A Workflow-Driven Approach to Manufacturing Operations Management (MOM)

introduce

"The first rule of any technology used in a business is that automation applied to efficient operations will magnify efficiency. The second is that automation applied to inefficient operations will magnify inefficiency." - Bill Gates.

Workflows are structured activities primarily involving human-to-human or human-to-machine interactions, all designed to enable profitable operations without compromising safety, reliability, and consistency. Workflow technology is beginning to move from a purely IT domain practice to the Manufacturing Operations Management (MOM) domain as defined by ISA-95.

This article explores the challenges of global organizations associated with introducing workflow technology into MOM by providing examples of workflow technology in MOM. This is done using a global perspective and focusing on the continuous process industry.

The need to converge business and operational strategies is transforming MOM from a primary data collection and transformation function to a value enabler in a knowledge-driven economy. A very visible step in this shift is the dashboard, which is getting a lot of publicity in the trade press and among MOM system vendors. Beyond dashboards, companies have begun to realize the importance of building and reusing business processes in the MOM domain, often integrating with enterprise-level business processes and manufacturing systems and procedures. When this step occurs, the definition of business intelligence may expand to include manufacturing business processes.

While technological advances have increased the reliability of assets and equipment, they have failed to improve expectations for "human reliability," which is a major cause of accidents and lost production. Coupled with margin pressures forcing continuous processing industries to pursue lean manufacturing strategies, an aging workforce and fluid job market are challenging business continuity. Leading process industry companies are investigating business process and workflow automation in MOM.

Technologies such as Web services and service-oriented architecture (SOA) enable disparate systems to communicate and collaborate; however, it is the owners and users of the systems who determine the success of this integration. The process of building knowledge into reusable business intelligence units requires careful work, end-user buy-in, and top management buy-in. The maturity of the enterprise and manufacturing site can be an important factor in the amount of change management necessary for a successful workflow project.

An often overlooked factor in workflow projects for global manufacturing companies is globalization. The recognized pressures of globalization on business are reduced profit margins, trade opportunities, geographical mobility of manufacturing, and access to larger markets. Less well understood is how globalization has opened the way for knowledge and best practice across cultures and countries.

Flexible business processes, based on proven knowledge and integrating business and operational objectives, can improve the safety, consistency, reliability and profitability of manufacturing operations. The initial goals of a workflow project typically include initiation, transition management, and closure processes.

Although this article focuses on the continuous process industry, the concepts also apply to other process industries such as chemicals, power generation, and steel manufacturing.

The challenge of working together

Market and Industry Dynamics

Globalization has brought about broader markets, more fragmented supply chains, and a wider product range. Rapidly changing consumer preferences drive companies to respond to shorter product cycles, pricing pressure, and quality demands, while striving to avoid commoditization of their products. Companies across the supply chain are looking for higher margins and more unique products. These pressures have moved up the supply chain from the consumer goods market.

Suppliers of materials, i.e. process industries. The process industry is still reeling from the 2008 crude oil shock and the ensuing volatility in oil prices. Issues related to oil price volatility are compounded by lower demand and product prices, both driven by the current economic slowdown. Many manufacturers responded by repositioning themselves as dealers and operating below their rated capacity. To quickly switch between a market economy and a limited-capacity economy, companies are moving from make-to-stock (MTS) to make-to-order (MTO) production strategies.

Both Adam Smith's theory of "absolute advantage" and David Ricardo's theory of "comparative advantage" advocate the use of regional advantages in labor to achieve competitive advantage. These theories also apply to today's global manufacturing economy. They made it clear that globalization was about acquiring resources, not owning them, and pushing production beyond regional boundaries to where conditions were most favorable.

However, the profitable operation of multinational companies depends on many other factors, including health, safety and environment (HSE) standards, prevailing protectionism and pricing policies, as well as consumer behavior and domestic market size. Agility and the ability to keep pace with market dynamics is quickly becoming a requirement. Less nimble companies face larger, more serious existential challenges.

Regional dynamics

Mature economies in the US, Japan, and Europe are consolidating their capacity to improve efficiency by updating older factory assets and providing real-time visibility across the supply chain. An aging workforce is drying up knowledge and expertise in developed countries, forcing them to consider augmenting their lean manufacturing strategies with more sophisticated automation.

