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Highlights
- Since the emergence of intelligent automation, organizations across sectors and geographies have delivered concrete results by embedding automation into their processes.
- Making business processes run smarter and faster is a great start, but intelligent automation has bigger potential.
- To successfully implement intelligent automation, enterprises must be visionary, results-oriented, and data-driven, while planning effective use of ecosystems and data democratization.
In this article
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IA’s potential
The potential of intelligent automation
Since its emergence, intelligent automation has provided endless ways for both traditional and digital businesses to become more effective and efficient. Organizations across sectors and geographies have delivered concrete results by embedding automation into their processes.
Yet only a few companies have been able to use automation to truly transform their businesses—to escape the gravitational influence of conventional methods and reach into the stratosphere. The reasons are myriad, and they include insufficient business engagement, poor planning, lack of focus on business outcomes and consumer context, or just not thinking big enough.
Intelligent automation, done the right way, provides a lot more opportunities than just “smart” and “fast.” Here are seven ways to super-power your automation journey. But be warned—you’ll have to leave the familiar behind.
Outcome-oriented
1. Stay focused on clear business outcomes
At the most fundamental level, enterprises must clearly articulate their desired outcomes for intelligent automation in terms of improving efficiency, scaling in a non-linear way, accelerating business decisions, or achieving something even more ambitious. They must also focus on the end game.
Here, the crucial element is staying on course with a vision locked in on outcomes. This requires a holistic, insights-driven view of all the factors that are tied to outcomes and performance trends benchmarked against best-in-class industry standards.
Visionary
2. Envision end-to-end automation
Most enterprises, due to their risk appetite, implement automation technology one singular joint at a time before moving to the next phase. This piecemeal implementation misses the opportunities that might be provided by intersections across multiple components, and it creates a lack of visibility and cohesion across the value stream.
For automation to be truly transformative, enterprises must take an end-to-end approach, ensuring that all automation components are working in continuity. This approach requires adopting an elevated mindset and looking across business silos with a goal of quick, successful process completions.
For example, it could mean looking across the entire order to cash (O2C) value chain—covering customer setup, inquiries, order receipt, billing, cash collections, and disputes—and making sure that all automation interventions are systematic, sequential, and cohesive. We worked with one global chemical organization to infuse intelligent automation across the O2C processes. The project led to improved order tracking and the prevention of order failures, which improved on-time order fulfillment from 71% to 93%.
Data-driven
3. Take a data-driven approach
Going 100% automation with full force is not feasible. The depth, intensity, and intervention points should be optimized. A successful automation program hinges on a data-driven approach that guides where and how much automation to apply. This type of approach provides a systematic way to assess both automation maturity and the impact of various automation levers on business results.
For example, we worked with a major utility player that was spending a significant amount of money on ombudsmen payments due to billing errors. A data-driven approach helped to identify the exact candidates for automation within the billing process, which led to a substantial reduction in errors and the corresponding penalties.
Ecosystems-oriented
4. Keep in mind the ecosystem play
To make the most of automation, businesses must look beyond their own enterprises and find ways to partner with academia, start-ups, and other established businesses. A purpose-led ecosystem acts as a gateway to collaboration across industries and institutions, and allows companies to access research and new use cases.
For example, travel companies can chalk out new revenue streams by analyzing behavioral and spending patterns to create customer segments. With that information, they might partner with financial institutions to offer personalized travel loans, credit cards, or currency exchange.
Flexible
5. Plan automation for configurability
At any point, an enterprise may need to change gears and move from one business model to another, one mode of the supply chain to another, one channel of customer onboarding to another, or one pricing structure to another (for example, premium to “freemium”). Enterprises should build the capability to incorporate modular changes that allow them to adapt to the fast-changing environment while business-as-usual continues. An ecosystem of plug-and-play, modular, and scalable digital solutions will help address these varying needs.
For instance, consider how automation might allow a manufacturing company to set up a configurable buying-channel selector—one that provides a quick way of switching the location, vendor, or ingredients being purchased based on changing market conditions. Or imagine how hyper-automation could create real-time business information and financial analysis for news providers.
Democratized
6. Democratize IA to achieve scale
For organizations to gain the most from intelligent automation, they must scale their solutions across the enterprise, allowing contributions from employees within different lines of business who bring varying levels of technical knowledge.
For this democratization to be successful, organizations should have a robust framework to assess, prioritize, and track citizen development initiatives. A center of excellence (CoE) dedicated to building and implementing an easy-to-follow low-code no-code (LCNC) technology can help make it easier for people from non-technical teams to use and develop automation solutions. To be successful, the CoE must include people who serve as change navigators, who bring strong contextual knowledge and can coach employees on projects.
Persistent
7. Plan for perpetual innovation
Enterprises must create a model where employees have a persistent desire to experiment with ideas purposefully and develop innovative automation use cases. Adopting a lean start-up approach to automation helps companies to test the waters before remodeling into full-scale transformation.
Also, to drive innovation within the organization, there should be a targeted effort to gather innovative solutions combined with enterprise-wide evangelism to spur downstream innovation. Solution prototypes can come from formal research, process improvement initiatives, events such as “ideathons,” and through proactive outreach to employees who may have ideas. To create a scalable program, it is crucial to have a well-defined career trajectory and training programs to encourage participation from a large number of employees.
The rapidly evolving business and technology landscape has shown us intelligent automation can be a booster that helps companies speed ahead. However, to get there, automation must be embedded in the company’s DNA and not patched on as an afterthought. The seven boosters will help enterprises derive purposeful and strategic value from automation.
