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An IBM Institute for Business Value report points out how automation is shaping the future of organizations, evolving from basic to intelligent operations.
- More than 90 percent of C-level executives who use intelligent automation say their organization performs above average in managing organizational change in response to emerging business trends.
- More than 50 percent of C-level executives who use intelligent automation have identified key operational processes that can be augmented or automated using AI capabilities.
Operational decisions are fundamental to organizations and their automation technologies. Operational decisions are everywhere. Just think of the thousands of decisions made in day-to-day operations: managing risk, assessing credit and loan applications, defining or adjusting pricing, offering promotions to loyal clients, detecting fraud. There are operational decisions behind pretty much every aspect of most organizations across industries.
How to overcome decision automation challenges
As automation becomes pervasive, the challenges companies face in implementing these decisions are plentiful. Business stakeholders need to easily and consistently implement, test and deploy decision changes to reach markets quickly. Organizations should eradicate the lack of consistency in how decisions are made.
Challenges such as these are addressed through a robust decision automation platform. Whether you are considering starting your journey or you are in the middle of your automation project, the following three things are important to drive success with your decision automation project.
- Business-oriented methodology. Let your business experts take control by discovering business decisions and validating them with no need to write code. For example, consider a collaborative platform where they can directly author, change and validate business policy decisions and share with team members.
- Ability to grow with changing needs. Decisions are the key assets driving business, and you will need to manage them professionally. Imagine if you have a single platform that scales from your first project to an enterprise-wide program without the need for huge incremental investment.
- Intelligent operations with robotic process automation. Bots can help you automate repetitive tasks, but you can make them much more intelligent by allowing them to make decisions, such as those involving eligibility, compliance, pricing and tax decisions.
How to ease the transition
You can make implementing automation projects simpler by considering how company employees will interact with the solution. Below are three tips culled from our many client interactions.
Model decisions visually. Simplify the discovery and the authoring of decisions through visual models that you can validate in a few clicks. These models help business users decompose a decision into small pieces that contribute to the final decision visually. This makes life easier and doesn’t require writing code.
Prototype solutions. Add value by creating more sophisticated decisions, validate your decisions in complex scenarios, simulate the impact of new decisions, and manage user access and change management.
Make your bots smarter. Make it easier for non-technical people to create intelligent bots, without programming skills. Expose key decisions through APIs or interactive user interfaces that robotic process automation bots can operate.
How IBM Operational Decision Manager can help
The recently released IBM Operational Decision Manager 8.10 and the cloud-based service IBM Decision Composer greatly simplify how decisions can be authored, shared, tested and then executed within enterprise applications. This new methodology blends together well-defined decisions using decision modeling and notation (DMN) visuals and the power of the IBM Operational Decision Manager solution. It also puts business experts in the driver’s seat so that they can author powerful executable decisions without typing a single line of code.
You can now try Decision Composer for free to experience the power of decision modeling.