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Exam Code: 000-575 Practice exam 2022 by team
IBM Tivoli Federated Identity Manager V6.2.2 Implementation
IBM Implementation action
Killexams : IBM Implementation action - BingNews Search results Killexams : IBM Implementation action - BingNews Killexams : 7 Basic Tools That Can Excellerate Quality

Hitoshi Kume, a recipient of the 1989 Deming Prize for use of quality principles, defines problems as "undesirable results of a job." Quality improvement efforts work best when problems are addressed systematically using a consistent and analytic approach; the methodology shouldn't change just because the problem changes. Keeping the steps to problem-solving simple allows workers to learn the process and how to use the tools effectively.

Easy to implement and follow up, the most commonly used and well-known quality process is the plan/do/check/act (PDCA) cycle (Figure 1). Other processes are a takeoff of this method, much in the way that computers today are takeoffs of the original IBM system. The PDCA cycle promotes continuous improvement and should thus be visualized as a spiral instead of a closed circle.

Another popular quality improvement process is the six-step PROFIT model in which the acronym stands for:

P = Problem definition.

R = Root cause identification and analysis.

O = Optimal solution based on root cause(s).

F = Finalize how the corrective action will be implemented.

I = Implement the plan.

T = Track the effectiveness of the implementation and verify that the desired results are met.

If the desired results are not met, the cycle is repeated. Both the PDCA and the PROFIT models can be used for problem solving as well as for continuous quality improvement. In companies that follow total quality principles, whichever model is chosen should be used consistently in every department or function in which quality improvement teams are working.

Quality Improvement

Figure 1. The most common process for quality improvement is the plan/do/check/act cycle outlined above. The cycle promotes continuous improvement and should be thought of as a spiral, not a circle.

7 Basic Quality Improvement Tools

Once the basic problem-solving or quality improvement process is understood, the addition of quality tools can make the process proceed more quickly and systematically. Seven simple tools can be used by any professional to ease the quality improvement process: flowcharts, check sheets, Pareto diagrams, cause and effect diagrams, histograms, scatter diagrams, and control charts. (Some books describe a graph instead of a flowchart as one of the seven tools.)

The concept behind the seven basic tools came from Kaoru Ishikawa, a renowned quality expert from Japan. According to Ishikawa, 95% of quality-related problems can be resolved with these basic tools. The key to successful problem resolution is the ability to identify the problem, use the appropriate tools based on the nature of the problem, and communicate the solution quickly to others. Inexperienced personnel might do best by starting with the Pareto chart and the cause and effect diagram before tackling the use of the other tools. Those two tools are used most widely by quality improvement teams.


Flowcharts describe a process in as much detail as possible by graphically displaying the steps in proper sequence. A good flowchart should show all process steps under analysis by the quality improvement team, identify critical process points for control, suggest areas for further improvement, and help explain and solve a problem.

The flowchart in Figure 2 illustrates a simple production process in which parts are received, inspected, and sent to subassembly operations and painting. After completing this loop, the parts can be shipped as subassemblies after passing a final test or they can complete a second cycle consisting of final assembly, inspection and testing, painting, final testing, and shipping.

Quality Improvement Tools

Figure 2. A basic production process flowchart displays several paths a part can travel from the time it hits the receiving dock to final shipping.

Flowcharts can be simple, such as the one featured in Figure 2, or they can be made up of numerous boxes, symbols, and if/then directional steps. In more complex versions, flowcharts indicate the process steps in the appropriate sequence, the conditions in those steps, and the related constraints by using elements such as arrows, yes/no choices, or if/then statements.

Check sheets

Check sheets help organize data by category. They show how many times each particular value occurs, and their information is increasingly helpful as more data are collected. More than 50 observations should be available to be charted for this tool to be really useful. Check sheets minimize clerical work since the operator merely adds a mark to the tally on the prepared sheet rather than writing out a figure (Figure 3). By showing the frequency of a particular defect (e.g., in a molded part) and how often it occurs in a specific location, check sheets help operators spot problems. The check sheet example shows a list of molded part defects on a production line covering a week's time. One can easily see where to set priorities based on results shown on this check sheet. Assuming the production flow is the same on each day, the part with the largest number of defects carries the highest priority for correction.

Quality Improvement Tools

Figure 3. Because it clearly organizes data, a check sheet is the easiest way to track information.

Pareto diagrams

The Pareto diagram is named after Vilfredo Pareto, a 19th-century Italian economist who postulated that a large share of wealth is owned by a small percentage of the population. This basic principle translates well into quality problems—most quality problems result from a small number of causes. Quality experts often refer to the principle as the 80-20 rule; that is, 80% of problems are caused by 20% of the potential sources.

A Pareto diagram puts data in a hierarchical order (Figure 4), which allows the most significant problems to be corrected first. The Pareto analysis technique is used primarily to identify and evaluate nonconformities, although it can summarize all types of data. It is perhaps the diagram most often used in management presentations.

Quality Improvement Tools

Figure 4. By rearranging random data, a Pareto diagram identifies and ranks nonconformities in the quality process in descending order.

To create a Pareto diagram, the operator collects random data, regroups the categories in order of frequency, and creates a bar graph based on the results.

Cause and effect diagrams

The cause and effect diagram is sometimes called an Ishikawa diagram after its inventor. It is also known as a fish bone diagram because of its shape. A cause and effect diagram describes a relationship between variables. The undesirable outcome is shown as effect, and related causes are shown as leading to, or potentially leading to, the said effect. This popular tool has one severe limitation, however, in that users can overlook important, complex interactions between causes. Thus, if a problem is caused by a combination of factors, it is difficult to use this tool to depict and solve it.

A fish bone diagram displays all contributing factors and their relationships to the outcome to identify areas where data should be collected and analyzed. The major areas of potential causes are shown as the main bones, e.g., materials, methods, people, measurement, machines, and design (Figure 5). Later, the subareas are depicted. Thorough analysis of each cause can eliminate causes one by one, and the most probable root cause can be selected for corrective action. Quantitative information can also be used to prioritize means for improvement, whether it be to machine, design, or operator.

Quality Improvement Tools

Figure 5. Fish bone diagrams display the various possible causes of the final effect. Further analysis can prioritize them.


The histogram plots data in a frequency distribution table. What distinguishes the histogram from a check sheet is that its data are grouped into rows so that the identity of individual values is lost. Commonly used to present quality improvement data, histograms work best with small amounts of data that vary considerably. When used in process capability studies, histograms can display specification limits to show what portion of the data does not meet the specifications.

After the raw data are collected, they are grouped in value and frequency and plotted in a graphical form (Figure 6). A histogram's shape shows the nature of the distribution of the data, as well as central tendency (average) and variability. Specification limits can be used to display the capability of the process.

Quality Improvement Tools

Figure 6. A histogram is an easy way to see the distribution of the data, its average, and variability.

Scatter diagrams

A scatter diagram shows how two variables are related and is thus used to test for cause and effect relationships. It cannot prove that one variable causes the change in the other, only that a relationship exists and how strong it is. In a scatter diagram, the horizontal (x) axis represents the measurement values of one variable, and the vertical (y) axis represents the measurements of the second variable. Figure 7 shows part clearance values on the x-axis and the corresponding quantitative measurement values on the y-axis.

Quality Improvement Tool

Figure 7. The plotted data points in a scatter diagram show the relationship between two variables.

Control charts

A control chart displays statistically determined upper and lower limits drawn on either side of a process average. This chart shows if the collected data are within upper and lower limits previously determined through statistical calculations of raw data from earlier trials.

The construction of a control chart is based on statistical principles and statistical distributions, particularly the normal distribution. When used in conjunction with a manufacturing process, such charts can indicate trends and signal when a process is out of control. The center line of a control chart represents an estimate of the process mean; the upper and lower critical limits are also indicated. The process results are monitored over time and should remain within the control limits; if they do not, an investigation is conducted for the causes and corrective action taken. A control chart helps determine variability so it can be reduced as much as is economically justifiable.

In preparing a control chart, the mean upper control limit (UCL) and lower control limit (LCL) of an approved process and its data are calculated. A blank control chart with mean UCL and LCL with no data points is created; data points are added as they are statistically calculated from the raw data.

Figure 8. Data points that fall outside the upper and lower control limits lead to investigation and correction of the process.

