the case of an audit, BPM can be used to demonstrate that the organization is cognizant of compliance standards and is doing what is required.

This also extends to industry-specific other compliance mandates  such as those in healthcare, pharmaceutical and the financial services industries.

The Regulatory Rationale for Integrating Data Management & Data Governance

The Democratization of Information:

Increasing an organizations ability to retain knowledge is another cross-industry use case for business process modeling. This use case benefits organizations in two key areas:

1. Democratization of information.

By documenting processes, organizations can ensure that knowledge and information is de-siloed and that the organization as a whole can benefit from it. In this case, a key best practice to consider is the introduction of role/user-based access. This way an organization can ensure only the necessary parties can access such information and ensure they are in keeping with compliance standards.

2. Knowledge retention.

By documenting processes and democratizing information, process-specific knowledge can be retained, even when key employees leave. This is particularly important in the case of an aging workforce, where an organization could suffer a “brain drain” as large numbers of employees retire during a short span of time.

Digital Transformation:

Once in a while, a technological revolution turns the nature of business on its head. The most recent and arguably most significant of which – although at this point it’s hard to argue – is the rise of data-driven businesses.

In a relatively short amount of time, the leaders in data-driven businesses were launched and stormed their way to the forefront of their respective industries – think Amazon, Netflix and Uber.

The result? Data is now considered more valuable than oil and industries across the board are seeing digital transformation en masse.

There’s a clear connection between business process modeling and digital transformation initiatives. With it, an organization can explore models to understand information assets within a business context, from internal operations to full customer experiences.

This practice identifies and drives digital transformation opportunities to increase revenue while limiting risks and avoiding regulatory and compliance gaffes.

Organizations that leverage BPM in their digital transformation efforts can use their greater

understanding of their current processes to make more informed decisions about future implementations.

And the use cases for business process modeling don’t stop there.

A better understanding of your organizations processes can also ease software deployments and make mergers and acquisitions (M&A) far easier to handle. Large organizations grow through M&A activity, and the combining of business processes, software applications and infrastructure when two organizations become one is very complex.

Business process modeling offers visibility into existing processes and helps design new processes that will deliver results in a post-merger environment.

The latest guide from the erwin Experts expands on these use cases and details how best to use business process modeling to tame your organization’s complexity and maximize its potential and profits.

Business Process Modeling Use Cases