The BRICS (Brazil, Russia, India, and China) economies are emerging as global economic powerhouses and building new production facilities, including oil refining and steelmaking. In the process industry, capacity in the Middle East continues to grow significantly, now moving down the supply chain into chemicals.

Due to recent industrialization and lack of indigenous expertise to manage world-class facilities, developing countries are not prepared to take advantage of their high-tech, newer infrastructure. As such, they continue to rely on mature economies for technology transfer and expertise. This dependency limits many factories in developing countries to local practices that have been carefully crafted for their infrastructure of the past, rather than world-class best practices. The lean manufacturing paradigm is not a priority for developing countries due to rising populations and growing domestic production capacity. These differences in skills and knowledge have hindered many initiatives aimed at harmonizing the business processes of a global company focused on gaining economies of scale.

These dynamics are expanding the need for knowledge acquisition and, with it, the need for knowledge distribution among the factories of global enterprises.

Technology dynamics

Tremendous advances in technology have enabled manufacturers to transition from the electrical age to fieldbus and wireless technology in a matter of decades. Advances in digital technology are powering real-time centralized and remote control of production facilities. The scarcity of data is giving way to a new problem of data deluge. Data mining and warehousing enable terabytes of data to be distilled into useful information.

Dashboards are emerging to provide visibility at every level of information and decision support. Enterprise resource planning products haven't kept pace, so a MOM system is needed to facilitate business-centric operations. Even with a history of slow adoption of advanced technologies and a continued focus on tried-and-tested practices, the process industries appear to be making a major effort to bring IT advances to manufacturing.

Organizational Dynamics and Intra-firm Factors

Collaboration between different groups within an enterprise is also an essential requirement for maintaining profitable operations. Due to differences in management priorities, scope of work, information needs, and information systems, teams rarely collaborate effectively. Although these information systems are central to their functional goals, they are different at the plant level.

Integrating these data islands digitally is neither simple nor sufficient. There is also a need to integrate people, their ways of thinking and their actions. For example, as part of their functional responsibilities, maintenance groups often schedule the maintenance of critical equipment according to their own priorities, unaware or only partially aware of production schedules until the last moment. On the other hand, due to sales or other requirements, the production plan is changed in a short period of time, which affects the access of the maintenance group to the equipment. This disconnect significantly widens the gap between planning and actual execution, creating another barrier to business agility.

In addition to external triggers such as globalization and lean manufacturing, there are also internal enterprise factors that have a mixed influence on the outcome of coordinating work practices across enterprise factories.

Based on the research, the following is a list of significant impacts (from a business perspective) and possible deterrent human factors:

Human resource flexibility: Business expansion, contraction, mergers and acquisitions are often accompanied by the transfer of personnel between facilities. This presents knowledge management challenges for the transfer of systems and local work procedures.
Lack of alignment and common purpose: As mentioned earlier, despite integration and change management, most factories still face a disconnect between different functional people and systems due to differences in work priorities and activities. For example, maintenance uses computerized maintenance management systems (CMMS) and enterprise asset management systems (EAMS), while operations use work order systems, permit management systems, and shift notebooks. Each group's system provides a different view of the data, and sometimes each group maintains its own version of the same data. These systems often remain data silos.
Specialization: Some critical jobs, such as boiler startup and compressor shutdown, require specialized skills and expertise. Factories must often schedule such activities around the availability of experts, at the expense of operational flexibility.
Centralized Production Planning and Scheduling: Economic decisions, such as raw material procurement or pricing decisions, are often made in business offices away from the factory floor and without awareness of day-to-day operational issues. Actions taken by these remote offices can disrupt planned operational activities, causing coordination issues within the plant. Due to the lack of context, the decision support provided by the dashboard may not be enough to prevent such problems from happening.
Greater focus on end-to-end traceability: Adherence to strict quality and HSE practices requires end-to-end traceability throughout the supply chain, from raw material receipt to product shipment. There are different systems and people in the company's internal supply chain, and data synchronization is required between them.
Accessibility of standard operating procedures (SOPs): SOPs are often maintained more for process consistency than for guidance. In less mature operating environments, they may not be up to date or available to operators when needed, reducing operator reliability and increasing HSE risk.

human problem

People have a significant impact on the overall outcome of initiatives to collect, digitize, standardize and distribute knowledge. Change management is critical to successfully introducing workflow automation into the workforce, especially in manufacturing environments that are not accustomed to thinking in terms of business processes.