Figure 8 is based on 25 samples or subgroups. For each sample, which in this case consisted of five rods, measurements are taken of a quality characteristic (in this example, length). These data are then grouped in table form (as shown in the figure) and the average and range from each subgroup are calculated, as are the grand average and average of all ranges. These figures are used to calculate UCL and LCL. For the control chart in the example, the formula is ± A2R, where A2 is a constant determined by the table of constants for variable control charts. The constant is based on the subgroup demo size, which is five in this example.


Many people in the medical device manufacturing industry are undoubtedly familiar with many of these tools and know their application, advantages, and limitations. However, manufacturers must ensure that these tools are in place and being used to their full advantage as part of their quality system procedures. Flowcharts and check sheets are most valuable in identifying problems, whereas cause and effect diagrams, histograms, scatter diagrams, and control charts are used for problem analysis. Pareto diagrams are effective for both areas. By properly using these tools, the problem-solving process can be more efficient and more effective.

Those manufacturers who have mastered the seven basic tools described here may wish to further refine their quality improvement processes. A future article will discuss seven new tools: relations diagrams, affinity diagrams (K-J method), systematic diagrams, matrix diagrams, matrix data diagrams, process decision programs, and arrow diagrams. These seven tools are used less frequently and are more complicated.

Ashweni Sahni is director of quality and regulatory affairs at Minnetronix, Inc. (St. Paul, MN), and a member of MD&DI's editorial advisory board.

Tue, 12 Jul 2022 12:00:00 -0500 en text/html
Killexams : The IBM 1401’s Unique Qui-Binary Arithmetic

Old mainframe computers are interesting, especially to those of us who weren’t around to see them in action. We sit with old-timers and listen to their stories of the good ol’ days. They tell us about loading paper tape or giving instructions one at a time with toggle switches and LED output indicators. We hang on every word because its interesting to know how we got to this point in the tech-timeline and we appreciate the patience and insanity it must have taken to soldier on through the “good ol’ days”.

[Ken Shirriff] is making those good ol’ days come alive with a series of articles relating to his work with hardware at the Computer History Museum. His latest installment is an article describing the strange implementation of the IBM 1401’s qui-binary arithmetic. Full disclosure: It has not been confirmed that [Ken] is an “old-timer” however his article doesn’t help the argument that he isn’t.

Ken describes in thorough detail how the IBM 1401 — which was first introduced in 1959 — takes a decimal number as an input and operates on it one BCD digit at a time. Before performing the instruction the BCD number is converted to qui-binary. Qui-binary is represented by 7 bits, 5 qui bits and 2 binary bits: 0000000. The qui portion represents the largest even number contained in the BCD value and the binary portion represents a 1 if the BCD value is odd or a 0 for even. For example if the BCD number is 9 then the Q8 bit and the B1 bit are set resulting in: 1000010.

The qui-binary representation makes for easy error checking since only one qui bit should be set and only one binary bit should be set. [Ken] goes on to explain more complex arithmetic and circuitry within the IBM 1401 in his post.

If you aren’t familiar with [Ken], we covered his reverse engineering of the Sinclair Scientific Calculator, his explanation of the TL431, and of course the core memory repair that is part of his Computer History Museum work.

Thanks for the tip [bobomb].

Thu, 16 Jun 2022 12:00:00 -0500 Brandon Dunson en-US text/html
Killexams : Comprehensive Change Management for SoC Design By Sunita Chulani1, Stanley M. Sutton Jr.1, Gary Bachelor2, and P. Santhanam1
1 IBM T. J. Watson Research Center, 19 Skyline Drive, Hawthorne, NY 10532 USA
2 IBM Global Business Services, PO BOX 31, Birmingham Road, Warwick CV34 5JL UK


Systems-on-a-Chip (SoC) are becoming increasingly complex, leading to corresponding increases in the complexity and cost of SoC design and development.  We propose to address this problem by introducing comprehensive change management.  Change management, which is widely used in the software industry, involves controlling when and where changes can be introduced into components so that changes can be propagated quickly, completely, and correctly.
In this paper we address two main topics:   One is typical scenarios in electronic design where change management can be supported and leveraged. The other is the specification of a comprehensive schema to illustrate the varieties of data and relationships that are important for change management in SoC design.


SoC designs are becoming increasingly complex.  Pressures on design teams and project managers are rising because of shorter times to market, more complex technology, more complex organizations, and geographically dispersed multi-partner teams with varied “business models” and higher “cost of failure.”

Current methodology and tools for designing SoC need to evolve with market demands in key areas:  First, multiple streams of inconsistent hardware (HW) and software (SW) processes are often integrated only in the late stages of a project, leading to unrecognized divergence of requirements, platforms, and IP, resulting in unacceptable risk in cost, schedule, and quality.  Second, even within a stream of HW or SW, there is inadequate data integration, configuration management, and change control across life cycle artifacts.  Techniques used for these are often ad hoc or manual, and the cost of failure is high.  This makes it difficult for a distributed group team     to be productive and inhibits the early, controlled reuse of design products and IP.  Finally, the costs of deploying and managing separate dedicated systems and infrastructures are becoming prohibitive.

We propose to address these shortcomings through comprehensive change management, which is the integrated application of configuration management, version control, and change control across software and hardware design.  Change management is widely practiced in the software development industry.  There are commercial change-management systems available for use in electronic design, such as MatrixOne DesignSync [4], ClioSoft SOS [2], IC Manage Design Management [3], and Rational ClearCase/ClearQuest [1], as well as numerous proprietary, “home-grown” systems.  But to date change management remains an under-utilized technology in electronic design.

In SoC design, change management can help with many problems.  For instance, when IP is modified, change management can help in identifying blocks in which the IP is used, in evaluating other affected design elements, and in determining which tests must be rerun and which rules must be re-verified. Or, when a new release is proposed, change management can help in assessing whether the elements of the release are mutually consistent and in specifying IP or other resources on which the new release depends.

More generally, change management gives the ability to analyze the potential impact of changes by tracing to affected entities and the ability to propagate changes completely, correctly, and efficiently.  For design managers, this supports decision-making as to whether, when, and how to make or accept changes.  For design engineers, it helps in assessing when a set of design entities is complete and consistent and in deciding when it is safe to make (or adopt) a new release.

In this paper we focus on two elements of this approach for SoC design.  One is the specification of representative use cases in which change management plays a critical role.  These show places in the SoC development process where information important for managing change can be gathered.  They also show places where appropriate information can be used to manage the impact of change.  The second element is the specification of a generic schema for modeling design entities and their interrelationships.  This supports traceability among design elements, allows designers to analyze the impact of changes, and facilitates the efficient and comprehensive propagation of changes to affected elements.

The following section provides some background on a survey of subject-matter experts that we performed to refine the problem definition.     


We surveyed some 30 IBM subject-matter experts (SMEs) in electronic design, change management, and design data modeling.  They identified 26 problem areas for change management in electronic design.  We categorized these as follows:

  • visibility into project status
  • day-to-day control of project activities
  • organizational or structural changes
  • design method consistency
  • design data consistency

Major themes that crosscut these included:

  • visibility and status of data
  • comprehensive change management
  • method definition, tracking, and enforcement
  • design physical quality
  • common approach to problem identification and handling

We held a workshop with the SMEs to prioritize these problems, and two emerged     as the most significant:  First, the need for basic management of the configuration of all the design data and resources of concern within a project or work package (libraries, designs, code, tools, test suites, etc.); second, the need for designer visibility into the status of data and configurations in a work package.

To realize these goals, two basic kinds of information are necessary:  1) An understanding of how change management may occur in SoC design processes; 2) An understanding of the kinds of information and relationships needed to manage change in SoC design.  We addressed the former by specifying change-management use cases; we addressed the latter by specifying a change-management schema.


This section describes typical use cases in the SoC design process.  Change is a pervasive concern in these use cases—they cause changes, respond to changes, or depend on data and other resources that are subject to change.  Thus, change management is integral to the effective execution of each of these use cases. We identified nine representative use cases in the SoC design process, which are shown in Figure 1.

Figure 1.  Use cases in SoC design

In general there are four ways of initiating a project: New Project, Derive, Merge and Retarget.  New Project is the case in which a new project is created from the beginning.  The Derive case is initiated when a new business opportunity arises to base a new project on an existing design. The Merge case is initiated when an actor wants to merge configuration items during implementation of a new change management scheme or while working with teams/organizations outside of the current scheme. The Retarget case is initiated when a project is restructured due to resource or other constraints.  In all of these use cases it is important to institute proper change controls from the outset.  New Project starts with a clean slate; the other scenarios require changes from (or to) existing projects.    

