Transform Your Business With Operational Decision Automation

Decisioning Applications Bring The Value Of Operational Decisions To Light

Businesses face the imperative to transform business from analog to digital due to intense competition for increasingly demanding and digitally connected customers. The imperative to transform has ushered in a new era of decisioning applications in which every operational decision an organization makes can be considered a business asset. New applications inform and advance customer experience and drive operational actions in real time through automation. These applications are at the forefront of the effort to streamline operations and help organizations take the right action at the right time near-instantaneously.

Achieve Digital Goals With Automated Operational Decision Making

Automating decision life cycles allows firms to manage the fast changes required in increasingly digitized business processes. Automation of operational decisions is crucial to meeting digital goals: More than three-quarters of decision makers say it is important to their digital strategy —and close to half say it is very important.

« The Share of Decisions that are Automated will Increase Markedly in two Years »

The importance of automated operational decision making to digital strategy will lead to a sharp increase of automation in the near term. Today, about one-third of respondents say they have the majority of their operational decisions fully or partially automated. In two years, that group will double.

Use Cases For Automated Decisions Span The Customer Lifecycle But Current Focus Is On Early Stages

To improve the operational aspects of customer experience —and to reap the business benefits that come with delighting customers — firms align automated decision use cases to the customer lifecycle. At least some firms have expanded their share of automated operational decision making to include touchpoints across the customer lifecycle, from the discover phase all the way to the engage phase. However, our survey found that the majority have yet to implement automated decisions as fully in later stages.

Top Challenges Will Intensify With Rapid Expansion Of New Decisioning Tools

Firms are experiencing middling success with current decision automation tools. Only 22% are very satisfied with their decisioning software today. Misgivings with today’s tools include inability to integrate with current systems or platforms, high cost, and lack of consistency across channels and processes.

The growth of real-time automation use cases and the number of technologies brought on to handle them will exacerbate existing challenges with complexity and cost.

Decision Makers Recognize High Value In Decisioning Platforms That Work In Real Time

Decision makers face significant implementation and cost challenges on their path to automated operational decisions. As a result, getting the greatest business value for the power of their automation tools is top of mind.

« Eighty-one percent of Decision Makers say a Platform with Real-Time Decision-to-Action Cycles would be Valuable or Very Valuable to Achieving Digital Transformation Goals. »

With better, targeted decisions based on real-time analytics, companies have the potential to acquire better customers, improve the operations that serve them, and retain them longer.

decision automatization

click here to access forresters’s research report

RPA – A programmatic approach to intelligent automation to scale growth, manage risk, and drive enterprise value

Business leaders and chief information officers around the world are jumping on the robotic process automation (RPA) pilot bandwagon to start their companies on the automation journey. Some RPA pilots are evaluating software designed to stitch together known technology concepts—such as screen scraping and macrobased automation—through user-friendly tools to take process automation to the next level. Other pilots are venturing into the use of machine learning and cognitive automation to unleash new business insights.

These pilots—or proof-of-concept programs—help leaders set a foundation for their understanding of RPA, while at the same time introducing new ideas for how automation can help scale operations or define new business strategies. And now the pilot was successful, and leaders are seeing the possibilities. So what happens next?

When performing RPA pilots many companies get stuck in basic automation and stop there. Other companies have basic and cognitive automation pilots going on simultaneously.

Aligning the goals of basic RPA with cognitive computing and artificial intelligence can seem improbable. But are the objectives really that different? Leaders want to use all levels of automation to

  • drive business growth,
  • manage risk,
  • and increase value.

The trick is having a strategy for getting from pilot to program, and putting in place a comprehensive structure looking beyond the RPA pilots to intelligent automation (IA) as an across-the-board investment. This ensures IA ventures become more than speculation and remain significant to the business.

  • But how can leaders ensure that IA is more than a one-time cost play?
  • How are future automation opportunities identified and evaluated for both risk and benefit?
  • How is “electronic employee” service performance monitored?
  • How do leaders ensure the optimal mix of basic, enhanced, and cognitive automation?
  • How is business continuity maintained if the IA solution fails?
  • How is
    • system security,
    • change management,
    • system processing,
    • and authentication control
  • maintained as automation risk becomes more complex?
  • How will IA be used to transform the business?

Leaders know technology is changing rapidly, and IA is a moving target. Implementing a “bullet-proof” value-based program is critical to managing the automation revolution and ensuring it delivers positive business impacts over time. Robust program management balances risk and reward with structures driving sustainable IA value. An IA program model delivers these ideals.

An Intelligent Automation program can help enhance and expedite the implementation of IA throughout an organization. Here are four critical characteristics for success:

  1. It is strategically positioned – Positioning IA on par with other business strategies as integral to enterprise objectives is the best place to start. Similar to outsourcing (OS), these dependent IA vendor relationships are treated as strategic. Global processowners (GPO) use IA to transform end-to-end services. Global teams engage in IA opportunity evaluation to ensure bad processes are not automated.
  2. It uses a “center of excellence” service model – Establishing a center of excellence (CoE) demonstrates a commitment to IA success. Focus drives effectiveness, and CoEs drive transparency to IA results. CoEs have varied formats (virtual, centralized, regional, etc.) and engage cross-functional teams. CoE governance guides IA strategy and validates results. Clarifying decision rights balances governance and operations accountabilities. Incorporating IA support roles (e.g., HR, IT Security, Internal Audit, risk) in decision-making ensures change integration is well managed.
  3. It has a robust delivery framework – Integrating technologies, toolkits, and tactics into IA program execution safeguards sustainability. Including relevant designers, IT professionals, and operations teams in testing makes sure solutions work. Socializing and managing life cycle compliance (e.g., intake, approvals, testing) ensures team interaction is clear. Program management, repository, and workflow tools makes oversight effective.
  4. It incorporates a proactive risk management structure – Making IT risk and security control oversight a part of IA development ensures solutions are sound. Like any technology integration, change control is critical to implementation success. An IT security risk and control framework provides this support. Risk mitigation strategies linking security reviews to IA validation ensures business goals and technology risks are appropriately considered.

RPA

Click here to access KPMG’s detailed RPA report