The undercurrent of resistance can be caused by (among other things):

Knowledge is power: the sharing of knowledge or expertise is visualized as a dilution of individual power or identity, thereby encouraging experts to hoard knowledge and fail to share best practice.
Convenient practice instead of best practice: Developing suboptimal but convenient practices over time can lead to inertia that workflow automation projects must overcome.
Undocumented procedures: People employ informal work procedures without leaving sufficient traces or documenting their default information and best practices.
Insecure: Dashboards can be viewed as management spies. Amplify human inefficiencies under the pretext of providing operational visibility to upper management. This view creates feelings of insecurity or constant management surveillance, so employees resist efforts to increase transparency.
Not-Invented-Here (NIH) Syndrome: May resist change when introducing successful best practices from other plants, often saying “it won’t work here because…”
Blame and learn from mistakes: Some simple tasks are underperformed due to complacency or forgetfulness. Operators may find it difficult to remember infrequently performed procedures, such as startup and shutdown. Systems can track these errors and report them to management for analysis, but this is seen as an effort to blame the actors rather than a way to learn from mistakes.

overcoming challenges

The challenges discussed above are the result of pressures that companies face from the market, globalization, technology and within the organization. Nonetheless, once recognized, challenges can be managed and overcome.

One way to overcome these challenges is to employ a MOM system. One driver of this trend in MOM system adoption is maturity. Due to a lack of manufacturing integration, many manufacturing companies' enterprise resource planning (ERP) systems are not delivering the full benefits initially expected.

Capturing, refining and reusing the knowledge of the enterprise to coordinate actions in the value chain will bring greater benefits to the enterprise. The basic requirements of this approach to knowledge sharing, known as the 4Cs, are key to business process and workflow automation.

Coordination (Shared Program)
communicate (share information)
Collaboration (sharing information and tasks)
Collaborate (share tasks, information and goals)

Business processes and automated workflows are the link between the desire to be an agile enterprise and the ability to reuse accumulated knowledge in real time. To move to the next step, companies must be able to distribute knowledge as standardized, consistent and configurable units of operational intelligence. This is critical in moving from the process-centric operations of the past to the business-centric operations of the future.

"It's not what you know that matters, but how you use what you know."

Workflow automation can help operations staff make the most of their knowledge.

Changes in the role of the MOM system

Dashboards can now report on production goals and plant safety performance, such as fatal accidents, near misses, and the number of days of incident-free operation since the last incident. Technology today allows dashboards to present this data to diverse audiences in near real time.

However, dashboard implementations face challenges in determining a "single version of the truth." Determining a "single version of the truth" can be difficult when results and status are reported in near real time until data is harmonized at the MOM and business level. Examples of these challenges faced by dashboard implementations include:

Multiple views of data: This occurs when performance metrics are available from two or more systems, with different time delays or different perspectives of the metrics at the same point in time. For example, a maintenance backlog, when obtained from a maintenance system, may not match data from an operations-related system, because each system uses different business rules and reflects different points in the same business process. Operations personnel may each feel that their data is correct and correct from everyone's point of view, but the dashboard design must choose a "single version of the truth" or provide context for the entire business process so that both Either (or all) numbers are understandable.
Real-time data may be adjusted later: Readings and key performance indicators (KPIs) calculated in real time are error-prone and are often reconciled and adjusted manually later. For example, a petrochemical plant's dashboard reports in real time the production of Grade A linear low-density polyethylene (LLDPE) -- based on its melt flow index (MFI) of 8-3.1. Based on real-time MFI calculations, the number of A-grades is reported once the "grade-change" transition is complete. This event updates inventory etc. in real time. However, following a quality control check, the MEI is determined to be outside the specified range and the resulting material will be reclassified as Grade B. In such cases, the level of reclassification must be coordinated across the plant's business and operating systems. The challenge for the dashboard is how to provide context for this reclassification from A to B. Solutions to this challenge include delaying reporting until production is complete or providing dashboard insights for the entire business process including production, QC and inventory adjustments.
Variation in source data: Dashboards rely on a large number of data measurements, often from various systems. A common problem is that low-level engineering or production-oriented changes in one system can change the data in a dashboard, providing inaccurate data or missing data feeds.