Once the project is initiated, the next phase is to update the design. There are two use cases in the Update Design composite state.  New Design Elements addresses the original creation of new design elements.  These become new entries in the change-management system.  The Implement Change use case entails the modification of an existing design element (such as fixing a bug).  It is triggered in response to a change request and is supported and governed by change-management data and protocols.

The next phase is the Resolve Project and consists of 3 use cases. Backout is the use case by which changes that were made in the previous phase can be reversed.  Release is the use case by which a project is released for cross functional use. The Archive use case protects design asset by secure copy of design and environment.


The main goal of the change-management schema is to enable the capture of all information that might contribute to change management

4.1     Overview

The schema, which is defined in the Unified Modeling Language (UML) [5], consists of several high-level packages (Figure 2).

Click to enlarge

Figure 2.  Packages in the change-management schema

Package Data represents types for design data and metadata.  Package Objects and Data defines types for objects and data.  Objects are containers for information, data represent the information.  The main types of object include artifacts (such as files), features, and attributes.  The types of objects and data defined are important for change management because they represent the principle work products of electronic design: IP, VHDL and RTL specifications, floor plans, formal verification rules, timing rules, and so on.  It is changes to these things for which management is most needed.

The package Types defines types to represent the types of objects and data.  This enables some types in the schema (such as those for attributes, collections, and relationships) to be defined parametrically in terms of other types, which promotes generality, consistency, and reusability of schema elements.

Package Attributes defines specific types of attribute.  The basic attribute is just a name-value pair that is associated to an object.  (More strongly-typed subtypes of attribute have fixed names, value types, attributed-object types, or combinations of these.)  Attributes are one of the main types of design data, and they are important for change management because they can represent the status or state of design elements (such as version number, verification level, or timing characteristics).

Package Collections defines types of collections, including collections with varying degrees of structure, typing, and constraints.  Collections are important for change management in that changes must often be coordinated for collections of design elements as a group (e.g., for a work package, verification suite, or IP release).  Collections are also used in defining other elements in the schema (for example, baselines and change sets).

The package Relationships defines types of relationships.  The basic relationship type is an ordered collection of a fixed number of elements.  Subtypes provide directionality, element typing, and additional semantics.  Relationships are important for change management because they can define various types of dependencies among design data and resources.  Examples include the use of macros in cores, the dependence of timing reports on floor plans and timing contracts, and the dependence of test results on tested designs, test cases, and test tools.  Explicit dependency relationships support the analysis of change impact and the efficient and precise propagation of changes,

The package Specifications defines types of data specification and definition.  Specifications specify an informational entity; definitions denote a meaning and are used in specifications.

Package Resources represents things (other than design data) that are used in design processes, for example, design tools, IP, design methods, and design engineers.  Resources are important for change management in that resources are used in the actions that cause changes and in the actions that respond to changes.  Indeed, minimizing the resources needed to handle changes is one of the goals of change management.

Resources are also important in that changes to a resource may require changes to design elements that were created using that resource (for example, when changes to a simulator may require reproduction of simulation results).

Package Events defines types and instances of events.  Events are important in change management because changes are a kind of event, and signals of change events can trigger processes to handle the change.

The package Actions provides a representation for things that are done, that is, for the behaviors or executions of tools, scripts, tasks, method steps, etc.  Actions are important for change in that actions cause change.  Actions can also be triggered in response to changes and can handle changes (such as by propagating changes to dependent artifacts).

Subpackage Action Definitions defines the type Action Execution, which contains information about a particular execution of a particular action.  It refers to the definition of the action and to the specific artifacts and attributes read and written, resources used, and events generated and handled.  Thus an action execution indicates particular artifacts and attributes that are changed, and it links those to the particular process or activity by which they were changed, the particular artifacts and attributes on which the changes were based, and the particular resources by which the changes were effected.  Through this, particular dependency relationships can be established between the objects, data, and resources.  This is the specific information needed to analyze and propagate concrete changes to artifacts, processes, resources.

Package Baselines defines types for defining mutually consistent set of design artifacts. Baselines are important for change management in several respects.  The elements in a baseline must be protected from arbitrary changes that might disrupt their mutual consistency, and the elements in a baseline must be changed in mutually consistent ways in order to evolve a baseline from one version to another.

The final package in Figure 2 is the Change package.  It defines types that for representing change explicitly.  These include managed objects, which are objects with an associated change log, change logs and change sets, which are types of collection that contain change records, and change records, which record specific changes to specific objects.  They can include a reference to an action execution that caused the change

The subpackage Change Requests includes types for modeling change requests and responses.  A change request has a type, description, state, priority, and owner.  It can have an associated action definition, which may be the definition of the action to be taken in processing the change request.  A change request also has a change-request history log.

4.2    Example

An example of the schema is shown in Figure 3.  The clear boxes (upper part of diagram) show general types from the schema and the shaded boxes (lower part of the diagram) show types (and a few instances) defined for a specific high-level design process project at IBM.

Click to enlarge

Figure 3.  Example of change-management data

The figure shows a dependency relationship between two types of design artifact, VHDLArtifact and FloorPlannableObjects.  The relationship is defined in terms of a compiler that derives instances of FloorPlannableObjects from instances of VHDLArtifact.  Execution of the compiler constitutes an action that defines the relationship.  The specific schema elements are defined based on the general schema using a variety of object-oriented modeling techniques, including subtyping (e.g., VHDLArtifact), instantiation (e.g., Compile1) and parameterization (e.g. VHDLFloorplannable ObjectsDependency).


Here we present an example use case, Implement Change, with details on its activities and how the activities use the schema presented in Section 4.  This use case is illustrated in Figure 4.

Click to enlarge

Figure 4.  State diagram for use case Implement Change

The Implement Change use case addresses the modification of an existing design element (such as fixing a bug).  It is triggered by a change request.  The first steps of this use case are to identify and evaluate the change request to be handled.  Then the relevant baseline is located, loaded into the engineer’s workspace, and verified.  At this point the change can be implemented.  This begins with the identification of the artifacts that are immediately affected.  Then dependent artifacts are identified and changes propagated according to dependency relationships.  (This may entail several iterations.)  Once a stable state is achieved, the modified artifacts are Verified and regression tested.  Depending on test results, more changes may be required.  Once the change is considered acceptable, any learning and metrics from the process are captured and the new artifacts and relationships are promoted to the public configuration space.


This paper explores the role of comprehensive change management in SoC design, development, and delivery.  Based on the comments of over thirty experienced electronic design engineers from across IBM, we have captured the essential problems and motivations for change management in SoC projects. We have described design scenarios, highlighting places where change management applies, and presented a preliminary schema to show the range of data and relationships change management may incorporate.  Change management can benefit both design managers and engineers.  It is increasingly essential for improving productivity and reducing time and cost in SoC projects.


Contributions to this work were also made by Nadav Golbandi and Yoav Rubin of IBM’s Haifa Research Lab.  Much information and guidance were provided by Jeff Staten and Bernd-josef Huettl of IBM’s Systems and Technology Group. We especially thank Richard Bell, John Coiner, Mark Firstenberg, Andrew Mirsky, Gary Nusbaum, and Harry Reindel of IBM’s Systems and Technology Group for sharing design data and experiences.  We are also grateful to the many other people across IBM who contributed their time and expertise.







Sun, 26 Jun 2022 12:00:00 -0500 en text/html
Killexams : Beacon Leadership Council

Vincent Caprio founded the Water Innovations Alliance Foundation (WIAF) in October 2008. In this role he created the Water 2.0 Conference series of which he is currently the Chairman Emeritus. As an early advocate for nanotechnology, Mr. Caprio is the Founder and Chairman Emeritus of the NanoBusiness Commercialization Association (NanoBCA). In 2002, he launched the highly successful NanoBusiness Conference series, now in its 19th year. 

A pioneer at the intersection of business and technology, Vincent Caprio possesses a unique ability to spot emerging and societally significant technologies in their early stages. He successfully creates brands and business organizations focused on specific technology markets, and launches events that not only educate, but also connect and empower stakeholders that include investors, technologists, CEOs and politicians. 

