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Risk Assessment

Risk Rating: Scoring Challenges and Solutions

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Risk rating is a complex scoring system, which relies upon previous experiences and foresight to anticipate risks that might impact the smooth functioning of business. When risks are well managed, a business can maximize opportunities and control the impact of disruptive events. Alternatively, if a risk is underestimated—or not anticipated at all—a business can suffer significant economic or reputational damage as a result of this unpreparedness.

What is the Purpose of Risk Rating?

Businesses use risk rating to assess the risks involved in an activity. The goal is to anticipate and classify potential risks as low, medium or high based on the expected impact and the likelihood of such an event occurring in the near future. This allows businesses to adopt control measures that can help cure, mitigate or remove the anticipated impact of the risk.

Risk Rating

In situations where risk cannot be controlled or removed, a business may choose to accept the risk or cancel the activity. This decision depends on the likelihood of the risk event occurring and the expected severity of the impact.

Why is Risk Rating a Challenge?

Experience and historical data are useful references when rating the probability and impact of risks that have happened before and may happen again under the same set of circumstances. The bigger challenge is managing unknown risks. Obvious examples include Covid-19, the economic meltdown of 2007-2008, the Fukushima nuclear accident. Unknown risks typically form through complex interdependencies and dynamics that are not fully understood until the event happens.

Human imagination is limited in such cases. Further, humans have a tendency to underestimate the probability of an outlier event or downplay the expected impacts. Even as the economic events of 2007-2008 were unfolding, the US Fed’s risk model did not predict the scope or severity of the resulting recession. With Covid-19, scientists warned governments and healthcare to prepare for the possibility of a coronavirus pandemic, but most did not have sufficient plans in place to contain the health and economic impacts of the virus.

The unexpected impacts of climate change provide another example of how domino effects can catch entire industries and governments off guard. Extreme weather events are causing slowdowns across major supply chains. And rising temperatures are threatening the safety of water supplies. As the world becomes more globally connected and the pace of change intensifies, it will become even more difficult to anticipate the full range of risks that need to be managed.

How Can a Digital Twin Help Improve Risk Scoring?

A digital twin provides a software representation of a physical asset, system or process designed to detect, prevent, predict and optimize the system being studied through real time analytics. Digital twins created within X-ACT include time dependent behaviors, which is key if you want to accurately model the dynamics of assets that change over time—for instance aging or cyclical changes that may impact performance.

Using the digital twin to perform stress testing and sensitivity analysis allows users to quickly identify any conditions that might cause a physical asset to deviate from its expected behavior or find the root cause of problems. As risks are revealed, fixes or controls can be identified using the digital twin and implemented when needed. Users can also gain confidence in decisions and see how different choices playout under various conditions. This is particularly useful to predict the outcome of scenarios that would be difficult, costly or even impossible to test in the real world.

For example, a digital twin can be used to evaluate the benefit versus risk of deploying innovative technologies, like artificial intelligence, blockchain or Internet of Things. Or even help rate the risk of a new business activity, like funding loans for smart city projects, when there is no historical precedent to reference.

By covering every variable which may directly or indirectly influence risk, digital twin analysis can predictively cover known risks and expose unknown risks. This arms decision makers with the missing risk intelligence they need to successfully navigate the complex dynamics and uncertainty of modern business.

 

Taking a Computer-Aided Engineering Approach to Business Transformation

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Changing competitive landscapes, technological advances and consumer trends are rapidly disrupting businesses and creating an imperative to execute transformation programs that improve operational efficiencies, optimize workforces and offer better customer experiences. Across industries vast amounts of resources are being spent on business transformation programs, but so far the results are dismal. According to IDC, $1.7 trillion was spent in 2017 by companies worldwide on their digital transformation efforts and yet analysis suggests that only 1% of transformation programs will actually achieve or exceed their expectations.

Business transformations are pursued to fundamentally change systems, processes, people and technology across an entire business or subdivision to achieve measurable improvements in efficiency, effectiveness and stakeholder satisfaction. When transformation programs fail, time and money are wasted, while no significant improvements are gained. In the meantime, risks related to product or service obsolescence, rising costs, declining revenues or other factors that spurred the transformation in the first place, have grown.

Intelligent Business Transformation

Taking a computer-aided engineering (CAE) approach to business transformation can help businesses manage program risks, maximize value, decrease costs and accelerate innovation. CAE is widely used in a range of industries to build the right product at best performance versus cost ratio. A main goal being to improve designs or anticipate the resolution of potential problems as early as possible.

