A Clear Understanding of Outcome-Based Contracts?

It’s easy to hear a buzz word in the industry and make assumptions. However, what happens when those assumptions prove incorrect? And what happens when those assumptions are the bedrock under which a sourcing contract is being shaped, priced and a customer/service provider relationship is developed?

I’ve heard it many times; “I don’t care how you do it – but we need the job done.” This can be a dangerous mindset if seeking to embark on an outcome-based project. If the customer is stating this, they have missed the point of an outcome-based agreement and should re-think their approach. If a service provider is on the other side of the table hearing that statement, they should challenge the customer’s approach and determine whether the customer has fully comprehended the level of work and commitment associated with the outcome-based approach.

Outcome-based contracting is not a tool by which customers can shift responsibility to their service providers and seek to avoid the effort and time associated with good governance and performance delivery. It is an operational model that requires a strong customer and service provider relationship, trust and a genuine sharing of risk and reward. If a customer misunderstands what outcome-based contracting is (and perhaps confuses it with output-based contracting as this statement suggests), the customer’s expectations are already misaligned with the service provider’s and what each party should be committing to.

Outcome-based models are by no means new to the sourcing world but now with a greater understanding and implementation of Artificial Intelligence (AI) at the customer side, they have grown again in popularity as we see a resurgence in customers demanding greater innovation and more cost-effective service, particularly in process-driven services such as finance and accounting.

But with potential for misunderstanding and customers confusing output for outcome, will we start to see an increase in issues arising from outcome-based contracts?

A true outcome-based model requires a considerable amount of strategic planning from the customer before engaging with service providers. A customer needs to be capable of introspective analysis to understand, develop and communicate its business values and strategic agenda. However, this flow of information will need to go both ways as the parties will need to determine whether they share the same business values and approach on which to base the relationship. While trust will be of utmost importance, this flow of communication should be subject to early contractual commitments of confidentiality. Both parties may want to share, at a high level, their business strategies and potentially confidential information about business projections and future aspirations. This should be done in a controlled and respectful manner, sharing only the information that will benefit the relationship, with the requisite protections in place.

Ultimately both parties need “buy in” from senior stakeholders and will need commitment from every level of the organisation before a strong working relationship can be established. All levels of the customer organisation have to want to work with a service provider as a strategic partner and see the benefit in the service provider helping them achieve their organisational goals. This is more than just the parties outlining and agreeing to certain contract outcomes. A strong and well developed business case should be circulated to ensure that internal alignment. In turn, the service provider has to want to align its business with the customer and trust that the customer will commit to a true risk and reward model.

Each party will need to invest in the process at an early stage. The customer will need to have the right resources available for its internal analysis and baseline of existing services. Both parties will need their project teams to invest time and effort in deal structuring and seeking to exclude external factors that may impact the measurable outcomes that the service provider is remunerated upon. Early investment of this type (on both sides) will be key to demonstrating commitment to the process and a successful, working contract. The time spent in the early stages of development of core principles, agreed measures and conducting due diligence means that there is a significant level of work done before the parties reach contractual negotiation. If customers are not capable or cannot spare the resource to take on these tasks, they would do well to consider using a consultant who understands the complexities of an outcome-based approach and who can assist with baselining the relevant existing services and create a true risk and reward program.

Although not yet at contracting phase, the work effort involved in this early stage of development should be documented and agreed to by the parties. In addition, the baselines from which the outcomes can be measured, the outcomes themselves and any risk factors that may adversely impact the service provider’s efforts should also be agreed on and clearly documented. Outcome measurements will involve negotiation and discussion between the parties. Each measurement should be capable of being objectively monitored rather than an internal metric understood by only one of the parties.