It is Mr. Caprio’s avid interest in history and background in finance that enabled him to be among the first to recognize the impact that specific technologies will have on business and society. By building community networks centered around his conferences, he has facilitated the growth of important new technologies, including nanotechnology, clean water technology and most recently, engineering software. 

Mr. Caprio is also one of the foremost advocates for government funding of emerging technology at both the State and Federal levels. He has testified before Congress, EPA, Office of Science and Technology Policy (OSTP), as well as the state legislatures of New York and Connecticut, and has been an invited speaker at over 100 events. Mr. Caprio has also organized public policy tours in Washington, DC, educating politicians about emerging tech through meetings with high-level technology executives. 

In the events sector, Mr. Caprio served as the Event Director who launched of The Emerging Technologies Conference in association with MIT’s Technology Review Magazine. He also acted as consultant to the leading emerging technology research and advisory firm Lux Research, for its Lux Executive Summit in 2005 & 2006. In 2002, Mr. Caprio served as the Event Director and Program Director of the Forbes/IBM Executive Summit. 

Prior to founding the NanoBCA, Mr. Caprio was Event Director for Red Herring Conferences, producing the company’s Venture Market conferences and Annual Summit reporting to Red Herring Magazine Founder and Publisher Tony Perkins, and Editor, Jason Pontin. His industry peers have formally recognized Mr. Caprio on several occasions for his talents in both tradeshow and conference management. 

Mr. Caprio was named Sales Executive of the Year in 1994 while employed with Reed Exhibitions, and was further honored with three Pathfinder Awards in 1995 for launching The New York Restaurant Show, Buildings Chicago and Buildings LA. 

Prior to joining Reed Elsevier’s office of the Controller in 1989, Mr. Caprio was employed at Henry Charles Wainwright investment group as a Senior Tax Accountant. In the 1980’s, he specialized in the preparation of 1120, 1065 and 1040 tax forms, and was also employed with the Internal Revenue Service from 1979- 1981. 

During the past 10 years, Mr. Caprio has been involved in numerous nonprofit philanthropic activities including: Fabricators & Manufacturers Association (FMA), Easton Learning Foundation, Easton Community Center, Easton Racquet Club, First Presbyterian Church of Fairfield, Omni Nano, FBI Citizen’s Academy, Villanova Alumni Recruitment Network and Easton Exchange Club. 

Mr. Caprio graduated from Villanova University with a Bachelor of Science in Accounting/MIS from the Villanova School of Business. He received an MBA/MPA from Fairleigh Dickinson University. 

In the spring of 2015, Mr. Caprio was appointed to Wichita State University's Applied Technology Acceleration Institute (ATAI) as a water and energy expert. In 2017 he was named Program Director of the Center for Digital Transformation at Pfeiffer University. Mr. Caprio was elected in November 2016 and serves as the Easton, Connecticut Registrar of Voters. 

Mon, 23 May 2022 19:36:00 -0500 en text/html
Killexams : Security tool will help protect against 'quantum' hackers

Professor Steven Galbraith, Head of Department of Mathematics at Auckland University. Photo / Supplied

A security tool picked up by the US Government is based on Auckland University research and will help protect against cyber attacks from "quantum" hackers.

Crystals-Dilithium is the name of one of four "quantum-resistant encryption systems" approved for use by the US National Institute of Standards and Technology last week.

"Quantum-resistant encryption" refers to security systems that can withstand attacks by quantum computers - a new generation of computers, hundreds of million times more powerful than the most advanced supercomputers today.

The system was built on research co-authored by Professor Steven Galbraith, Head of the Department of Mathematics at Auckland University.

Current cryptography methods rely on mathematical algorithms so complicated that even supercomputers would take millennia to solve, but the advance and wider accessibility of quantum computers would make this redundant.

In 2019, an algorithm expected to take IBM's supercomputer Summit 10,000 years to compute was completed in a mere 200 seconds by Google's quantum computer.

"A hacker with a quantum computer could decrypt a lot of sensitive information, including health records and national security information. They could also do industrial espionage by getting access to the intellectual property of companies," Galbraith said.

New Zealand's institutional cybersecurity (or lack of) was exposed when the Waikato District Health Board was hacked last year, leaving systems disabled and leaking confidential information.

The attack did not involve quantum computers, raising concerns regarding the inadequate cybersecurity practices in place now, let alone preventing attacks in the future.

"At the moment the only people with quantum computers are large governments and large companies like IBM and Google," Galbraith said.

"Hackers do not have access to their own quantum computers. But the business model of IBM and Google will be to sell access to their quantum computers…much like how Amazon sells access to the AWS system for machine learning," he told the Herald.

Post-quantum cryptography helps to prevent attacks by "quantum hackers".

"Post-quantum cryptography is a more practical solution for the real world.

"[Post-quantum cryptography] can be used on current computers, phones and networks… but is based on different mathematics and so is secure against an attacker with a quantum computer."

Crystals-Dilithium is based on a mathematical principle called structured lattices and is used for digital signatures.

Digital signatures are a secure way of authenticating the authenticity of a digital document, using mathematical algorithms.

The paper Galbraith co-authored in 2016 introduced a way to reduce the size of these certificates, improving their usability and ease of implementation in other systems.

Current applications of digital signatures include online credentials (e.g. passports, electronic driver's licenses), electronic contracts, cryptocurrency, and automatic software updates.

Digital signatures are one of many systems constantly operating in the background, making access to secure online services possible.

"In the future, there will be changes in the software to make the system post-quantum, but people will not notice the difference. Cryptography is usually invisible to the users."

Considering New Zealand's limited investment in the field, the contribution of local research is an even greater achievement.

"I (together with my students) am the only person studying post-quantum cryptography [in New Zealand]. There is not a lot of investment. In 2014 I had no funding for the work from outside the university," he says.

"I don't think there is likely to be a lot of investment and innovation in post-quantum cryptography in New Zealand… but, there is hope for NZ to be a leader in cybersecurity more broadly."

Last month G7 leaders called for "allied action" on a myriad of courses including technological standards, stating a commitment "to develop and implement robust international cyber norms".

The leaders also addressed concerns surrounding China's artificial intelligence development and potential technological dominance.

"Due to our size, if Government and industry were better at collaborating and sharing information we could drive innovation in a number of areas, such as threat detection and prevention, data sovereignty, protection of critical infrastructure, etc."

Mon, 11 Jul 2022 14:47:00 -0500 en text/html
Killexams : IBM Transforms Business Operations with the RISE with SAP Solution in Expanded Partnership with SAP

Expanded Premium provider Option with IBM for RISE with SAP Now Supports Cloud Workloads Using IBM Power on Red Hat Enterprise Linux on IBM Cloud

ARMONK, N.Y. and WALLDORF, Germany, May 11, 2022 /PRNewswire/ -- IBM (NYSE: IBM) and SAP today announced the latest milestone in their long-standing partnership as IBM undertakes one of the world's largest corporate transformation projects based on SAP ® ERP software, designed to fuel the company's growth and better support its clients.

As part of the expanded partnership, IBM is migrating to SAP S/4HANA ®, SAP's next-generation ERP software, to perform work across more than 120 countries, 1,000 legal entities and numerous IBM businesses supporting software, hardware, consulting and finance. The project is focused on improving business processes with RISE with SAP S/4HANA Cloud, private edition, premium provider option with IBM Consulting, and will ultimately move more than 375 TB of data to IBM Power on Red Hat Enterprise Linux on IBM Cloud. RISE with SAP brings together what businesses need to pursue their digital transformation objectives and accelerate their move to the cloud.

Driven by the need to modernize processes and deliver better insights to support clients running in the cloud, RISE with SAP is helping IBM centralize and standardize data worldwide. With access to the SAP HANA ® database, data can be accessed in real time and shared more efficiently among business units and teams. The expanded partnership will also help with improved decision-making supported by AI and automated workflows. Once the transformation is completed, nearly all of IBM's US$58 billion in revenue will flow through SAP software.

"This expanded partnership will enable IBM to accelerate its business transformation in the cloud and fuel its future growth," said Christian Klein, CEO and Member of the Executive Board of SAP SE. "As a result, IBM will be positioned to provide the highest value of support and flexibility to its clients, allowing them to simplify and accelerate their business transformations while benefitting from the full value of RISE with SAP."