Using the emulation-based capabilities of X-ACT®, we are helping businesses achieve the same benefits of CAE in their transformation programs:

  • Make business transformation decisions based on key metrics including performance, time to market and cost
  • Manage risk and communicate the long-term business implications of any decisions to all stakeholders
  • Use computer emulation rather than real world testing to save money and time—while supporting a broader scope of upfront validations
  • Gain risk and performance insights earlier in the transformation process, when changes are less expensive to make
  • Explore innovative solutions that may not have been considered plausible without the aid of computer emulation

Reliable Predictive & Prescriptive Intelligence

When businesses want to build best in class systems or ensure the optimal performance of exiting business ecosystems, computer emulation is an effective way to validate plans, predictively expose risks, and identify which corrective actions will achieve the desired results for any given situation. X-ACT algorithmically emulates business structures and produces advanced predictive analysis to determine the limits of dynamically complex systems, identify potential risks and recommend which corrective actions are needed to meet business objectives.

While CAE typically uses simulation to replicate system behaviors, these methods are not sufficient to cover a change in dynamics, meaning some risks will not be exposed until the event occurs because only the knowns are represented and so reproduced. X-ACT uses emulation in place of simulation to mathematically reproduce risks that may occur under certain conditions even if there is no historical record of these events happening.

Quickly & Economically Explore All Options

Once the emulation is successfully created within X-ACT, it allows transformation teams to quickly test and economically explore an unlimited number of change scenarios that would otherwise be complex, expensive or even impossible to test on a real system. Users simply change variables—such as volume, architecture and infrastructure—or perform sensitivity predictions on changing process dynamics to observe the predicted outcome.

Validated through robust testing in hundreds of applications and various industries, X-ACT provides visibility across complex business and IT ecosystems so that decision makers can quickly agree upon the most strategic plans and proactively take corporate actions with confidence in the outcome. Additionally, X-ACT supports transformation programs by enabling users to test optimization and rationalization scenarios to confirm the best-fit solution before committing funds or resources to any project.

Manage the Transformation Project Outcome

During the execution phase, X-ACT provides the foresights necessary to ensure an optimal outcome that weighs both short and long-term cost benefits in alignment with performance and scalability goals so that the business can minimize risks and consistently gain all the intended benefits of the transformation program. Ultimately, these capabilities help businesses define and make the right moves at the right time to continuously achieve better economy, control risk and support critical renewal.

Learn more about the benefits of using of X-ACT for Business Transformation

Read the Intelligent Business Transformation solution paper to learn why and how businesses use X-ACT in a Computer-Aided Engineering (CAE) capacity to validate transformation plans and control risks.

Report

 

Top Research Firm Praises URM GROUP for Helping Customers Manage Risk Across Complex Business and IT Ecosystems

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EMA confirms X-Act platform offers unmatched breadth of prescriptive and predictive analytics, calling it “a step beyond BI, big data, AIOps, and other IT analytic investments”

Universal Risk Management Group (URM GROUP), today announced a new report from top market research firm Enterprise Management Associates (EMA), which praises the predictive insights and correctional guidance offered by URM GROUP’s X-Act® platform as “a step beyond business intelligence (BI), big data, AIOps, and other IT analytic investments.”

EMA has labeled this new category of capabilities “Transformational Analytics,” reporting that the sophisticated algorithms used in X-Act place it in an advantaged position vis-à-vis other, more operations-centric analytic tools that typically rely more on statistics.

Download ENTERPRISE MANAGEMENT ASSOCIATES® (EMA™) White Paper, How X-Act can Optimize Business Performance by Managing the Unknown at https://urmgrp.com/portfolio-item/ema-urm-xact/.

Dennis Drogseth, Vice President of Research at Enterprise Management Associates (EMA) noted, “EMA interviews and market research confirmed that no other solution in the market today is designed to bring IT and business components and processes together in a single, unified model as deeply and as efficiently as X-Act. As such, the platform stands out for being proactively prescriptive in minimizing risk and optimizing both IT and business performance.”

What Customers are Saying about X-Act

“I do not believe that there is any other solution in the market that offers a single consistent model for business processes and the application/infrastructure when you seek to optimize both effectively. Only X-Act does that, and it does so with unique levels of accuracy,” Head of Infrastructure Operations at a global Financial Services Company said.

