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.
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.