This business  transformation will eventually move more than 300 SAP instances and consolidate 500 servers with the RISE with SAP solution on IBM Power on Red Hat Enterprise Linux on IBM Cloud. The migration to SAP S/4HANA is already in progress across the company's software business unit. The initial deployment is focused on IBM's software-as-a-service and billing system and is already benefiting clients and IBM business partners through simplified billing and payment systems while enabling orders and contracts to be processed quickly.

IBM Consulting, with more than 38,000 highly trained SAP consultants, is leading the transformation providing the advisory, implementation, security, industry and technical expertise required to move these complex systems and applications to a digital environment. This is another example of IBM and SAP's accelerated ecosystem strategy, teaming up on both technology and consulting expertise while supporting most any cloud environment to help make it easier for clients  to embrace a hybrid cloud approach and move their mission-critical SAP software workloads to the cloud.

"Enterprise clients are seeking increased choice and control as they modernize their mission-critical workloads. Enabled by RISE with SAP, this is a milestone business transformation initiative for both companies due to its complexity and scale," said Arvind Krishna, IBM Chairman and Chief Executive Officer. "With this move, and IBM's experience using RISE with SAP internally, we will be even better prepared to support our clients on their hybrid cloud and business transformation journeys."

Expanded Premium provider Option for RISE with SAP on  IBM Power  on Red Hat Enterprise Linux on IBM Cloud

To provide clients more flexibility and computing power, including those in highly regulated industries, IBM is making the same cloud-based computing power that is underpinning its own migration available to clients. For clients who run RISE with SAP on IBM Cloud, an expansion of the premium provider option  provides an additional choice to run workloads on IBM Power on Red Hat Enterprise Linux on IBM Cloud.

As a premium supplier, IBM was the first cloud provider to offer infrastructure, technical managed services, business transformation and application management services as part of RISE with SAP. With clients increasingly leveraging hybrid cloud strategies to modernize their workloads, IBM and SAP are giving clients running on Power servers the ability to use RISE with SAP S/4HANA on Power infrastructure consistent with the architecture they run on premise. Underpinned exclusively by Red Hat Enterprise Linux, businesses running IBM Power on IBM Cloud will be able to achieve high levels of performance in a cloud environment for their mission-critical workloads, with the flexibility, resiliency and security features delivered by IBM and Red Hat.

To learn more about the RISE with SAP offering, please visit:

About IBM

IBM is a leading global hybrid cloud and AI, and business services provider. We help clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Nearly 3,000 government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM's hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM's breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and business services deliver open and flexible options to our clients. All of this is backed by IBM's legendary commitment to trust, transparency, responsibility, inclusivity and service.

Visit for more information.

Statements regarding IBM's future direction and intent are subject to change or withdrawal without notice and represent goals and objectives only.

About SAP

SAP's strategy is to help every business run as an intelligent, sustainable enterprise. As a market leader in enterprise application software, we help companies of all sizes and in all industries run at their best: SAP customers generate 87% of total global commerce. Our machine learning, Internet of Things (IoT), and advanced analytics technologies help turn customers' businesses into intelligent enterprises. SAP helps provide people and organizations deep business insight and fosters collaboration that helps them stay ahead of their competition. We simplify technology for companies so they can consume our software the way they want – without disruption. Our end-to-end suite of applications and services enables business and public customers across 25 industries globally to operate profitably, adapt continuously, and make a difference. With a global network of customers, partners, employees, and thought leaders, SAP helps the world run better and Excellerate people's lives. For more information, visit

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause real results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of SAP's 2021 Annual Report on Form 20-F.

SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE in Germany and other countries. Please  see  for additional trademark information and notices.

Red Hat, Red Hat Enterprise Linux and the Red Hat logo are trademarks or registered trademarks of Red Hat, Inc. or its subsidiaries in the U.S. and other countries. Linux ® is the registered trademark of Linus Torvalds in the U.S. and other countries.

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Wed, 11 May 2022 08:39:00 -0500 text/html
Killexams : Quantum Computing Becoming Real

Quantum computing will begin rolling out in increasingly useful ways over the next few years, setting the stage for what ultimately could lead to a shakeup in high-performance computing and eventually in the cloud.

Quantum computing has long been viewed as some futuristic research project with possible commercial applications. It typically needs to run at temperatures close to absolute zero, which means most people never actually will see this technology in action, which is probably a good thing because quantum computers today are still a sea of crudely connected cables. And so far, it has proven difficult to create enough qubits for a long enough period of time to be useful. But the tide appears to be turning, both for how to extend the lifetime of quantum bits, also known as qubits, as well as the number of qubits that are available.

A qubit is the unit of quantum information that is equivalent to the binary bit in classical computing. What makes qubits so interesting is that the 1s and 0s can be superimposed, which means that it can perform many calculations at the same time in parallel. So unlike a binary computer, where a bit is either 0 or 1, a quantum computer has three basic states—0, 1, and 0 or 1. In greatly oversimplified terms, that allows operations can be carried out using different values at the same time. Coupled with well-constructed algorithms, quantum computers will be at least as powerful as today’s supercomputers, and in the future they are expected to be orders of magnitude more powerful.

“The first applications will probably be in things like quantum chemistry or quantum simulations,” said Jeff Welser, vice president and lab director at IBM Research Almaden. “People are looking for new materials, simulating molecules such as drug molecules, and to do that you probably only need to be at around 100 qubits. We’re at 50 qubits today. So we’re not that far off. It’s going to happen within the next year or two. The example I provide is the caffeine molecule, because it’s a molecule we all love. It’s a fairly small molecule that has 95 electrons. To simulate the molecule, you simulate the electron states. But if you were to exactly simulate the 95 electrons on that to actually figure out the energy state configuration, it would take 1048 classical bits. There are 1050 atoms in the planet Earth, so there’s no way you’re ever going to build a system with 1048 classical bits. It’s nuts. It would only require 160 qubits to do those all exactly, because the qubits can take on exactly all the quantum states and have all the right entanglements.”

Fig. 1: IBM’s 50Q system. Source: IBM

Exact numbers and timing tend to get a bit fuzzy here. While almost everyone agrees on the potential of quantum computing, the rollout schedule and required number of qubits is far from clear. Not all qubits are the same, and not all algorithms are created equal.

“There are two elements driving this technology,” said Jean-Eric Michellet, senior director of innovation and technology at Leti. “One is the quality of the qubit. The other is the number of qubits. You need to achieve both quality and quantity, and that is a race that is going on right now.”

These two factors are closely intertwined, because there also are two different types of qubits, logical and physical. The logical qubit can be used for programming, while the physical qubit is an real implementation of a qubit. Depending on the quality of the qubit, which is measured in accuracy and coherency time (how long a qubit lasts), the ratio of logical and physical qubits will change. The lower the quality, the more physical qubits are required.

Another piece is the quality of the quantum algorithms, and there is much work to be done here. “We’re still at the beginning of the software,” said Michellet. “This is a new way of doing algorithms.”

Yet even with the relatively crude algorithms and qubit technology today, quantum computing is beginning to show significant progress over classical computing methods.

“The performance (for quantum computing) is exponential in behavior,” said James Clarke, director of quantum hardware at Intel Labs. “For very small problems, you probably have quite a bit of overhead. When we measure traditional algorithms, there is some crossover point. A quantum algorithm is going to be exponentially faster. There are discussions in the community that this crossover point would be 50 qubits. We actually think it’s more like a thousand or so for certain types of optimization algorithms.”

Intel is working on two qubit technologies—superconducting qubits and spin qubits in CMOS. The company recently demonstrated a 49-qubit computer, based on superconducting technology it has code-named Tangle Lake.

Fig. 2: Intel’s 49-qubit Tangle Lake processor, including 108 RF gold connectors for microwave signals. Source: Intel

Faster sums of all fears
One of the key drivers behind quantum computing is a concern that it can be used to break ciphers that would take too long using conventional computers. The general consensus among security experts is that all ciphers can be broken with enough time and effort, but in the most secure operations that could take years or even decades. With a powerful quantum computer, the time could be reduced to minutes, if not seconds.

This has spawned massive investment by governments, universities, industry, and groups composed of all of those entities.

“Cryptography has really driven research at the government level around the world,” said Clarke. “The thought that security would be compromised is perhaps a worry but perhaps a goal for something like a quantum computer. Within this space, it actually requires a very powerful quantum computer that’s probably many years off.”

The more pressing question involves security measures that are in place today.

