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Re-engineer Decision Making

Embedding intelligence into the workflow
Re-engineer Decision-Making

Iconic 20th-century management guru Peter F. Drucker said once, “Whatever a manager does, he does through making decisions.” Irrespective of the size of the organization business processes and context always change due to market dynamics as well as an internal shift in strategy. Over time, as the business context evolves organizations create plans, organize discussions, give orders or advice, approve plans or reject them – every action involves decision making. Right decisions, at the right time enabled by the right set of people, empower an organization to function efficiently.

Need for a paradigm shift in the decision-making process

The current state of the decision-making process isn’t adequate to produce sustainable results. 67% of the 146 business leaders in a Gartner Survey agreed that the Decision-making process has become more complex. Stakeholders are involved in the process and more options are available due to advancements in technology. There is an emerging need of making decision cycles shorter and these decisions need to be justified. In a Business Application Resource Centre survey, it was found that 58% of the companies base 50% of their decisions on gut feel. The current decision-making process is plagued with various challenges:


Whatever a manager does, he does through making decisions
-- Peter F. Drucker

  1. Often managers and stakeholders cherry-pick data points to justify their decisions. The analysis is consumed in hindsight after the consequence of the decision has been realized – the focus is on seeking validation for the decision. In the Gartner survey, it was found that - 53% of the respondents cherry pick a certain data point that would help them make the case.
  2. There is a considerable dependency on IT which makes it difficult for users to back their decisions leveraging the data available with the business. In PWC’s global data and analytics survey, two-thirds of the respondents said that decision-making is only somewhat or rarely data-driven.
  3. Current decision-making process is time-consuming. Insights through static pre-defined reports limit the ability of the business users to expedite interrogation of the data and back their decisions with insights. As the decision-making process becomes more complex, more decisions are being made with an expectation of a faster decision-making cycle.
  4. Often business context specificity seems to be missing during the decision-making process. Personal or organizational implications of bad decision-making are ever so significant in this competitive environment. Without the right frame of business context, decision-making will not be able to relate to the implication of a decision.

Re-engineering decision making: Embedding insights into the workflow

Embedding insights into the workflow ensures the consumption of real-time contextualized analytics at the point of decision making. Insights are stitched into the business process where the transaction, analysis, and recommendation take place simultaneously in real-time. This not only reduces the time to insight, lowering the cycle time for the decision-making process but also eliminated the need to browse through other applications to consume analytics. Insights are designed to address user-role-based requirements focused on individual tasks and thus, become highly responsive to the business context. Business users can also consume insights without leaving the application resulting in better adoption. Such self-service analytics drives the culture of a data-driven organization.

Insights are designed to address user-role-based requirements focused on individual tasks and thus, become highly responsive to the business context.

Let’s take an example of the workflow of a purchasing manager which comprises simple transactions like creating or maintaining a purchase order, selecting a supplier and finalizing the PO value, and then releasing the order. The purchase manager needs to analyze supplier performance metrics, respective contract utilization, and margins to decide on a supplier. Through embedding insights into the workflow, the purchase manager need not leave the application to analyze supplier performance data. He/she can receive instant delivery of insights within the workflow and make faster decisions.

Embedded Intelligence

Integrating processes with intelligence

In a traditional approach business process and business intelligence were decoupled and conducted in silos. Thus, creating a disconnect between the decision-makers and the analysts. Even if the analysis is being conducted by the decision-maker that increases the cycle time for the decision-making process. Moreover, organizations often fail to leverage key opportunities and risks that emerge from the insights as the insights are consumed in hindsight after the event has occurred. Today’s organizations need to design smarter processes leveraging contextualized insights, AI/ML, exception handling, visualization, drill-down reporting, etc engraved into the process itself.

Embedded Business Intelligence

How We Can Help ?


By embedding insights into the workflow, we help you by pushing insights into the front lines at the point of decision-making.

Packaged Analytics Offering - S/4 HANA Starter Pack:

  • Develop analytics strategy & roadmap aligned with S/4 Embedded Analytics Data Warehouse Strategy
  • Change Management with bootcamps, training and self-serve analytics
  • Focus on self-serve consumption of insights using FIORI and SAC
  • Deploy foundation quickly to and address critical customer gaps
  • Accelerate refinement and reduce complexity to simplify your analytics landscape
  • A running start into Analytics with pre-built Industry solutions for FI, Sales, HR and Procurement