Strong governance is key in most (if not all) sourcing relationships, but it is even more important when working on an outcome-based model. Governance structures should be developed early in the relationship and be robust with the ability to flex over time in line with the relationship needs and both customer’s and service provider’s businesses. It is of paramount importance that the parties – at all levels of the relationship – adhere to the agreed structure. Like with all sourcing models, if one party deviates from the model, the relationship is strained and trust is lost.

The parties will need to trust each other sufficiently to afford a greater level of transparency than is customary with other contractual models. If a party experiences changes in its interests, business strategies or demands, it is important that this information be shared in sufficient detail to allow the parties to address what changes may need to be made, whether that should cause a re-baselining or a change in measurable business outcome. These will be difficult to legislate for at the outset but the contract should afford the parties sufficient flexibility to ensure the ongoing success of the contract for both parties.

Some may feel an outcome-based contract implies a greater level of understanding and more sophisticated level of contracting between customer and service provider. However, more simplistically it involves good planning, a clear demand from the customer for increased innovation and cost savings and a genuine alignment of the service provider’sI lov and customer’s interests. Outcome-based contracting is not suitable for all services but for business processes the model is a joint endeavour that rests on the strength of the relationship and an honest and open sharing of information and risk and reward.

Source: futureofsourcing.com-A Clear Understanding of Outcome-Based Contracts?


Outsourcing DevOps? Here’s What to Look For – DevOps.com

DevOps synthesizes methods, processes and tools with the goal of improving your company’s velocity at which you deploy applications, which serves your customers better. Teams using DevOps best practices and tools to create production software are much faster than organizations using traditional infrastructure management and software development methods. In 2016, RightScale’s “State of the Cloud Report” estimated that 70 percent of SMBs were adopting DevOps methods. Every indication is that percentage has increased.

For companies that already understand the value of software development outsourcing, partnering with a capable outsourcing vendor for DevOps is a natural next step. For companies who want to embrace the benefits of DevOps but haven’t yet, aligning with a qualified DevOps outsourcing company is really worth considering.

Consideration No. 1: Pick the Right Project

If DevOps is new to your company, or the DevOps partner is new to your company—or both—it’s very important to pick the right project to begin work together. Also, it’s possible that the project you target will influence the selection of your DevOps outsourcing partner.

Here are some questions you may want to use in selecting the right project:

This question…. is important because… Which software, if successful, will show the clearest benefit (i.e.: ROI) to the company? Software with clear business benefit will generally get better buy-in from the user community, and higher quality participation. Which software has the clearest goals and scope of work? It’s always easier to achieve the goal, when the goal is clear. Do any projects require the use of new, unproven technology? Unfamiliar technology can be a dangerous variable in your work and risk estimates. How many other systems will the newly completed software need to integrate with? Integration testing is time-consuming and requires a high levels of coordination. Which projects are expected to have the longest duration? Unforeseen variables naturally occur in long running projects — personnel changes, other business distractions, loss of momentum, etc. Which projects are expected to require the largest number of participants? More people involved equals more complexity. What employees (IT and business stakeholders) will be part of the projects? DevOps requires good collaboration and speed. IT and business area participants must be able to fulfill their roles accordingly.

Consideration No. 2: Vendor Communication

In selecting the right outsourcing DevOps partner, the ability to communicate well is one of the most important considerations. A partner who communicates poorly can derail a relationship that has all the right methods and tools in place for success. design iterations and project sprints simply cannot happen if your outsourcing partner lacks the proper communication skills. Conversely, an outsourcing vendor who is truly acting like a partner in the relationship, communicating well and often, can help you overcome any number of unforeseen issues along the way.

Evaluate how well prospective vendors respond to your due diligence questions. Their responses could tell you a lot about how they’ll interact with you during the project. Are they clear? Do they interact in professional ways, or does it seem a bit random and disorganized? Are they prompt and timely in their interactions, or are there “black holes of silence”?

If you see evidence of poor communication during the due diligence process, you’ll almost certainly have problems when you’re actually engaged in working together. As you check references, try to determine if other customers experienced problems in communication and interaction—those can pose as red flags when it comes to selecting your vendor.