“Some, not all, cryptography algorithms will break with quantum computing,” said Paul Kocher, an independent cryptography and computer security expert. “We’re probably not at risk of things being broken over the next five years. But if you record something now, what happens in 30 years? With undercover operations you expect them to be secret for a long time. Something like AES 56 is not breakable any faster with a quantum computer than a conventional computer. The same is true for long keys. But with public keys like RSA and Diffie-Hellman key exchange, those could be broken. We’re still far away from building a quantum computer that could do that, but this could up-end the whole game on the PKI (public key infrastructure) front. Those things are suddenly at risk.”

Challenges remain
Today’s qubits are far from perfect. Unlike classical bits, they don’t exist for very long, and they aren’t completely accurate.

“That’s the major focus for quantum computing right now,” said IBM’s Welser. “It’s not only how to increase the number of qubits, which we know how to do just by continuing to build more of them. But how do you build them and get the error rates down, and increase coherency time, so that you can actually have time to manipulate those qubits and have them interact together? If you have 100 qubits, but the coherency time is only 100 microseconds, you can’t get them all to interact efficiently to do an real algorithm before they all have an error. In order to move forward, we talk about something called quantum volume, which then takes into account the number of qubits, the coherency time, the length of time they stay stable, and the number that can be entangled together. Those factors provide what we believe is the best way to compare quantum computers to each other.”

IBM is focused on quantum volume as the best path forward, but that point is the subject of debate in academic circles today. “Clearly, getting that coherency time to go longer is important,” Welser said. “But even at the level we’re at right now, we simulated three-atom molecules on our 7-qubit machine and showed that it works. They are error prone, but they get the right answer. You just run the simulation of thousand times—it takes very little time to do that—and then you take the probabilities that come out of that and you map out your answer.”

One of the key metrics here is the classic traveling salesman problem. If a salesman has a certain route to cover that involves multiple cities that are not in a straight line, what is the most efficient way to manage travel? There is no simple answer to this problem, and it has been vexing mathematicians since it was first posed in 1930. There have even been biological comparisons based upon how bees pollinate plants, because bees are known to be extremely efficient. But the bee studies conclude that complete accuracy isn’t critical, as long as it’s good enough.

And that raises some interesting questions about how computing should be done. Rather than exact answers to computational problems, the focus shifts to distributions. That requires less power, improves performance, and it works well enough for big problems such as financial valuation modeling.

Welser said banks already have begun exploring the quantum computing space. “They want to get started working on it now just to figure out what the right algorithms are, and understand how these systems will run and how to integrate them in with the rest of all of their simulations. But they’ll continue to use HPC systems, as well.”

Economies of efficiency
With the power/performance benefits of scaling classical computing chips diminishing at each node after 28nm, and the costs rising for developing chips at the latest process nodes, quantum computing opens up a whole new opportunity. That fact hasn’t been lost on companies such as IBM, Intel, Microsoft, Google and D-Wave Systems, all of which are looking to commercialize the technology.

Fig. 3: D-Wave’s quantum chips. Source: D-Wave

The big question is whether this can all be done using economies of scale in silicon manufacturing, which is already in place and well proven.

“These are larger chips,” said Intel’s Clarke. “For a small chip with 2 qubits, those we can wirebond to our package. Any larger than that, we are starting to do flip-chip bonding. Any larger than about 17, we are adding superconducting TSVs.”

That’s one way of approaching qubit manufacturing, but certainly not the only way. “We are also studying spin qubits in silicon,” Clarke said. “Basically, what we are doing is creating a silicon electron transistor. Instead of having a current through your channels, we trap a single electron in our channel. We put a magnet in the refrigerator. So a single electron in a magnetic field spins up or spins down. Those are the two states of the qubit. Why is this appealing? One of these qubits is a million times smaller than a superconducting qubit in terms of area. The idea that you can scale this to large numbers is perhaps more feasible.”

There are different business models emerging around the hardware. Intel’s is one approach, where it develops and sells quantum chips the way it does with today’s computer chips. IBM and D-Wave are building full systems. And Microsoft and Google are developing the algorithms.

Quality control
One of the big remaining challenges is to figure out what works, what doesn’t, and why. That sounds obvious enough, but with quantum computing it’s not so simple. Because results typically are distributions rather than exact answers, a 5% margin of error may produce good-enough results in one case, but flawed results in another.

In addition, quantum computing is highly sensitive to environmental changes. These systems need to be kept at a constant temperature near absolute zero, and noise of any kind can cause disruptions. One of the reasons these systems is so large is they provide insulation and isolation, which makes it hard to do comparisons between different machines.

On top of that, quality of qubits varies. “Because you use a qubit once in a certain configuration, will it behave the same in another? That can affect what is true and what is false,” said Leti’s Michellet. “And even if you have exactly the same state, are you running the same algorithms the next time? We need some tools here.”

And finally, the algorithms being used today are so basic that they will undoubtedly change. While this is generally a straightforward process with machine learning and AI to prune and weight those algorithms more accurately, when it comes to quantum computing the algorithms can leverage the superimposed capabilities of the qubits, adding multiple more dimensions. It’s not entirely clear at this point how those algorithms will evolve, but everyone involved in this space agrees there are big changes ahead.

Quantum computing is coming. How quickly isn’t clear, although the first versions of this technology are expected to begin showing up over the next few years, with the rollout across more markets and applications expected by the middle of the next decade.

While quantum computing is unlikely to ever show up in a portable device, it is a disruptive technology that could have broad implications both for the cloud and for edge devices that connect to these computers. For the chip industry in particular, it provides another path forward beyond device scaling where massive performance gains are not based on cramming more transistors onto a piece of silicon. And given the technical challenges chipmakers are facing at 3nm, the timing couldn’t be better.

—Mark LaPedus contributed to this report.

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Mon, 20 Jun 2022 12:00:00 -0500 en-US text/html
Killexams : Enterprise Performance Management Market Growing at a CAGR 7.0% | Key Player Unicom Systems, Planful, Unit4, OneStream, SAP
Enterprise Performance Management Market Growing at a CAGR 7.0% | Key Player Unicom Systems, Planful, Unit4, OneStream, SAP

“Unicom Systems (US), Planful (US), Unit4 (Netherlands), OneStream (US), SAP (Germany), Oracle (US), IBM (US), Infor (US), Anaplan (US),Workday (US), Epicor Software (US), BearingPoint (Netherlands), Broadcom (US), Board International (Switzerland), LucaNet (Germany), Prophix (Canada), Vena Solutions (Canada), Solver (US), Kepion (US), Jedox (Germany).”

Enterprise Performance Management Market by Component, Application (Enterprise Planning & Budgeting, Reporting & Compliance), Business Function, Deployment Type, Organization Size, Vertical and Region – Global Forecast to 2027

The global Enterprise Performance Management Market size is expected to grow at a Compound Annual Growth Rate (CAGR) of 7.0% during the forecast period, to reach USD 8.3 billion by 2027 from USD 6.0 billion in 2022. Enterprise Performance Management (EPM) is a set of processes formulated to help organizations plan, budget, forecast, and report on business performance, as well as consolidate and finalize financial results. EPM vendors across the globe are deploying innovative solutions to support organizations in financial budgeting and planning to Excellerate the financial position of their businesses. The emergence of the latest technologies enables vendors to offer financial budgeting and planning solutions to empower organizations to take appropriate actions. The rising need for mobility to implement a flexible work system is expected to boost the growth of the EPM market.

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EPM software market vendors across the globe are adopting innovative solutions to support organizations in financial planning and budgeting to Excellerate the financial position of their businesses. The evolution of the latest technologies is enabling vendors to offer financial budgeting and planning solutions to empower organizations to take appropriate actions. Organizations require software solutions to handle larger business information. It becomes a challenge for an organization to gather data from different departments available in different data formats. The EPM solutions facilitate information management at different levels and result in informed decision-making. The objective of EPM solutions is to enhance business performance and help enterprises Excellerate their decision-making process. Organizations across verticals use EPM solutions to increase their operational efficiency and productivity.

