In today’s business world, collaboration is key, not only for humans, but also for systems. Business Process Integration is a distinct practice in itself that occurs when multiple business processes across multiple verticals work together to meet defined enterprise goals.
No organization can run on a single software stack and no stack has a workflow tool sophisticated enough to handle all of your needs. Data-linked integration or interoperability, i.e., drawing data from and sending data to other systems, is part and parcel of system-level integration.
ROUNDMAP™ could and should be perceived as the outcome of business process modeling, as it represents the processes of an enterprise that are involved with the customer development process. The mapping system not only involves an integration on a lateral level, i.e., the interconnected customer lifecycle, but also incorporates the vertical processes – all the way up to strategic management.
Key distinctions between process management and project management are repeatability and predictability. If the structure and sequence of work is unique, then it is a project. In business process management, a sequence of work can vary from instance to instance: there are gateways, conditions; business rules etc. The key is predictability: no matter how many forks in the road, we know all of them in advance, and we understand the conditions for the process to take one route or another. If this condition is met, we are dealing with a process.
Customer Data Platform
One of the key components required to succesfully integrate the customer creation and retention processes is a customer data platform (CDP). It is a type of packaged software which creates a persistent, unified prospects and customers database that is accessible to other systems. Data is pulled from multiple sources, cleaned and combined to create a single customer profile. This structured data is then made available to other systems. A CDP is GPPR-proof, because it isn’t storing anonymous visitor data, rather collects data from identified visitors, allowing the business to offer prospects and customers relevant information and personalized experiences, regardless of the channels used.
According to Gartner, customer data platforms have evolved from a variety of mature markets, including multichannel campaign management, tag management and data integration. Marketing leaders surveyed in Gartner’s 2017-2018 CMO Survey invested two-thirds of their budget in supporting customer retention and growth. With so many customers oscillating between phones, tablets, game consoles, desktops and laptops, many marketers are desperate for a unified view of the customer.
A Data Management Platform (DMP) collects anonymous web and digital data. CDPs collect data that is tied to an identifiable individual. Users of CDP can leverage the intelligence to provide more personalized content and delivery.
A data warehouse or data lake collects data, usually from the same source and with the same structure of information. While this information can be manually synthesized, neither type of system delivers the identity resolution needed to build a consolidated single customer view. Data warehouses are often updated at scheduled intervals whereas CDPs ingest and make available data in real time. In practice, most CDPs use the same technologies as data lakes; the difference is the CDP has built-in features to do additional processing to make the data usable, while a data lake may not.