Consideration No. 3: Vendor Location

Global software development outsourcing is a proven success for many companies. However, you must be attuned to the vendor’s geographic location compared to yours. Would time zone differences be an issue? This may affect the geographic location from which you’ll select your outsourced DevOps team. In a recent survey, one-third of U.S. companies that outsourced to India considered the 10-hour (or more) time difference to be a big challenge. DevOps activities cannot be artificially hampered because of time zone issues. The best DevOps outsourcing companies have a business model that allows U.S. time zone companies to interact easily with the vendor’s “A team” supporting your project. Be wary of companies that assume that all Skype and conference calls will be done off-hours to your normal business day—or plan to have secondary members of their team available during your normal work hours.

Consideration No. 4: Vendor Technical Skills

As you examine a prospective outsourcing DevOps partners technical capabilities, consider these questions:

  • Do they have the relevant skills and tools experience I need?
  • Is this a core competency of the company, or the expertise of a small select few inside the company?
  • How does this company go about attracting new talent with these same skills?
  • What certifications do they hold?

Automation of good process makes it possible to eliminate bottlenecks in the software development cycle, so you can truly “sprint through your Sprints.” Automation tools must be used with consistency by you and your outsourcing DevOps partner. Perform an inventory of the available tools:

  • Will you be able to seamlessly (and automatically) promote code?
  • Can you perform test-driven design?
  • Can you perform test-driven development?
  • Can you easily associate features and fixes with promoted code?
  • How will you perform regression testing?

DevOps teams will have programming language expertise that includes Python, Ruby, PHP and Java. Remember: DevOps means infrastructure as well as applications, so a true DevOps outsourcing company will have employees with expertise in infrastructure-oriented software and tools such as Windows PowerShell, Docker, Puppet, Ansible and SaltStack. You may also want to look for expertise and certifications for networks, databases, and operating systems.

DevOps outsourcing companies should be experienced with the continuous integration (CI) method—the CI tools which support the associated processes. CI tools help merge source code updates from all developers on a specific software build, notifying the team of any failures in the process. Popular CI Tools include CruiseControl, Jenkins, Travis CI, TeamCity and GitLab.

The best partners employ a programming staff that have achieved certifications that are important for your DevOps project needs. In addition to certifications around the tools and language mentioned earlier (such as Puppet Certification, for example), you will want to look for certifications in:

Consideration No. 5: Vendor Commitment to Training

As you evaluate a prospective DevOps outsourcing company, ask yourself: Is continuous training a part of their business model? A good partner invests in their programming staff’s training on a continual basis. We like to see evidence that their programming staff regularly renews their certifications—and the outsourcing company should be actively advocating this.

Consideration No. 6: Vendor Experience and Size

To succeed with DevOps outsourcing, you need a partner who has relevant experience and is a size that complements your company size.

Experience. The ideal DevOps outsourcing team will have experience in your business vertical (example: discrete manufacturing, banking, etc.). It also should have expertise in the system functional area of your target project (e.g. finance, e-business order processing, warehouse management, etc.). Of course, the demonstrable experiences should include work using Agile and DevOps techniques.

Size. The right partner should be neither too large nor too small. The outsourcing company needs a pool of programmers large enough to keep with the intended work pace of your project. Conversely, we caution IT managers to be wary of extremely large outsourcing companies. Your project and company must be “big enough to matter” to the partner you select. If you are seen as too small in terms of the revenue opportunity, the outsourcing company will defer attention and their top talent to larger customers who are more able to influence decision-making.


Source: Devops.com-Outsourcing DevOps? Here’s What to Look For

Cashing in on the Future

A financial incentive is a key driver for new business initiatives and investments. Future of Work technologies have a lot of potential to reduce costs, but they also have many additional benefits, called non-cashable benefits. Despite their name, it is possible to drive additional revenues through these to maximize the gross profit.

