When it comes to organizations' values, the cumulative of business decisions they make and execute becomes their value. This means the organization should focus on the center of authority, build teams around business decisions, and ensures they can make and execute business decisions at scale.
However, enabling teams to do that so requires a whole new mindset, methodology, and technology to support them. Let’s have a look at what is needed at a high level.
Business Decision Modeling
For sure, the very core of this approach is to capture business decisions in every area, manage them methodical and ensure every member of team and all stakeholders understand the business decisions and how they impact the organization's overall objectives.
The best way to capture and communicate business decisions is using the decision graph, enabling leaders to model complex, hierarchical, and multi-step decisions. This model clearly layouts how a decision is made. Hence it is a simple visual model abstracting the technology complexity out; it will communicate to every stakeholder all about the business decisions.
Once the team frames the particular decision, this just model becomes the blueprint of all dependencies of the business decision. Any business decision depends on required data and information, systems, technology, and even other business decision outcomes (sub-decisions).
Decision Logic Choices
The next step is to understand the nature of the dependent decisions and sub-decisions in the established blueprint to determine the right choice of technology for implementing the decisions.
- Is the decision related to regulations and policies?
- Is the decision about your customer behavior and how they are engaged?
- Is the decision about a prospect and how you need to nurture them?
- Is the decision about how you should be collecting money from a debtor?
- Is the decision about what procedure and complementary medicine is the best option for the patient?
- Is the decision about minimizing customer waiting time while all your agents are not busy?
- …and so on…
Therefore, depending on the nature of the decision and the consequence of them, there are many choices that broadly falling into these categories:
- Rule-driven decisions: allowing to capture and execute business rules around specific decisions in using multiple methods such as Decision Table, Natural language and so on.
- Data-driven decisions: This includes building and statistical model, and data visualization for training and executing machine learning (ML) models to satisfy the outcome of the specific decision.
- Constraint-based decisions: There are techniques to model constraints to optimize a specific business KPI once a decision has multiple outcomes. Optimization models such as minimizing or maximizing something in the business can use constraint programming, learning programming, etc.
- Decision-making process: These types of decisions look like processes, but the whole purpose of the process is about making a business decision rather than coordinating between people and systems.
Many decisioning platforms do only rule-driven decisions stop here once they model and ready to execute a particular decision logic. Though this is an important step, however, this is not all you need when it comes to accelerating decisioning at scale!
Building the Context
Business decisions do not live in isolation. They exist to produce the outcome related to a business objective. Even if we look at the mechanics of decision-making based on OODA loop decision cycle, we notice there are two stages prior to the stage where the actual decision-making happens. Observer and Orient stages are where the data is loaded, and the context for decision-making is created.
Data changes constantly, and I don’t mean the new records of data – that is for sure; I mean the data structure and sources of the data itself. For instance, a new field of information is collected. The data aggregation logic changes. The source of a look-up field will be moved to other systems. Customer information requires a set of new fields. The source of input data i.e. XML, CSV, Excel file, are restructured or changed based on different countries or states. All these changing components will change how the context for decisioning is prepared and created.
As obvious as it is, to scale the decisioning, this preparation and building context should not become the barrier. You need to connect to online services, databases, and applications easily. You also need to be able to aggregate the collected data, transform and enrich them and put together the information you need to create the context for decision making.
To ensure this stage does not become a barrier to scale, you need to manage the whole chain of other components related to the business decision cohesively, including the data and information required. However, at the same time, your decision model should not reference the physical field and use them as part of the decisioning.
The decision model should reference to a Live Context™ which enables organizations to make situation-ware decisions.
To accelerate decisioning at scale in your organization you need to integrate the outcomes of decisions into the business operation i.e., information systems, data, reports, business processes, and so on.
The End-to-End Decision Automation must have the muscle to carry out the actions to make things happen. Just putting the decision out there and hoping everyone and every application will use it, and it will be integrated into the day-to-day operation of the business, is just wishful thinking.
Therefore, an advanced orchestration with the power of robotics is needed to integrate business decisions outcomes into organizations’ operations. This is the only way to ensure the outcomes of the decisions will be deriving the business operation proactively and will increase the organization's operational capacity.
Business decisions are the very core of business operation and the organization’s value. Focusing on managing and automating them is a no-brainer. However, accelerating the decisioning at scale is not just about modeling business decisions only, but it is about empowering organizations to have full control of making and executing business decisions as fast as possible throughout the whole chain of dependencies of business decisions.
This requires empowering teams by giving them authority, tools, and methodology to make and execute business decisions end-to-end, measure the overall impact and decision's drift, and enable them to refine the business decisions along the way.
Just building and deploying a decision model is not enough to enable organizations to accelerate decisioning at scale. Many other components should go hand in hand seamlessly to ensure the decisions’ outcomes are fully integrated into the operations of the business. Therefore, a full-stack decision technology that supports all requirements in a unified and integrated manner will definitely go a long way to empower all your leaders of business, operation, and IT to improve the speed and quality of key business decisions.
Published August 18th, 2022 at 04:57 pm
CEO and the founder of FlexRule – He is an expert in architecture, design, and implementation of operational decisions, business rules, and process automation. Created Decision-Centric Approach, a methodology that brings People, Data, Rules, and Processes together to automate operational business decisions.
This approach is recognized by Gartner as the missing link to provide business value to organizations.