Implementing workflow automation in layer 3 (and sometimes layer 2) can increase the value of dashboards by providing more reliable and consistent information. Workflow automation can also improve operational performance by formalizing and preserving knowledge as repeatable best practices before knowledge is lost through an aging or mobile workforce.

Beyond the Dashboard

Business systems have traditionally focused on profitable operations and the ability to flexibly meet market demands, entrusting compliance with HSE requirements to control systems. Likewise, control systems are more focused on protecting worker life and safety and environmental compliance than on the profitability and agility of the business.

In the current business world, the functional divide between business and operations is shrinking as their goals become more intertwined.

Rising energy costs and variability in raw material availability, quality and price make continuous improvement of production processes imperative. These pressures have also prompted enterprises to aggregate process data into higher-resolution production and business data, thereby adding a dimension of control to business drivers. MOM is changing roles in event-driven real-time workflows as it assumes greater importance as an enabler of seamless integration of business and operational functions.

The functions of ISA-95 layers 2, 3, and 4 must be coordinated to provide full value. A workflow automation system should be used to coordinate the flow of information between the various systems and their users.

Coordination powered by automated workflows can include horizontal and vertical integration of various plant functions and their actors through prompted and fully automated workflows.

Business processes and their automated workflows can be used to better integrate production processes and enterprise business processes.

Manufacturing Workflow

A workflow is one of several implementations of a business process. They are structured activities that primarily direct human-to-human or human-to-machine interactions, often across the various functions of an enterprise. The ability to coordinate activities between different systems and different human roles is one of the benefits of using a workflow system in MOM.

As the use of workflow automation in the MOM space continues to grow, so does the availability of workflow-related tools designed specifically for manufacturing. A new generation of manufacturing-oriented workflow automation products draws on widely adopted IT standards such as Web Services, Service-Oriented Architecture, and Business Process Modeling Notation (BPMN). The use of these IT standards is important to enable business processes across the ISA-95 hierarchy to use the appropriate tools in each domain.

A manufacturing workflow automation system requires the following capabilities:

Capture real-time information
Provides context-sensitive guidance and role-based views
Enables all users in a role to consistently perform highly skilled tasks, independent of their individual skill levels
Break down plans into timelines and turn plans into work instructions
Schedule workflows on a regular basis or use them infrequently or exceptionally
Promote safe and reliable operation through clear instructions
Continuously track program performance
Provides end-to-end traceability for production and user interactions
Perform KPI calculations and generate reports to facilitate workflow improvements
Display results with contextual information on a dashboard
Flexible and real-time reconfigurable
Follow industry standards and use off-the-shelf or commercial technology
Interface with existing automation and information systems using common industrial protocols and methodologies such as OPC and event-based triggers
Integration with control system operator station
Synchronize activities and information across various information systems to ensure information integrity
Provides vertical integration down to the work order and tracking level
Provide cross-functional horizontal integration by coordinating processes and workflows

A workflow automation system does not execute an entire business process by itself. Instead, their role is to coordinate and direct the services provided by the various systems. Sometimes, existing systems cannot help operators perform specific tasks or procedures. Thus, a workflow system also includes a work order component or system.

Work order components or systems typically:

Break down high-level goals into function-specific tasks and provide detailed guidance for performing those tasks
Reflects digitized operational intelligence and knowledge gained over the years, including anticipated responses to events, such as crude oil volatility
Provides contextual and role-specific information to personnel in real-time, in addition to information about best practices and standard operating procedures (SOPs)
From the perspective of human workflow and related workflow interaction, is it based on engineered business processes
Provides vertical integration, coordinating activities across the production floor and horizontal integration within Level 2 as required

Design knowledge base

The creation and maintenance of automated workflows is similar to designing a knowledge base (also known as operational intelligence). The process of designing a knowledge base requires both top-down and bottom-up activities. Top-down activities define the business process, including the definition of the manufacturing domain and the lower-level manufacturing workflows required to implement the associated business process activities. The bottom-up activity identifies existing automation and information systems that provide the services needed to implement the workflow, and then fills in the gaps with new automation and/or work instructions as part of the workflow system. Top-down and bottom-up activities overlap in manufacturing workflows, often requiring multiple iterations or negotiations to align.