“X-Act tells you where the problems are, where they are likely to materialize in the future, and how planned changes on all fronts may affect the outcome one way or another. This makes investments in new resources, if they’re needed, a fact-based discussion with a clear business context. Not surprisingly, this is one of the reasons for IT executive enthusiasm.” IT Architect, Large European Bank said.

Learn more about X-Act platform at https://urmgrp.com/technology/.

About URM GROUP

URM GROUP provides the technology and services many of the world’s most recognizable brands depend on to optimize opportunities and comprehensively control risks across diverse business and IT systems. With patented generative intelligence technology, X-Act® platform provides a revolutionary way to quickly and predictively pinpoint hidden sources of risk within business ecosystems and know which actions should be taken to meet business goals. Leaders across financial services, retail, manufacturing, transportation, healthcare and governments trust X-Act to make informed decisions relating to a wide range of strategic objectives—from digital transformation, cost management, mergers and acquisitions to supply chain management and production performance. For additional information, visit https://urmgrp.com or connect with us on Twitter @URMgroup.

About EMA

Founded in 1996, EMA is a leading industry analyst firm that specializes in providing deep insight across the full spectrum of IT and data management technologies. EMA analysts leverage a unique combination of practical experience, insight into industry best practices, and in-depth knowledge of current and planned vendor solutions to help clients achieve their goals. Learn more about EMA research, analysis, and consulting services for enterprise line of business users, IT professionals and IT vendors at http://www.enterprisemanagement.com.

URM GROUP Launches to Arm Executives with Better Risk Intelligence, Bridging the Business and IT Gap

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Building on 15 Years of Success as Accretive Technologies, URM GROUP Aims to Revolutionize how the World’s Largest Brands Prescriptively Manage Business-IT Risk

Universal Risk Management Group (URM GROUP), formerly Accretive Technologies, today launched to deliver its patented generative intelligence technology, X-Act® platform to a broader base of global organizations that desperately need a better way to manage risk across highly complex business and IT domains. Fueled by record profits and growing market demand, URM GROUP aims to arm executives with the intelligence they need to optimize business performance and prescriptively treat risks that domain experts, business intelligence (BI), business process management (BPM), AIOps, and other analytic investments often miss.

“In a world that is constantly morphing due to the acceleration of innovation and digital disruption, businesses can no longer afford to pay an army of experts and then wait months while they argue over the cause of poor performance or settle on the best strategic plan,” said Charlie Fote, Chairman of the Board, URM GROUP and former CEO & Chairman, First Data. “With the innovations URM GROUP is bringing to market, decision makers can quickly gain a single, unified view of their entire business and verify, with better certainty, which actions will lead to the most desirable outcome.”

Proven through more than 350 cases worldwide, URM GROUP provides the technology, innovation and expertise that leading brands within financial services, retail, manufacturing, transportation, healthcare and governments trust to identify hidden risks and make informed decisions relating to a wide range of strategic objectives—from digital transformation, cost management, mergers and acquisitions to supply chain management and production performance.

Dennis Drogseth, Enterprise Management Associates (EMA), Vice President of Research said, “URM GROUP’s X-Act platform stands out for delivering beyond its customers’ expectations. Moreover, its promise is in no way a small one. X-Act produces critical predictive insights and correctional guidance to minimize risk and optimize business performance across complex business and IT ecosystems.”

Building on 15 years of success as Accretive Technologies, URM GROUP is backed by a strong performance record and a history of innovation.

  • Currently serves some of the largest and most recognizable brands in the world across multiple industries including financial services, retail, manufacturing, transportation and healthcare
  • 2017 marked the second year in a row that the company has grown revenue and the second consecutive year of growing gross margins over 60%
  • Repositioning strategy has poised the company for further growth
  • Holds a variety of patents involving the innovative use of mathematical modeling and related methodologies covering both business and IT systems
  • Maintains strong partnering agreements with IBM, Accenture, Persistent Systems, and Dynatrace

“It’s always satisfying to hear that X-Act helped a customer save hundreds of millions of dollars or prevented them from making really a bad decision,” said Nabil Abu el Ata, CEO, URM GROUP. “We’ve dedicated fifteen years into the research and development of X-Act to make these results consistently possible for our customers. With the launch of URM GROUP, the people, technology and channels are finally in place to serve the broad base of companies that want to use X-Act to quickly and cost effectively know when and which actions should be taken to ensure the most optimal business outcome.”

