From Spreadsheets to Business Rules Engines: Navigating the Shift to Smarter Decision-Making

Łukasz Niedośpiał
April 9, 2024

According to Gartner's study, 65% of today's decisions are more complex (involving more choices or stakeholders) than 2 years earlier.

McKinsey & Company study showed that 20% of respondents think, their organization's decisions are not optimal. 68% of mid-level managers and 57% of C-level executives say their decision-making is time inefficient.

Meanwhile, better and more efficient decision-making can increase your revenue by up to 20%.

We believe that our beloved spreadsheets are partially responsible for the mess.

In this article, we describe the issues with decisions made using spreadsheets and how to improve it with rules engines.

Traditional Decision-Making

Traditionally, decision-making has been heavily reliant on spreadsheets. These digital ledgers have been the go-to tool for managing everything from inventory and budgets to complex business rules that guide decision-making.

Accounting Today reports that 90% of companies use it for budgeting and planning.

Spreadsheets Decision-Making

Most companies understand the need for data-driven decision-making. Actually, 65% of them will make data-driven decisions by 2026. Today, 90% of corporate marketing strategies mention information as a key tool in decision-making.

However, collecting and managing vast amounts of data is tough. 90% of current data was created in the last two years (we have 2024 as of these words).

The appeal of spreadsheets lies in their simplicity and the universal familiarity within the business community. They allow for the storage, manipulation, and analysis of data in a format that's both accessible and, to a degree, customizable.

However, the simplicity of spreadsheets masks significant limitations, especially as business operations become more complex. The manual entry of data, for instance, introduces a high risk of human error, turning decision-making into a potentially flawed process. 

Furthermore, spreadsheets struggle to scale up efficiently. As a business grows, its decision-making processes become more intricate, involving more variables and conditions that a simple spreadsheet cannot handle without becoming cumbersome and error-prone.

A case of Enron's bankruptcy showed us the scale of problems with spreadsheets. During the investigation by SEC, over 600,000 emails were retrieved.

  • more than 10% (68,679) of emails were about spreadsheets,
  • 24% of spreadsheets in questions contained formula error, where one erroneous cell affected on average 9,6 other formulas,
  • 6% of words from these 68,679 emails about spreadsheets referred to errors.

Spreadsheets lack the dynamic interactivity required for real-time decision-making. They operate in a static environment, where changes in one area do not automatically update or inform other relevant parts of the business. This limitation can lead to outdated information guiding critical business decisions, potentially leading to inefficiencies or missed opportunities.

Another critical shortfall is the challenge of version control and audit trails in spreadsheets. In environments where decisions need to be fast yet accurate, tracking who made what change and when can be a logistical nightmare, making accountability and historical analysis difficult.

The Evolution of Business Needs

In 2021 Signal AI surveyed over 1000 C-level executives about decision-making. According to their report, the biggest block in making a decision is an overwhelming amount of data.

What's more disturbing, the report estimates that a total of $4,26 trillion USD is wasted due to bad or slow decision-making. Implementing technology into the decision-making could increase revenue by 20%.

Studies on decision support systems have found that artificial intelligence (AI), networking, and cloud computing are upgrading old decision-making systems into smarter ones, solving tough problems. 

AI uses computer algorithms to perform tasks that usually need human intelligence, such as:

  • classifying and analyzing data, 
  • making predictions, 
  • acting on data, 
  • learning from new data, and getting better over time.

It's similar to how a child grows into an adult.

Adaptation to the Digital Age

In the digital age, businesses are inundated with data from various sources—social media, e-commerce platforms, customer feedback, and internal operations. The ability to quickly sift through this data, identify patterns, and make informed decisions is crucial. Unlike in the past, where data was more static and manageable, today's data is dynamic and voluminous, demanding tools that can automate and streamline the decision-making process.

Need for Speed and Efficiency

The speed of business has accelerated dramatically. Decisions that once took days or weeks now need to be made in hours or even minutes to maintain a competitive edge. This necessitates a move away from manual processes, like those associated with spreadsheet management, towards automated systems that can process information and enforce business rules in real-time.

Scalability and Complexity

As businesses grow, so does the complexity of their operations. The scalability issue of spreadsheets becomes evident when businesses try to manage an expanding set of rules and data. There's a limit to how much complexity a spreadsheet can handle before it becomes unmanageable or prone to error. Business rules engines, on the other hand, are designed to handle complexity and scale effortlessly with the business, ensuring that decision-making processes are not hindered by the tool's limitations.

The Demand for Flexibility and Adaptability

The only constant in business is change. Regulatory changes, market shifts, and evolving customer preferences require businesses to be flexible and adapt quickly. Spreadsheets, by their nature, are static and require manual updates, making them unsuitable for environments where rules and conditions may need to be frequently updated or changed.

Integration and Interoperability

Today's systems and applications need to communicate seamlessly. Spreadsheets are siloed documents that do not easily integrate with other systems. 

Business rules engines, however, are designed to integrate with a wide array of databases, applications, and software, facilitating a more cohesive and efficient operational framework.

Introduction to Rule-Based Decision Engines

In the journey towards smarter, faster, and more efficient decision-making, businesses are increasingly turning to rule-based decision engines. These sophisticated systems represent a significant leap forward from traditional spreadsheet-based rule management, offering a dynamic and automated approach to decision-making that can handle the complexity and speed required by modern businesses.