Simply reflecting current processes and workflows is not always the desired outcome of business process realization. Doing so may result in the further institutionalization of a sub-optimal or undesirable process or workflow. Recommend an analytical process that includes researching and mining existing systems, standard operating procedures, work orders, permits, shift reports and production reports to identify best practices for the plant and identify opportunities to improve them based on industry best practices .

The collaborative plan, do, check, act (PDCA) approach to problem solving is useful for iteratively improving workflow implementation and incorporating key user feedback. It is often worth the time and effort spent with plant personnel to gain default information and reasoning for their current and desired workflows.

A top-down approach to engineering business processes in layer 3 can use layer 2 services and include layer 3 tasks. These business processes may span multiple categories of operations, such as production, maintenance, inventory, and quality, or be entirely within a single category.

In Tiers 3 and 4, the use of SOA-based Web services can provide an acceptable integration tool between business process engines, work order systems, and other MOM systems. However, there are many legacy systems in Layer 2 and Layer 3 that do not support Web services, so many systems need to be integrated into workflows using common industrial protocols such as OPC.

The PDCA cycle works from the bottom up and should be executed individually and independently for each Tier 2 task to enable the integration of actions and information within each Tier 2 organization. This approach can be extended to multiple Layer 2 organizations and systems to establish common goals and connect individual tasks or workflows into higher-level tasks. Higher level tasks can be presented to layer 3 activities as services that layer 2 can perform. By working from Tier 2, it becomes easier to incorporate HSE considerations, legacy system realities and constraints into workflow tasks and activities.

plan

The first step is to decide which business processes to implement as automated manufacturing workflows and identify the Layer 3 operations that support them. The goals, the methods followed to achieve them, and the results required for each Layer 3 operation are categorized as tasks or units of work.

Tasks or units of work are organized into templates. Each template contains the information needed to achieve the goal, including instructions, references to SOPs, reporting formats, and role and device information. A template is the master definition of a workflow. When a workflow template is run, it is considered a unique instance of the workflow, with unique execution data associated with it.

Once the Layer 3 part of the workflow is defined, the Layer 2 services it requires are identified and linked to the workflow. Doing so may require another engineering iteration to ensure the correct Layer 2 services are delivered.

In other cases, the workflow may extend to layers 2, 3, 4. For example, integrating planning, logistics, QA, operations and maintenance into one workflow may require actions in layers 2, 3, 4 within the same or different operations.

Planning is complete when the workflow template is complete, tested, and published to operations.

implement

When a business process is executed, a workflow template is converted into an instance and run or executed. Each run of a workflow creates execution activities and tasks and collects unique data, while also building an audit trail. In addition to the data required to directly complete business process activities in Layers 2 and 3, relevant data such as alerts, events, user notes, and screenshots can be collected to help provide context for actions at a later date.

examine

As part of a process improvement program, plant management, engineers, or consultants should regularly mine and review records of business process and workflow performance data. The goal is to improve best practices or adopt new best practices. Workflow systems can be programmed to provide usage statistics, such as the number of templates or knowledge added, used, or modified in a previous period. Other useful statistics might be the average, best, and worst cycle times required to complete each of these tasks, as well as metrics such as adherence to schedules, plans and processes, and how often specific tasks are performed.

action

The results of the inspection process can identify top performers and consistent work practices. This data can be used to update templates to improve overall performance and can be shared with other plants. The results can also identify new workflow templates, tasks, or jobs that illustrate where operations will be improved.

Based on the analysis of the results of the inspection process, the scheduling of periodic tasks can be decided.

In all PDCA cycles, it's important to remember that preserving collective knowledge, iterating industry and company-wide best practices, and reusing business intelligence across sites are key goals. Doing these things contributes to the safe, consistent, reliable, and profitable operations of all parts of the company.

Selection of Automation Level in Workflow Design

The role of automation in continuous processes is becoming increasingly important as industry adopts lean manufacturing techniques and strives for more consistent and safer operations.

While technology has been used to improve the reliability of assets and equipment, it has not been widely used to improve human reliability, the leading cause of accidents and lost production.

Automating procedures and workflows is one way to apply technology to improve safety in processing plants.

Choosing the right level of automation depends on many factors. Time-critical or hazardous processes, such as nuclear fusion reactions, are usually controlled with a high degree of program automation in highly reliable control systems. This level of automation can provide safe, repeatable and efficient operations, but it is not always economically viable for all processes, and it does not readily support continuous improvement as other options.

