Category: Topic 3 – Data / Information Architecture Layer

Enterprise Information Architecture Strategies for Enterprise Information-Sharing

As the key challenges and key trends show, information sharing is a broad concept that impacts all levels of the organization. According to Gartner (2008), the key topics that support the information-sharing age are:

  • Overcoming silos include case studies and strategies for business leaders and technical strategies for overcoming data barriers.
  • Improving integration includes strategies and techniques to improve data integration, the role of canonical models to improve interoperability, the emergence of data service platforms for cloud computing, and considerations on information security in the Digital Age.

At the insurance company I work, new data integration capabilities are central to enterprise information architecture (EIA) and there are two trends key trends influencing the strategy: the adoption of cloud technologies and the introduction of a SaaS-based policy administration system (PAS) that will exist in parallel with the legacy mainframe PAS, and (2) the desire to support underwriting with self-service analytics for data mining and discovery. These new capabilities include:

  • Integration Platform-as-a-Service (Mulesoft) used for real-time integration with cloud-based systems.
  • Logical Data Warehouses (LDW) which supports the data sharing and advanced analytics strategies.

The Mulesoft iPaaS was adopted after realizing that the existing enterprise service bus (ESB) was not sufficient to integrate with SaaS provider(s). This also came with a shift from an enterprise-centric mindset to the broader ecosystem of service providers.

The LDW is a pattern that relies on data federation and virtualization, rather than the traditional enterprise data warehouse (EDW) pattern that typically involves a centralized repository. Used in combination with real-time replication tools to feed cloud-based data sources into a group of data hubs that are conceptually aligned to the core enterprise data domains, which data analysts can access with self-service data analytics tools. The data is replicated as-is, so to increase the likelihood that users will be able to “catch a fish” from the “data lake”, metadata is provided to help interpret the data, and semantic data is provided to join ‘like’ data from the legacy and new policy systems. Furthermore, in the event more formal data integration is required, having the data staged helps speed up delivery of downstream reporting needs.

References:

Gartner Research Brief. 2008. Gartner Clarifies the Definition of the Term ‘Enterprise Architecture.’

Newman, D. & Gall, Nicholas. (2009, December 15). Architecting for Participation: How Information-Sharing Environments Overcome Information Silos. Retrieved from https://www.gartner.com/document/1256213.

Intelligent Business Process Management (iBPM) Tools are Key to Agile Operational Information

In Ten Steps to Build an Agile Information Architecture (Gartner, 2007), the authors state that “Service-oriented architecture (SOA) brings new challenges to the architecture and management of information. Some companies think that SOA will hide and resolve all their data issues; this belief will prove fatal to many SOA projects. SOA increases the importance of focusing on information management issues”.

In order to better manage this complexity, the best practice (Step 10) is to look both at the business process and the data that supports it. Tying the business process, roles, and information together provides a business context and helps to focus on the goals or outcomes of the process, allowing for better business services and information architectures.

The central issue is that most legacy business applications are siloed in terms of the ability to share information (and capabilities). If a business process or workflow spans multiple departments, information sources, and applications, then the users are often left to manage those processes with post-it notes, email, or custom exception reports used to identify, track and resolve issues that require manual workarounds.

On the other hand, Services Oriented Architecture (SOA) solutions, that is the services themselves, are transactional in nature or CRUD-based (i.e. Create, Read, Update, Delete). This is design pattern is great when, for example, the application is required to support multiple UX (e.g. web, mobile, etc.), or using service wrappers to share information from legacy applications. Likewise, when the business process or workflow spans multiple departments, information sources, and applications, these transactional systems fail to address the business context and specific goal, nor can they address the end-to-end enterprise value streams.

The good news is that these issues represent a great deal of opportunity, in terms of business transformation, in the form of business process optimization and automation. “In most organizations, more than half of all business processes are human-to-human, without the involvement of built or purchased applications. Therefore, in terms of business process improvement, this category of processes makes the most sense to tackle first. IT can assist business users by installing business process management (BPM) suites to help redesign these processes and make them more agile and effective” (Gartner, 2007).

In Magic Quadrant for Intelligent Business Process Management Suites, Gartner defines an intelligent business process management suite (iBPMS) as an integrated set of technologies that coordinate people, machines and things. It emphasizes:
* Support for real-time human collaboration, including integration with social media, mobile and cloud access to processes
* Advanced analytics, real-time activity monitoring and decision management for intelligent coordination and management of the interactions of process participants.

These iBPM systems are also combining BMP with AI and automation in a low-code development to put more power in the hands of the business users or citizen coders which is intended to improve stakeholder engagement and minimize resistance while support agility and faster time-to-market for digital transformation initiatives that seek to streamline processes across the business.

References:

Dunie, Rob, et al. ( 2017, October 24). Magic Quadrant for Intelligent Business Process Management Suites. www.gartner.com/doc/3410738/magic-quadrant-intelligent-business-process.