What is a Rule-Based Decision Engine?

At its core, a rule-based decision engine is a software system that applies pre-defined business rules to data to automate decision-making processes. These engines are designed to take in data, process it according to a set of rules, and produce decisions or actions without the need for human intervention. 

The rules in these engines can range from simple if-then statements to complex algorithms that consider multiple variables and data points. 

How Does Rule Engine Work?

Rule-based decision engines operate on the principle of logic. They use a set of algorithms to evaluate data against established rules and then execute decisions based on the outcomes of those evaluations. 

This process involves three key components:

  • Rule Repository: This is where the business rules are stored. These rules define the conditions under which specific actions should be taken.
  • Inference Engine: The engine that processes the data, applies the rules, and infers actions or decisions based on those rules.
  • Interface: The means through which the system interacts with users or other systems, allowing for the input of data and the output of decisions.

The Advantages of Adopting a Decision Engine

The shift from spreadsheets to rule-based decision engines brings numerous benefits to businesses, including:

  • Automation: Automating the decision-making process reduces the need for manual intervention, which can speed up operations and minimize human errors.
  • Consistency: By applying the same set of rules across all decisions, businesses can ensure consistency in their operations, enhancing reliability and trust in their decision-making processes.
  • Scalability: Rule-based systems are designed to handle a large volume of data and complex decision-making processes, making them scalable as business needs grow.
  • Flexibility: These engines allow for quick updates and changes to rules, enabling businesses to adapt to new regulations, market conditions, or business strategies efficiently.
  • Integration: Decision engines can be integrated with other business systems, such as customer relationship management (CRM) and enterprise resource planning (ERP) systems, for seamless operations.

Rules Engines vs Spreadsheets

Feature Rule-Based Decision Engines Spreadsheets
Automation High: Automates decision processes, reducing manual tasks and errors Low: Requires manual data entry and formula setup, prone to human error
Consistency High: Applies the same rules consistently across all operations, enhancing reliability Medium: Can be consistent but relies on correct formula replication and human accuracy
Scalability High: Designed to manage large volumes of data and complex processes, grows with business needs Low to Medium: Limited by data volume handling and complexity, can become unwieldy
Flexibility High: Allows quick updates to rules for adapting to new conditions or strategies Medium: Flexible within the scope of formula adjustments, but changes can be labor-intensive
Integration High: Easily integrates with other systems (CRM, ERP) for streamlined operations. Low to Medium: Possible integration through APIs or add-ons, but not as seamless or native.

How To Apply Rules Engine in Your Organization Decision-Making

Transitioning to a business rule engine from traditional spreadsheet methods involves navigating specific challenges to boost business process efficiency, organizational decision-making, and business strategy. Key considerations include:

  • Upfront Investment and Learning: The shift to a business rule engine incurs considerable initial setup costs and a learning curve. Employees must be trained to create rules, grasp the business logic, and utilize this new software tool, crucial for harnessing process automation benefits.
  • Data Integration and Migration: Migrating critical data to a rule engine is intricate, necessitating careful planning to maintain data integrity. Successful integration ensures that rule flows align seamlessly with existing systems, preserving organizational behavior and the integrity of business processes.
  • Change Management in Organizational Behavior: Implementing a rule engine alters the fabric of organizational decision-making, transitioning from manual methods to relying on predefined rules. Managing this change is vital to sustain morale and foster effective decision-making based on a systematic approach.
  • Flexibility, Scalability, and Business Logic: Adapting business strategy and processes quickly is essential. The rule engine must allow for easy updates to business logic and predefined rules, ensuring scalability for handling an expanding scope of organizational decisions.
  • Formulating Accurate Business Rules: The accuracy in formulating rules that reflect the business strategy and logic is critical for the final decision's success. Continuous collaboration is required to ensure rules accurately represent desired outcomes, taking into account multiple factors and past decisions.
  • Transparency and Quality of Decisions: With more automated decision processes, maintaining clarity on how decisions are reached becomes challenging. It’s crucial to ensure that organizational decision-making remains transparent, especially when decisions are influenced by multiple factors, including past outcomes.
  • Human Insight Amidst Automation: While rule engines offer extensive process automation, the human element remains indispensable for decisions requiring nuanced judgment. Finding a balance ensures that automation complements rather than replaces human oversight, enriching the final decision-making process.
  • Technological Evolution and Security: Keeping abreast of advancements in decision-making technologies ensures that the business rule engine stays effective. Additionally, integrating new systems must not compromise data security, underscoring the need for stringent security measures in line with the business process and strategy.

Ready To Improve and Quicken Your Decision?

Do you feel like making complex decisions in your organization could be faster? As if it was engaging too many stakeholders, wasting their time? Do you want to reduce the impact of spreadsheets and need for them? Book a call with us and tell us of your use case of our rules engine Higson.

With Higson, benefit from enhanced decision intelligence, seamless integration with CRM systems, and unparalleled efficiency in handling vast data sources. Don't let outdated methods hold back your strategic agility and operational excellence. 

Contact us today for a tailored use case demonstration, and see firsthand how Higson empowers executives and decision-makers like you to make smarter, faster decisions. 

This can be your first decision towards making better decisions.

Get a personalized evaluation of Hyperon’s potential for your use case
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