TECHNOLOGIES FOR DIGITAL DECISION MAKING

Overview

Digital Decision Making upgrades corporate IT with Artificial Intelligence (AI) and Operations Research (OR), providing enterprises with a unique competitive advantage.

Success factors include:

Hybrid AI - INFORM technology integrates Operations Research and Artificial Intelligence, including Fuzzy Logic and Machine Learning. Leveraging computer algorithms with human expertise yields results significantly superior to both, traditional management and purely data driven algorithms.

Agile Optimization - Digital Decision Making empowers a new management strategy based on smart, rapid, and interactive decision making. Agile Optimization is particularly valuable where complex operations face many ad-hoc changes, volatility, disruptions, unpredictability, and time pressure.

Data Analytics - Advanced analytics software tools enable the integration of data from multiple and diverse sources, improve data quality, visualize data, and reveal their significance for operational management.

Turn-key Integration - Our more than 750 business analysts, data scientists, software engineers, and client consultants proudly support the turn-key implementation of Digital Decision Making solutions. This includes system integration as well as on-site go-live assistance and long-term support.

Industry Experience - In addition to providing advanced mathematics we are able to leverage profound management know-how. It was accumulated while empowering a wide range of operations at more than 1,000 customers in over 40 countries. Industry sectors and business processes include Aviation, Automotive, Banking & Insurance, Fraud Prevention & AML, IBP, Inventory & Supply Chain, Logistics, Manufacturing, Materials Handling, Production, Transportation, Workforce Management, and more.

ARTIFICIAL INTELLIGENCE (AI)

ARTIFICIAL INTELLIGENCE

We build upon a long history of expertise in many areas of AI, from general problem solving and decision making over knowledge representation, automated reasoning and deductive intelligence  to machine learning and intelligent control of autonomous systems. By combining techniques from these areas in a hybrid approach, our software systems can perform core functions traditionally associated with human intelligence: decision making and learning.

•    Expert knowledge about business processes and behavioral patterns as well as planning objectives and constraints is cast into digital decision models.  AI techniques (e.g. constraint programming) together with OR algorithms (e.g. mathematical optimization) can explore many millions of alternative decision options extremely fast, hence producing truly optimized results.

•    Machine learning techniques are used to automatically discover new knowledge by mining large data sets for patterns. Predictive models make use of these patterns to classify events and make forecasts about volumes, times and durations, thus providing improved input for the decision models.

Operations Research

Operations Research

Operations Research (OR) applies advanced analytical methods and algorithms to help make better decisions - a uniquely powerful approach to decision making.

Using techniques such as mathematical modeling and optimization, OR leads you to the very best choices. The power of OR algorithms comes from their ability to quickly compare an incredibly large number of feasible options to find solutions that are often overlooked by mere human intuition.

By combining OR with machine learning, we can mine data to gain insights and make forecasts that fuel our OR optimization algorithms.

OR puts data to its most valuable use: Sophisticated algorithms leverage today's computing power to suggest optimized options for decision makers.

Fuzzy Logic

Fuzzy Logic

“All traditional logic habitually assumes that precise symbols are being employed. It is therefore not applicable to this terrestrial life but only to an imagined celestial existence.” [Bertrand Russell]

Building upon the scientific work of our company's founder H.J. Zimmermann, recipient of the prestigious IEEE Fuzzy Systems Pioneer Award, we apply Fuzzy Logic for solving the fundamental challenge of deriving correct decisions from imprecise or uncertain input.

In traditional bivalent logic, any statement is either true or false, without a possibility in between.  Fuzzy logic, in contrast, allows intermediate values, making it suitable for representing linguistic information and expert knowledge. Decisions are taken in a manner similar to that used by humans.

Everybody regularly makes fuzzy decisions, for example when parking their car.  Instead of measuring the parking space exactly, you make a rough guess on all sides as to whether the car fits in the gap.

Fuzzy Logic lets us transfer our human ability of drawing the right conclusions from imprecise information into software.

MACHINE LEARNING

MACHINE LEARNING

Data is the oil that powers the digital economy of the 21st century. Like crude oil, it must be refined to fuel the algorithm engines that can turn it into competitive advantage.

Machine learning is about refining data. It blends concepts and techniques from different fields - such as mathematics, statistics, and computer science - to look for structural patterns in data to find valuable connections and insights and make reliable predictions.

Machine learning is a multi-step process, from data engineering (harmonization, transformation, and enrichment) and feature selection over the training and evaluation of predictive models to the final execution and monitoring of models in challenging real time environments.

The focus always is on model accuracy as well as on comprehensibility, with a preference for models that are understandable and produce justifiable results.

AGILE OPTIMIZATION

AGILE OPTIMIZATION

Agile Optimization is a management strategy for dealing with complexity and uncertainty in the planning and control of business processes. By responding quickly to ad-hoc changes and disruptions in complex business environments, it helps to increase a company's efficiency, agility, and resilience.

More traditional management strategies, such as Lean Management, sophisticated planning, or ad-hoc improvisation, are ill suited to cope with the challenges of today's VUCA world: volatility, unpredictability, complexity, ambiguity, and ever increasing time pressure. By providing smart, rapid, and interactive computer assistance, Agile Optimization is the strategy of choice to elevate decision making for many dynamic business operations.

Data Analytics

Data Analytics

In theory, data is the new oil. In real live, data is fraud with inconsistencies, errors, omissions, duplicates, irrelevant items, etc. It is often incomplete, so it does not represent quite all aspects to be taken into consideration for operational decision making.

Even worse, data comes in different formats and is typically scattered across a multitude of diverse data bases and other IT sources. For the purpose of management decision making, it has to be appropriately aggregated.

Therefore, rather than just visualizing data, our data analytics software tools provide three very useful services in the context of Digital Decision Making:

1.    Consolidating data from multiple data bases, formats, and IT sources into a single, unified data structure. Data is managed simultaneously by persistent and in-memory technologies. This capability alone proves invaluable facing the data challenges of real-life ERP and other traditional or legacy IT systems.

2.    Analyzing data to detect subtle patterns and hidden relationships, turning data into meaningful information. We use a wide range of statistical and machine learning techniques. In particular, this empowers forecasting and predictive analytics.

3.    Visualizing the situational context of management decision making with graphs, pivot and drill-down tables, data cockpits, etc.

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