Additional Resources

About URM GROUP

URM GROUP provides the technology and services many of the world’s most recognizable brands depend on to optimize opportunities and comprehensively control risks across diverse business and IT systems. With patented generative intelligence technology, X-Act® platform provides a revolutionary way to quickly and predictively pinpoint hidden sources of risk within business ecosystems and know which actions should be taken to meet business goals. Leaders across financial services, retail, manufacturing, transportation, healthcare and governments trust X-Act to make informed decisions relating to a wide range of strategic objectives—from digital transformation, cost management, mergers and acquisitions to supply chain management and production performance. For additional information, visit URMgrp.com or connect with us on Twitter @URMgroup.

Using X-ACT Metrics to Guide Decisions

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Learn how to make operational risk decisions with confidence

The X-ACT: Using Metrics to Guide Decisions | How to Guide shows how companies use the advanced analytics and emulation capabilities supported by X-ACT to identify how dynamic complexity leads to system limits, diagnose the root cause of limits and determine the best remedial actions by weighing the benefits, complexity and cost of proposed solutions.

Download Guide

The analytics and emulation capabilities supported by X-ACT® arm business and technology leaders worldwide with the foresights they need to confidently respond to changing system dynamics and clearly understand which (and when) preventive and opportunistic actions should be taken to ensure the continuous efficiency and cost effectiveness of operations.

Using accurate, representative and reproducible models of business processes, applications and infrastructure, X-ACT delivers an end-to-end emulation of a service that accurately represents the behavior of system dynamics. The emulation replaces structures, characteristics and behaviors by perturbations exerted on dynamic equations through multiple order perturbations on dynamic coordinates such as volume, service quality and cost. This is very complex math, but it is handled entirely by X-ACT.

Once a system is transformed into an emulation, it allows users to quickly test and economically explore an unlimited number of scenarios that would otherwise be complex, expensive or even impossible to test on a real system. In comparison to other practices, such as simulation, emulation is superior in its ability to accurately replicate a system, but its biggest advantage is that it allows for the discovery of previously unknown patterns, which cannot be determined using any other method.

Now users can emulate risk because X-ACT can mathematically reproduce unknowns that may happen under certain conditions. Once the emulation process is complete, X-ACT users can change variables—such as volume, architecture and infrastructure or perform sensitivity predictions on changing process dynamics—to observe the outcomes (even when we have no historical record of these events ever happening).

Discovering the cause and effects of dynamic complexity is foundational to our universal risk management approach. Since conventional methods ignore the unknowns, risk often appears as a surprise that may potentially impact operational performance. To predict risk and anticipate the appropriate course of treatment, we must discover these unknowns and determine their current and future influence on system behavior.

The X-ACT: Using Metrics to Guide Decisions | How to Guide shows how companies use the advanced analytics and emulation capabilities supported by X-ACT to identify risk and take remedial actions by weighing the benefits, complexity and cost of available solutions.

Risk Management in the Age of Digital Disruption

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Today, as the repercussions of the Fourth Industrial Revolution begin to take hold, many corporations are fighting hidden risks that are engendered by the obsolescence of their cost structures, outdated business platform and practices, market evolution, client perception and pricing pressures that demand some form of action. But change is often a difficult choice as it implies a certain degree of unknown risk.

Current risk management practices, which deal mostly with the risk of reoccurring historical events, cannot help business, government or economic leaders deal with the uncertainty and rate of change driven by the Fourth Industrial Revolution. As new innovations threaten to disrupt, business leaders lack the means to measure the risks and rewards associated with the adoption of new technologies and business models. Established companies are faltering as leaner and more agile start-ups bring to market the new products and services that customers of the on-demand or sharing economy desire—with better quality, faster speeds and/or lower costs than established companies can match.

Due to the continuous adaptations driven by the Third Industrial Revolution, most organizations are now burdened by inefficient and unpredictable systems. Even as the inherent risks of current systems are recognized, many businesses are unable to confidently identify a successful path forward.

PwC’s 2015 Risk in Review survey of 1,229 senior executives and board members, reports that 73% of respondents agreed that risks to their companies are increasing. However, the survey shows companies are not, largely, responding to increasing threats with improved risk management programs. While executives are eager to confront business risks, boost management effectiveness, prevent costly misjudgments, drive efficiency and generate higher profit margin growth, only an elite group of companies (12% of the total surveyed) have put in place the processes and structures that qualify them as true risk management leaders per PwC’s criteria.

