Large organizations such as Goldman Sachs rely on the timely and accurate execution of thousands of business processes, both manual and automated. Engineers have sought to implement systems that support many of these processes; however, the systems tend to be bespoke for a particular business, encoding “workflow” logic and more into a combination of server and client side code. This makes the data that represents concepts like breaks, tasks, and service calls extremely hard to connect horizontally across an organization. Furthermore, higher-level concepts like process oversight and control may have been implemented with localized views on custom datasets.
Colin White discusses Goldman Sachs’s industrialization program, under which it is digitizing processes, rules, and data in order to decrease cost, reduce time to market, and manage the risk of repetitive business processes. Goldman Sachs is taking models seriously. Its platforms use these models directly at runtime, and the data that is generated offers real insights into how to optimize its business. Formal modeling of processes, governance of firm-wide data taxonomies, and modeling of rules (and even of UI interactions) leads to both static and transactional datasets that can be fed into a data lake, where they can be analyzed and connected to other processes, enabling interesting questions to be asked that span multiple parts of the business.
This also leads to a huge degree of platform reuse—reducing time to market and driving up software development productivity. With the barrier to entry being incrementally lowered, processes that still rely heavily on email and other technologies can be systematically eliminated. With everything converging on its model driven platforms, reaching users through mobile devices is easier, and so on.
Colin White is a managing director and technology fellow within the Engineering division at Goldman Sachs. Colin is global head of the Workflow group within Enterprise Platforms, a core engineering group that builds services and capabilities to decrease time to market and drive the level of standardization across workflow-based applications firm-wide.
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