The market is expected to be driven by business process optimization and rising demand for mobility

The increasing demand for mobility solutions resulted in the growing adoption of cloud-based EPM software. On-premises EPM software lacked application programming interfaces or integrated technologies to connect them to mobile devices. Organizations are moving towards a flexible work environment after the outbreak of the COVID-19 pandemic. Cloud-based EPM solutions are designed to support organizations to grow faster and breakthrough geographic constraints. Additionally, the EPM systems support business processes by enabling organizations to manage and automate daily business activities from a integrated solution, which results in enhanced business performance and increased operational efficiency by ensuring accurate business planning and reporting. EPM systems offer a streamlined business process that eliminates the risk of manual errors and provides faster response time to key decision-makers in the organization. As data serves as a key metric to measure business performance, EPM systems gather and consolidate data automatically, which reduces the implementation time. These factors act as drivers to the enterprise performance management market.

The enterprise performance management market report includes major vendors, such as are Oracle (US), IBM (US), SAP (Germany), Infor (US), OneStream (US), BearingPoint (Netherlands), Workday (US), Anaplan (US), Epicor Software (US), Kepion (US), Unicom Systems (US), Unit4 (Netherlands), Broadcom (US), Planful (US), Board International (Switzerland), LucaNet (Germany), Jedox (Germany), Prophix (Canada), Vena Solutions (Canada), Solver (US), Corporater (Norway), Wolters Kluwer (Netherlands), and insight software (US). The top global players in the EPM market have enacted various growth strategies to expand their global presence and increase their market shares. Key players such as Oracle, SAP, IBM, Infor, and Anaplan have majorly adopted many growth strategies, such as new product launches, agreement and partnerships, collaborations, acquisitions, targeted towards expansion of their market presence and grow further in the enterprise performance management solutions and services market.

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Anaplan is a provider of cloud-based enterprise planning and modeling solutions for enterprises. It is a cloud-based platform that offers real-time scalable modeling and calculation engine for effective planning and better decision-making. The platform has various features, including modeling, collaboration, usability, and security and uptime. The Anaplan platform helps customers dynamically orchestrate performance enterprise-wide and convert constant change to their advantage. The company aims to make it possible to share actionable insights and empower and unleash creativity to drive innovation. The company offers a connected planning platform that supports planning in business functions, including sales, HR, finance, marketing, services, operations, supply chain, and IT. The platform enables an organization to make better-informed decisions.Anaplan also provides large-scale collaborative planning and decision-making across complex processes. The company has a significant presence across North America, Europe, and Asia Pacific and specializes in planning, forecasting, modeling, supply chain planning, sales performance management, performance management, and S&OP.

Infor provides cloud software products in the industry-specific market and is a global leader. It is a provider of enterprise software and services for finance and HR business functions. The company offers many enterprise solutions, including enterprise asset management, enterprise financial management, EPM, and enterprise resource planning. It sells its software and services through channel partners, alliance partners, and delivery partners. Infor builds and deploys industry suites in the cloud for more than 67,000 customers around the globe and has a presence in over 178 countries in North America, Europe, the Middle East & Africa, Asia Pacific, and Latin America.

Infor Dynamic Enterprise Performance Management helps organizations gain a complete, real-time view of their business performance by combining intelligent business tools and financial planning capabilities in an EPM software solution. Dynamic Enterprise Performance Management offers a holistic view of business performance and enables organizations to measure past and current performances and forecast future activities. It also provides modern intelligent business and financial performance management capabilities. Additionally, the company offers its cloud-based products to various industries, including automotive, financial services and insurance, healthcare, retail, oil and gas, and the public sector.

Workday was founded in 2005 and is headquartered in California, US. It is a leading provider of enterprise cloud applications for finance, HR, and planning. Workday delivers financial management, human capital management, and analytics applications designed for the world’s largest companies, educational institutions, and government agencies. Organizations ranging from medium-sized businesses to Fortune 50 enterprises have selected Workday as their business partner. The company specializes in financial management, human capital management (human resources management, workforce planning + talent management), payroll, expenses, time tracking, procurement, grants management, recruiting, and planning. The company offers an enterprise planning platform that supports planning in financial functions, including sales, workforce, operations, and analytics and reporting. The platform enables organizations to make better-informed decisions based on data and technology.

Workday caters to various verticals, such as communications, energy and resources, financial services, government, healthcare, higher education, hospitality, BFSI, life sciences, retail, manufacturing, and media and entertainment. It has an employee base of 15,200 and a global presence.

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Mon, 20 Jun 2022 12:00:00 -0500 GetNews en-US text/html
Killexams : Global Workflow Automation Market Report (2022 to 2027) - Featuring Appian, IBM and Kissflow Among Others

DUBLIN, June 20, 2022 /PRNewswire/ -- The "Global Workflow Automation Market (2022-2027) by Offering, Process, Operation, Deployment, Organization Size, Large Enterprises and SMES, Geography, Competitive Analysis and the Impact of Covid-19 with Ansoff Analysis" report has been added to's offering.

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The Global Workflow Automation Market is estimated to be USD 13.32 Bn in 2022 and is projected to reach USD 34.75 Bn by 2027, growing at a CAGR of 21.14%.

Market dynamics are forces that impact the prices and behaviors of the Global Workflow Automation Market stakeholders. These forces create pricing signals which result from the changes in the supply and demand curves for a given product or service. Forces of Market Dynamics may be related to macro-economic and micro-economic factors. There are dynamic market forces other than price, demand, and supply. Human emotions can also drive decisions, influence the market, and create price signals.

As the market dynamics impact the supply and demand curves, decision-makers aim to determine the best way to use various financial tools to stem various strategies for speeding the growth and reducing the risks.

Company Profiles

The report provides a detailed analysis of the competitors in the market. It covers the financial performance analysis for the publicly listed companies in the market. The report also offers detailed information on the companies' accurate development and competitive scenario. Some of the companies covered in this report are AllyO, Appian, Comindware Tracker, Exact, Gravity Flow, IBM Corp, Integrify, IPsoft Inc, Ipsoft Inc, etc.

Countries Studied

  • America (Argentina, Brazil, Canada, Chile, Colombia, Mexico, Peru, United States, Rest of Americas)

  • Europe (Austria, Belgium, Denmark, Finland, France, Germany, Italy, Netherlands, Norway, Poland, Russia, Spain, Sweden, Switzerland, United Kingdom, Rest of Europe)

  • Middle-East and Africa (Egypt, Israel, Qatar, Saudi Arabia, South Africa, United Arab Emirates, Rest of MEA)

  • Asia-Pacific (Australia, Bangladesh, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Sri Lanka, Thailand, Taiwan, Rest of Asia-Pacific)

Competitive Quadrant

The report includes Competitive Quadrant, a proprietary tool to analyze and evaluate the position of companies based on their Industry Position score and Market Performance score. The tool uses various factors for categorizing the players into four categories. Some of these factors considered for analysis are financial performance over the last 3 years, growth strategies, innovation score, new product launches, investments, growth in market share, etc.

Ansoff Analysis

The report presents a detailed Ansoff matrix analysis for the Global Workflow Automation Market. Ansoff Matrix, also known as Product/Market Expansion Grid, is a strategic tool used to design strategies for the growth of the company. The matrix can be used to evaluate approaches in four strategies viz. Market Development, Market Penetration, Product Development and Diversification. The matrix is also used for risk analysis to understand the risk involved with each approach.

The analyst analyses the Global Workflow Automation Market using the Ansoff Matrix to provide the best approaches a company can take to Excellerate its market position.

Based on the SWOT analysis conducted on the industry and industry players, The analyst has devised suitable strategies for market growth.

Why buy this report?

  • The report offers a comprehensive evaluation of the Global Workflow Automation Market. The report includes in-depth qualitative analysis, verifiable data from authentic sources, and projections about market size. The projections are calculated using proven research methodologies.

  • The report has been compiled through extensive primary and secondary research. The primary research is done through interviews, surveys, and observation of renowned personnel in the industry.

  • The report includes an in-depth market analysis using Porter's 5 forces model and the Ansoff Matrix. In addition, the impact of Covid-19 on the market is also featured in the report.

  • The report also includes the regulatory scenario in the industry, which will help you make a well-informed decision. The report discusses major regulatory bodies and major rules and regulations imposed on this sector across various geographies.

  • The report also contains the competitive analysis using Positioning Quadrants, the analyst's Proprietary competitive positioning tool.