The other is a manual procedure. Using manual procedures requires additional operators, makes compliance more difficult, and often leads to uncertain operations. These issues have played out in famous disasters over the years.

An alternative to fully automated and manual procedures is to use automation to guide operators through complex procedures designed from a task perspective. Such programs prompt the operator with contextual guidance and require human judgment at key points. Using prompt programs allows for automated compliance checks and more consistent program execution. Prompt procedures can combine the advantages of automatic and manual procedures.

Optimal levels of automation can be achieved with the right mix of manual, prompted and fully automated procedures and processes. Workflows should be designed to integrate with automation at all tiers, treating each tier as an available service. Initiating workflow implementation using the existing level of automation in the plant facilitates change management. It can also be a useful method for building consensus on further automation, especially within Layer 2, where it would be beneficial.

The use of business processes can be expanded. A business process may communicate with many other business processes, resulting in a set of enterprise-level or supply-chain-level business processes to meet the needs of today's ever-evolving enterprises.

Adding manufacturing operations and Layer 2 controls to business processes can help companies achieve company-wide optimization, regardless of location and people. These knowledge-driven systems lower the barriers to establishing new production facilities in regions where resources are available but talent is scarce.

Benefits of Workflow Solutions

Safe and secure operation: The solution leverages technology to provide users with contextual knowledge and procedure-based guidance. This improves personnel reliability and consistency of operation. It integrates human-computer interaction and system interaction, thus balancing the advantages of fully manual and fully automatic operation.
Synchronized business and operational goals: It reduces cross-functional coordination issues, aligning individual functional goals with the core goals of safe and profitable operations. Digitization of operations produces operational logs and audit trails, improving end-to-end traceability. Essentially, synchronized goals establish common goals and improve communication and collaboration.
Operational Intelligence and Business Continuity: Workflow solutions capture implicit information from expert users in the form of audit log entries or comments. This information can be mined for operational intelligence to share best practices and insulate businesses from business continuity issues, attrition, retirements, and more.
Scalable and Repeatable Operations: Operational intelligence and insights gained from workflow solutions can be scaled or distributed to multinational locations or factories within the enterprise. This helps to increase the consistency and repeatability of operations regardless of personnel skill level or location. This operational intelligence facilitates the production of products with the same quality and the same level of security in different locations independent of user and national context.
Improved Response and Agility: The near real-time communication of critical events to functions including planning and scheduling, operations and maintenance improves the quality and timing of responses. Such improvements make the business more agile.

A key enabler of each of the above benefits is the workflow's ability to seamlessly integrate the activities and tasks of different manufacturing roles using a common set of graphical user interfaces (GUIs).

in conclusion

Workflows are structured activities that primarily involve human-human or human-machine interaction. When aimed at the profitable operation of a process plant, they increase reliability, consistency and safety.

However, the countless combinations of humans and machines lead to interactions that may not always be optimal. While service-oriented architecture and Web services allow disparate systems to communicate and collaborate together, getting the owners of such systems to also collaborate requires significant effort. The process of capturing knowledge, distilling it and digitizing it into reusable units of business intelligence does not happen overnight. The organizational culture and social structure must support collaboration, and the value system must assimilate best practices.

The best way to roll out a workflow-driven process is to fine-tune it so users experience the benefits and assimilate them over time. When changes are radically different from what happened before, or have to happen within a short period of time, those affected need to be engaged and educated early on. Pioneers are expected to take ownership and become advocates and apostles of workflow-driven processes, creating an agile work environment.

The purpose of this article is not to assert that a workflow system can solve all coordination problems on the factory floor, but the point is that a well-designed workflow system will definitely make coordination easier. Resistance to adoption is likely to decrease over time if systems are designed from the perspective of routine workflows based on real factory floor experience and knowledge, rather than just technology. A workflow-centric approach to the MOM system helps align goals on dashboards with goals across the organization, as the functional goals of different people can all be correlated as workflows to support larger business goals for profitability and continuity. Actual performance is synchronized.

In addition to enabling this integration, well-designed business processes can improve safety and reliability in various phases of plant operations, such as start-up, transition management, and shutdown. Thus, a workflow-driven MOM system built on SOA empowers agility by extending business and IT infrastructure to the cloud beyond traditional enterprise boundaries, continuously adding business value and transforming companies into secure and profitable digital enterprises sex.