RPA vs Outsourcing

Today, Robotic Processing Automation (RPA) is one of the most mature Future of Work technologies. It is great for managing rules-based, data-heavy and repetitive tasks and integrates with existing systems – even legacy applications, without the need for a drastic overhaul. A conservative industry estimate is that an RPA robot costs one-third of an offshore employee and one-ninth of an in-house employee. RPA can also process many routine tasks faster and more accurately than most humans, allowing for significant reductions in overhead/FTE costs.

We have found that the typical ROI for RPA is between 300-800% over 5 years, with an average payback point achieved in under 18 months. The savings are not always back-loaded – in some cases of drastic process optimization, we have seen returns within as little as four months.

While BPO has helped many businesses achieve savings in the past decades, there are several underlying flaws with the offshoring model. For instance, it moves work to cheaper locations across the globe, resulting in work that is disconnected from the in-house processes (as discussed in the previous blog). Aside from this potential inefficiency, there is a high rate of attrition (offshoring roles traditionally have high growth and low salary), as the offshore labor market has become saturated over the years. So, while it may have started off as a cheap solution for most businesses, it tends to not remain economical due to increasing operational tensions, competitive labor markets and high inflation rates.

Who is Losing Out?

When there are larger costs for your resourcing solutions, it is the customer and employees who ultimately take the biggest loss. While labor arbitrage through offshoring may generate net savings, customers tend to suffer from lower-quality or less responsive services. This is an inherent trade-off to moving work hundreds of miles away. Additionally, employees tend to encounter issues with miscommunication, which can lower the quality of employment satisfaction. This is where a comparison between existing outsourcing models and RPA comes into the spotlight. Labor arbitrage through RPA tends to generate even larger savings, but without the bulk of the downsides listed above. In fact, RPA is increasingly recognized for the non-cashable opportunities it provides to a business.

Cashing in on the Non-Cashable Benefits

We like to represent the benefits of RPA under Mary Lacity’s “Triple Win” model. Automating processes that consist of routine, manual tasks can benefit not only the company, but also the employees and customers. The following are some examples of the common benefits we’ve seen among our clients:


  • The economics of RPA means that you are guaranteed to get hours back to your business. Time spent doing repetitive tasks can now be shaved off or dedicated to more valuable work.
  • Processes done by robots are always more accurate and faster than those done by humans. This provides a competitive advantage and improved output quantity and quality.


  • RPA takes the robot out of the human, so employees can look forward to more enjoyable and purposeful work
  • Employees learn new skills such as administrating robot workforces or working alongside assisted automation


  • Optimized workflows translate to faster turnaround times and improved service quality for customers. We often see improved customer satisfaction levels from RPA
  • Customers also enjoy service consistency and round-the-clock availability


High cash benefits are possible not only through the large ROI of Future of Work technologies like RPA, but also indirectly through non-cashable benefits. The benefits far outweigh those seen in traditional outsourcing models and provide promising solutions for both the business and the customer. These non-cashable benefits may be more difficult to quantify, but can ultimately make a significant business impact.

Source: blog.symphonyhq.com -Cashing in on the Future

The ITIL 2018 update better catch up to modern IT

ITIL, once known as the Information Technology Infrastructure Library, was last updated in 2011. A lot has happened since then, and for an ITIL 2018 release to regain the relevance that the IT service management framework has lost, it must accommodate the drive toward DevOps.


IT projects are moving away from Waterfall’s cascade style of deployment, with large initial releases followed by interim patches and functional upgrades at six- or 12-month intervals. Instead, services and applications have become continuous delivery projects with new functionality updates that release in monthly, weekly or shorter time sequences. Containerization begets new methods to manage software packaging, release and management. The move to a microservices-based, composite application model has enhanced distributed applications.