Key courses Covered:

1 Report Description

2 Research Methodology

3 Executive Summary

4 Market Dynamics
4.1 Drivers
4.1.1 Ease in Business Processes with the Installation of Workflow Automation Tools
4.1.2 Convergence of Workflow Automation with Traditional Business Processes
4.1.3 Focus on Streamlining Business Processes
4.1.4 Cost Efficiency Through Workflow Automation
4.2 Restraints
4.2.1 Data Insecurity Hindering the Implementation of Workflow Automation in the Financial Sector
4.3 Opportunities
4.3.1 Integration of New Technologies with Workflow Automation
4.3.2 High Demand for Workflow Automation in the Logistics Industry
4.3.3 Increased Focus on Digital Transformation Initiatives
4.4 Challenges
4.4.1 Lack of Awareness Regarding Workflow Automation
4.4.2 High Implementation Cost and Difficulty in Integrating New and Existing Systems Through Workflows

5 Market Analysis
5.1 Regulatory Scenario
5.2 Porter's Five Forces Analysis
5.3 Impact of COVID-19
5.4 Ansoff Matrix Analysis

6 Global Workflow Automation Market, By Offering
6.1 Introduction
6.2 Software
6.2.1 Model-Based Application
6.2.2 Process-Based Application
6.3 Services
6.3.1 Consulting
6.3.2 Integration and Development
6.3.3 Training

7 Global Workflow Automation Market, By Process
7.1 Introduction
7.2 Automated Solution
7.3 Decision Support & Management Solution
7.4 Interaction Solution

8 Global Workflow Automation Market, By Operation
8.1 Introduction
8.2 Rule Based
8.3 Knowledge Based
8.4 Robotic Process Automation Based

9 Global Workflow Automation Market, By Deployment
9.1 Introduction
9.2 Cloud
9.3 On-Premise

10 Global Workflow Automation Market, By Organization Size
10.1 Introduction
10.2 Large Enterprises
10.3 SMES

11 Global Workflow Automation Market, By Large Enterprises and SMES
11.1 BFSI
11.2 Telecom & IT Industry
11.3 Travel, Hospitality, & Transportation Industry
11.4 Retail & Consumer Goods
11.5 Manufacturing & Logistics Industry
11.6 Healthcare & Pharmaceuticals
11.7 Energy & Utilities
11.8 Other Industries

12 Americas' Global Workflow Automation Market
12.1 Introduction
12.2 Argentina
12.3 Brazil
12.4 Canada
12.5 Chile
12.6 Colombia
12.7 Mexico
12.8 Peru
12.9 United States
12.10 Rest of Americas

13 Europe's Global Workflow Automation Market
13.1 Introduction
13.2 Austria
13.3 Belgium
13.4 Denmark
13.5 Finland
13.6 France
13.7 Germany
13.8 Italy
13.9 Netherlands
13.10 Norway
13.11 Poland
13.12 Russia
13.13 Spain
13.14 Sweden
13.15 Switzerland
13.16 United Kingdom
13.17 Rest of Europe

14 Middle East and Africa's Global Workflow Automation Market
14.1 Introduction
14.2 Egypt
14.3 Israel
14.4 Qatar
14.5 Saudi Arabia
14.6 South Africa
14.7 United Arab Emirates
14.8 Rest of MEA

15 APAC's Global Workflow Automation Market
15.1 Introduction
15.2 Australia
15.3 Bangladesh
15.4 China
15.5 India
15.6 Indonesia
15.7 Japan
15.8 Malaysia
15.9 Philippines
15.10 Singapore
15.11 South Korea
15.12 Sri Lanka
15.13 Thailand
15.14 Taiwan
15.15 Rest of Asia-Pacific

16 Competitive Landscape
16.1 Competitive Quadrant
16.2 Market Share Analysis
16.3 Strategic Initiatives
16.3.1 M&A and Investments
16.3.2 Partnerships and Collaborations
16.3.3 Product Developments and Improvements

17 Company Profiles

18 Appendix

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Killexams : IoT in Manufacturing Market to Register Highest CAGR of 14.5% through 2022-2032

According to a accurate analysis issued by FMI, the IoT in manufacturing market share is likely to reach US$ 399.08 billion by 2026, up from US$ 175.3 billion in 2020, accounting for 14.5% CAGR through 2022-2032.

The ecosystem’s diversity of significant stakeholders has resulted in a competitive and diversified adoption of IoT in manufacturing market. The Internet of Things enables industrial units to automate their operations, which results in cost savings, faster time to market, mass customisation, and increased safety.

The IoT devices and next-generation manufacturing industry has experienced a tremendous increase in industrial automation in accurate years. As a result, IoT gateway manufacturers are more concerned with generating high volume and quality products due to increased market rivalry and end-user demand.

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As a result, they’ve decided to concentrate on the factory’s essential areas, such as the IoT sensors for manufacturing, asset monitoring, and asset maintenance and support. As a result, manufacturers would be able to minimize direct human labor costs and expenses, boost productivity, Excellerate a process or product consistency, and produce high-quality goods by using automation.

Control systems, such as computers or robots, are used in industrial automation processes to monitor and control machinery. In the manufacturing IoT sensors industry, a critical role is played by improving the process of industrial automation.

The global economy has been influenced by COVID-19. Energy, oil and gas, transportation and logistics, manufacturing, and aviation are among the financial and industrial sectors with a large economic influence. As a result, the world economy is expected to enter a recession due to the loss of billions of dollars.

“Economic activity is diminishing as a result of an increasing number of nations implementing and prolonging lockdowns, which will have an impact on the global economy. To boost flexibility and offer better production, IoT helps produce cooperative communications and interaction from IoT solutions for manufacturing industry field input or output including actuators, robots, and analyzers.” – opines an FMI analyst.

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Key Takeaways:

  • The increased demand for automated machinery and IoT devices for manufacturing will accelerate IoT adoption. In addition, demand for customization, simpler and easy-to-use machinery, and reliable data will drive the IoT in the future.
  • North America now has the largest market share with the growing number of start-ups and the widespread implementation of machine learning algorithms in both software and hardware equipment, which will contribute to the regional market’s growth.
  • The services category is a critical component of the IoT in manufacturing market, as it focuses on optimizing company processes and lowering needless expenditures and overheads for manufacturing firms.
  • Apart from North America, the Asia Pacific market will expand significantly in the future years. The increasing acceptance of sophisticated and automated concepts, as well as the following demand for them, would add to the market in the Asia Pacific.
  • Several factors have contributed to the market’s accurate expansion, such as industrial market competition has been extensively studied. The research also indicates the current strong demand and application areas for the product.

Competitive Landscape

Cisco (US), IBM (US), PTC (US), Microsoft (US), Siemens AG (Germany), GE (US), SAP (Germany), Huawei (China), ATOS (France), HCL (India), Intel (US), Oracle (US), Schneider Electric (France), Zebra Technologies (US), Software AG (Germany), Wind River (US), Samsara (US), Telit (UK), ScienceSoft (US), Impinj (US), Bosch.IO (Germany), Litmus Automation (US (US). To extend their portfolios and market shares in the worldwide IoT in manufacturing market, these companies have used various organic and inorganic growth tactics, such as new product releases, partnerships and collaborations, and acquisitions.

  • Cisco and Telstra inked a new deal in September 2021 to collaborate and continue their bridging regions with the strong IoT network to assist various industries, including retail, financial services, and government.
  • IBM and Boston Dynamics teamed in October 2021 to deliver mobile edge analytics to industrial operations. IBM will leverage this cooperation to offer data analysis at the edge, assisting industrial firms to enhance worker safety, optimize field operations, and increase maintenance productivity in places like manufacturing plants, power plants, and warehouses.

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Key Market Segments

By Component:

By Solution:

  • Network management
  • Data management
  • Device management
  • Application management
  • Smart surveillance

By Services:

  • Managed services
  • Professional services

By Organisation Size:

  • Small and Medium Enterprises
  • Large Enterprises

By Deployment Mode:

By Application:

  • Predictive maintenance
  • Business process optimization
  • Asset tracking and management
  • Logistics and supply chain management
  • Real-time workforce tracking and management
  • Automation control and management
  • Emergency and incident management and business communication

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About Future Market Insights (FMI)

Future Market Insights (ESOMAR certified market research organization and a member of Greater New York Chamber of Commerce) provides in-depth insights into governing factors elevating the demand in the market. It discloses opportunities that will favor the market growth in various segments on the basis of Source, Application, Sales Channel and End Use over the next 10-years.


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The post IoT in Manufacturing Market to Register Highest CAGR of 14.5% through 2022-2032 appeared first on Future Market Insights.

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