The shortcomings of traditional risk management technologies and probabilistic methodologies are largely to blame. According to Delloitte’s 2015 Global Risk Management Survey, 62% of respondents said that risk information systems and technology infrastructure were extremely or very challenging. Thirty-five percent of respondents considered identifying and managing new and emerging risks to be extremely or very challenging.

To remain competitive, companies must pursue two parallel strategies:

  1. Building agile and flexible risk management frameworks that can anticipate and prepare for the shifts that bring long-term success.
  2. Building the resiliency that will enable those frameworks to mitigate risk events and keep the business moving toward its goals.

While many risk management and business management experts agree on the need for better risk management methods and technologies, their proposed use of probabilistic methods of risk measurement and reliance on big data cannot fulfill the risk management requirements of the twenty-first century.

Many popular analytic methods are supported by nothing more than big data hype, which promises users that the more big data they have, the better conclusions they will be able to ascertain. However, if the dynamics of a system is continuously changing, any analysis based on big data will only be valid for the window of time during which the data was captured. Outside this window of time, an alignment with reality is unlikely.

To respond to the rate of change engendered by the Fourth Industrial Revolution, the practice of risk management must mature and become a scientific discipline. Our work with clients and research exposes the failures of traditional risk management practices. But many are not aware there is a better way to discover and treat risk. Ultimately, we will need more collaborators and partners who wish to teach business leaders and risk practitioners how new universal risk management approaches and mathematical-based emulation technologies can be used to identify new and emerging risks and prescriptively control business outcomes. If you are interested in joining our cause, please contact us as we are always looking for new research, technology and service partners.

How Dynamic Complexity Disrupts Business Operations

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Dynamic complexity always produces a negative effect in the form of loss, time elongation or shortage—causing inefficiencies and side effects, which are similar to friction, collision or drag. Dynamic complexity cannot be observed directly, only its effects can be measured. Additionally, dynamic complexity is impossible to predict from historic data—no matter the amount—because the number of states tend to be too large for any given set of samples. Therefore, trend analysis alone cannot sufficiently represent all possible and yet to be discovered system dynamics.

In the early stages, dynamic complexity is like a hidden cancer. Finding a single cancer cell in the human body is like looking for a specific grain of sand in a sandbox. And like cancer, often the disease will only be discovered once unexplained symptoms appear. To proactively treat dynamic complexity before it negatively impacts operations, we need diagnostics that can reliably reveal its future impact. System modeling and mathematical emulation allow us to provoke the existence of dynamic complexity through two hidden exerted system properties: the degree of interdependencies among system components and the multiple perturbations exerted by internal and external influences on both components and the edges connecting them directly or indirectly.

Successful risk determination and mitigation is dependent on how well we understand and account for dynamic complexity, its evolution, and the amount of time before the system will hit the singularity (singularities) through the intensification of stress on the dependencies and intertwined structures forming the system.

Knowing what conditions will cause singularities allows us to understand how the system can be stressed to the point at which it will no longer meet business objectives, and proactively put the risk management practices into place to avoid these unwanted situations.

Below we provide an example of a client case where dynamic complexity played a key role in terms of resource consumption, time to deliver, and volume to deliver. The scenario presented in the graph represents a trading and settlement implementation used by a volume of business that continuously increases. The reaction of the system is shown by the curves.

In the graph above, the production efficiency increases until it hits a plateau after which the business is increasingly impacted by a slowdown in productivity and increase in costs. The amount of loss is proportional to the increase in dynamic complexity, which gradually absorbs the resources (i.e. the cost) to deliver little. The singularity occurs when the two curves (productivity/revenue and cost) join, which in turn translates into loss in margin, over costing and overall instability.

In client cases such as this one, we have successfully used predictive emulation to isolate the evolving impact of dynamic complexity and calculate risk as an impact on system performance, cost, scalability and dependability. This allows us to measure changes in system health, when provoked by a change in dynamic complexity’s behavior under different process operational dynamics and identify the component(s) that cause the problem.

But knowing the how and what isn’t sufficient. We also need to know when, so we measure dynamic complexity itself, which then allows us to monitor its evolution and apply the right mitigation strategy at the right time.

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