Data is increasingly viewed as a strategic asset with real revenue impact for businesses of every size. A 2016 Capgemini survey found 61% of executives surveyed felt big data was a driver of revenue and was as valuable to their bottom line as the products or services they sell. Additionally, 65% of the surveyed executives felt they risked becoming irrelevant or uncompetitive if they failed to embrace big data.
As data occupies a more prominent position in corporate strategy, so too must the capabilities that enable businesses to effectively capture, transform and access that data; and it starts with data integration. Julie Hunt, author of the blog Highly Competitive, astutely points out in a recent post that “Data integration must be pursued as a strategic function that aligns with business objectives.” No longer can integration be addressed as a future or second-phase initiative, it must be considered at the beginning of a project. Otherwise, users risk implementing solutions that are inefficient or, worse yet, completely ineffective.
This rise of data integration as a strategic function correlates to the rise of cloud applications. Cloud applications have fundamentally shifted application implementation by making it quick and easy to deploy new functions across the enterprise with little investment or IT support. It has allowed enterprises to seek the best solution for a particular need rather than having to employ a “one application fits most” mentality. The result is often a best-in-class approach where companies surround a few core applications with specialty applications to improve their agility and real-time decision making.
To realize the desired benefits, however, enterprises must form a strategic approach to integration—one that can first and foremost address hybrid (on-premises and cloud) environments, so they can effectively manage an array of loosely coupled applications. The strategy, as Gartner observes, cannot be to rely on the application vendors alone to take care of it, particularly in ERP. This naïve approach will leave companies struggling to integrate applications at the last minute. Moreover, the strategy must be founded on the notion that the enterprise will have expanded its data-integration needs as it grows, so the infrastructure and people strategy needs to solve for these issues from the outset. They should plan for the fact that nonintegration specialists must do some of the work.
Recognizing the growing strategic importance of data integration, many SaaS vendors expanded the connectivity they offer out of the box. Often, how well an application integrates with other cloud and on-premises applications will determine whether a business chooses it. SaaS vendors now understand that having built-in data integration adds value to their solution; many offer connectors and APIs to improve connectivity.
So, if vendors are expanding their data-integration capabilities, why can’t companies rely on them to address their integration needs? New applications continue to outpace SaaS integration capabilities. The Internet of Things (IoT) promises to further accelerate this frenetic pace of innovation, making it harder and harder for SaaS vendors to innovate while keeping up with all the possible integration points. As a result, businesses need a comprehensive integration strategy that will allow customer-facing teams to change applications, fields and aggregations with ease.
Choosing an integration strategy is not a “one and done” activity. It’s a process that evolves over time and may include many different approaches to meet the needs of the organization from a functional, time and budget perspective. In thinking about the most appropriate integration strategy, companies should consider a few important points:
- Life-cycle-management costs: Before crafting an integration strategy, consider how many SaaS applications will be in use across the company. Companies with many SaaS applications may benefit from using an integration platform that provides a single point of control for their applications and integration developers. The platform vendor takes responsibility for ensuring compatibility with the applications it supports, eliminating the need for the company to dedicate resources to updating integrations in response to API changes made by SaaS vendors. It also facilitates changing systems. For example, if a company switches CRM systems, the move is almost seamless with an integration platform. The company simply connects the new CRM system to the integration platform and the platform vendor ensures the integration works for supported applications. Without the platform, the company would need to reintegrate all of its SaaS applications with the new CRM system individually. A platform streamlines and automates the process, reducing overall life-cycle-management costs.
- Custom application deployments: Sometimes the fastest way to integrate an application is by using the manufacturer’s integration capability to build custom extensions to the application. In pursuing this path, consider the likelihood of future changes to the application, as they will affect the integration and create rework. Consider adding a dedicated integration layer to create an abstraction layer, which allows the application to work without having to rebuild from scratch when there are changes.
- Field-level capabilities of integrations: All connectors are not created equal, so when considering an integration solution, companies should carefully consider not only which sources can be integrated, but which fields in those sources. Sometimes competitive differentiation lies in the specific information exchanged between two major systems.
- Business agility: Companies must consider how often they expect to change, add, and subtract applications and fields as well as orchestration steps between applications, because connectors provide differing levels of flexibility. That flexibility is proportional to the complexity of adapting the connector. If business users will be the primary integration managers, companies should consider a more fixed and less complex solution. If IT is the owner, a more flexible but more complex connector may be the right answer.
Most companies use a combination of strategies to address their data-integration needs. As data integration moves to the front line and becomes a major strategic function, companies must develop more-comprehensive approaches to its implementation and maintenance. The success of a company’s data strategy will be directly related to the success of its integration strategy. Getting the right data to the right people at the right time to make meaningful business decisions is a competitive advantage and can increase profitability.
About the Author
John Joseph is Vice President of Marketing at Scribe Software, where he is responsible for developing managing the company’s corporate-marketing, demand-generation, partner-marketing and product-marketing initiatives. Before joining Scribe, John was VP of Product Marketing at Lavastorm Analytics, where he managed the company’s launch into the BI/analytics software market. He holds a Bachelor of Science degree in electrical engineering from Massachusetts Institute of Technology (MIT), a Master of Science degree in electrical engineering from the University of Southern California, and a Master of Business Administration degree from MIT’s Sloan School of Management. In his spare time, John is an angler and coaches youth sports, including soccer, baseball and basketball.