Connecting Everything: 7 Integration Types in Digital Transformation

Digital transformations are not new to organizations, and many are in their third or fourth year of seeking competitive advantages with technology and data capabilities.

What does that mean in practice? For many organizations, digital transformations often require improving customer experiences, automating workflows, developing applications, and enabling a data-driven organization. CIOs seek to modernize applications while migrating to the cloud, while CDOs aim to institute proactive data governance, and all recognize the challenge of transformation management – the need to help employees in the organization to evolve workflows and adopt new technologies.

7 Integration Types in Digital Transformation by Isaac Sacolick

And what’s the glue that holds applications, workflows, and data flows together with the portfolio of SaaS, enterprise systems, proprietary applications, and third-party data sources? In a video I published last year, I shared three reasons integration should be a primary digital transformation platform. In this post, I share seven integration types that you’re likely to encounter when implementing many of the tech and data initiatives tied to digital transformation.

1. Connect Workflows Between SaaS and Enterprise Systems

In medium and large enterprises across industries, it’s common to see the ERP running across two or more data centers and a SaaS CRM used as a central hub for sales and marketing activities. In addition to these platforms, there’s likely a collection of other SaaS marketing tools, low-code applications, and data visualizations connecting data and supporting different workflows.

Who am I kidding? Chances are your medium or large enterprise supports multiple ERPs and CRMs, further complicating the integration challenges.

This is the most common integration use case, and enterprises leveraging a cloud-native, intelligent integration platform have the advantage of developing and evolving integrations across ERPs, CRMs, and the multitude of other apps used in employee workflows.

2. Expose and Manage APIs with API Gateways

Most organizations that build applications today adopt API-first strategies, and many develop microservice architectures. But experienced technology leaders know that developing software is only the first step, and getting adoption, supporting the code, and extending capabilities is the ongoing challenge.

API management is the practice of enabling a lifecycle around internal and externally accessible APIs. It includes capabilities such as versioning, cataloging, security, and authentication. Once API management is in place, architects and technology leaders can pursue API-led connectivity, an integration strategy to support experience, process, and system APIs.

3. Publish, Document, and Share Data Sources Across the Multicloud

Digital transforming organizations are not just building applications and integrating workflows. Becoming data-driven and democratizing access to data sources is a foundation transformation capability, and CIOs partnered with CDOs must consider the organization’s data management strategy, including data tools, platforms, processes, and governance.

That’s not trivial when most organizations operate hybrid clouds and target multicloud architectures. Data is in multiple locations, and a centralized data catalog helps streamline who gets access to what data sources and how analysts across the organization should use data in decision making.

 4. Integrate Entity Data into a Master Data Hub

The data catalog is only the first layer of publishing and sharing data access. To centralize, cleanse, and provide access to primary entity data such as customers, products, and suppliers, many organizations deploy a master data hub that acts as a centralized entity data resource.

Master data management is a simple concept that can be complex to explain to business stakeholders who view CRMs as the central repository for customer data and ERPs for product and supply chain data. They often miss that other systems manage additional profile and event data, and CRMs and ERPs are often less-optimal platforms to act as master hubs.   

For inspiration, check out how Cooke Aquaculture optimizes customer relationships or how Virtustream integrated ITSM data from ServiceNow, BMC Remedy, and other platforms.

5. Build a Customized Employee Experience in a Low-Code Platform

Architects often think of technology in layers and building blocks. With intelligent integration platforms and data catalogs in place, they provide a foundation for developing low-code apps that optimize employee experiences.

Employee onboarding is a classic example because “setting them up in the system” actually means having multiple administrators set them up in many systems. Often manually, slowly, and with delays frustrating the hiring manager and newly hired employees.

Need proof that employee onboarding can be differentiating in your industry? Check out how Moderna (biotech innovator), MOD Pizza (restaurant), and Lee Company (building services and construction) have all streamlined employee onboarding.

6. Streamline Processing of IoT and Real-Time Data Sources

Healthcare institutions must consider integrating real-time patient data from health tracking devices like the Fitbit, Garmin vivosmart, Apple Watch, and other wearable devices. Regulators need platforms to integrate data from real-time data sources, for example, an environmental regulator that captures data from sensors, drones, and satellite imagery.

More organizations need to rethink their integration platforms and strategies to support edge-to-core real-time data streaming capabilities that will power the next decade of innovation. These “emerging technologies” are graduating to mainstream status, and most industries that connect the physical and digital worlds will need to upgrade to real-time integrations.

 7. Accelerate M&A Integrations and Value Generation

My seventh integration type is common for many medium and large enterprises with mergers, acquisitions, and divestitures as part of their strategic programs. While many M&A integrations focus on integrating the financial, IT, and HR systems to “operate as one company,” many sales, marketing, operational, and fulfillment systems go untouched post-merger, and the technical debt can slowly decay to legacy system status.

Merging systems, workflows, and data is difficult and almost always takes longer than instrumenting the paper that inked the deal. But before merging systems, it is often beneficial and a best practice to find ways to connect and integrate workflows and data sources. Organizations that develop integration centers of excellence can find ways to generate value from M&A faster than peers that treat these integrations as custom projects.

So, in a world where there’s a significant advantage to organizations that accelerate digital transformation, connecting and integrating everything is a foundational platform to support ongoing innovation, automation, and adaptability. 

This post is brought to you by Boomi.

The views and opinions expressed herein are those of the author and do not necessarily represent the views and opinions of Boomi.

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