These changes to IT delivery forced many of the organizations that adopted ITIL to either massively adapt it to retain IT service management (ITSM) efficacy or drop it in favor of other frameworks that better meet their needs.

Google Trends

Figure 1. Interest in DevOps, as illustrated by this Google Trends search data, picked up around the same time ITIL was updated in 2011 and has shot up steadily through the end of 2017. An ITIL 2018 update could steal IT organizations’ attentions again.

Few organizations have adopted ITIL fully, but have rather integrated pieces of it with other, internal service management processes that function better than what is nominally best practice.

This piecemeal adoption has hindered outsourcing companies that want to apply a full ITIL framework to a customer’s environment, as well as service management software vendors that sell their products as ITIL-compatible.

Figure 2. ITIL started in U.K. government projects in the 1980s. Yet, it only gained traction when U.S. companies started to use it, and the idea later crossed back over the Atlantic.

The ITIL 2018 update has more than internal or DevOps-based methodologies to take into account. It also must maintain commonality with the ISO standard on service management, ISO 20000, which is currently in its 2011 version. ISO 20000 Part 11 maps out how ITIL and ISO 20000 interact and intersect with each other.

ITIL 2018 expectations

Axelos, a joint venture company set up by the U.K. government’s Cabinet Office and private entity Capita plc, is the group that oversees ITIL and that will control ITIL 2018’s upcoming release, which is based on research conducted with the global service management community. This update to ITIL should be good news for organizations with ITIL processes in place, but as always, the devil is in the detail.

If everyone offers ideas about what would make the fastest, best racehorse in the world, what comes out the other end is a camel.

If it is to survive the rapid rate of change in modern IT, ITIL 2018 will need to fully embrace continuous development driven by DevOps, as well as work harder to break down the silos of control in the development, test and operations environments. Users must also see ITIL 2018 as a path to more streamlined and effective processes, rather than as a constraint to task completion.

Axelos reported that it spent 18 months communicating with constituents of the service management chain, and that, as a community-driven initiative, ITIL changes will reflect the needs of real-life organizations and individuals. While community insights are important, too much input can confuse and suppress progress. If everyone offers ideas about what would make the fastest, best racehorse in the world, what comes out the other end is a camel. Unless those who provide input already face the pressing issues of moves to hybrid cloud, continuous development, containerization and DevOps, their goal could just be to optimize old-style ITIL processes to make cascade projects move faster, rather than to bring the ITIL 2018 release in line with modern operations. For example, in U.K. government IT projects, Agile and DevOps are far less common than they are in the private sector. Both groups are ITSM constituents that ITIL 2018 aims to please.

ITIL’s value

ITIL, particularly in large organizations, creates common processes to deal with many issues that arise across IT infrastructures. ITIL-structured IT organizations should more easily identify recurring issues and eradicate root causes. ITIL allows large IT deployments to continue to scale by automating many functions that would otherwise be carried out as standalone tasks by individual IT operations admins.



Find more PRO+ content and other member only offers, here.

However, ITIL implementation also risks becoming unwieldy and expensive. It has been criticized for cementing many of existing IT environments’ problems, such as siloed development, test and operations groups, and for working poorly with other ITSM and business approaches, such as Agile and Six Sigma.

The ITIL 2018 release must demonstrate awareness of these problems and dedication to get ahead of them. With its strong focus on process, ITIL 2018 must better cover hybrid IT environments, relatively static platforms and highly dynamic ones. ITIL 2018 must also become far more flexible internally — seven years between updates does not demonstrate ongoing relevance.

ITIL 2018 must address where it sits in the wider scheme of things. It cannot fall further into a perception of it being the center of the universe. It must work alongside many other tools and approaches that businesses use.

There is little detail available about the content of the ITIL 2018 update, which Axelos announced at the IT Service Management Forum USA Fusion event in Orlando, Fla., in the fall of 2017. This is where the devil might lie in wait: Organizations that seek to adopt or continue using ITIL must read all the details as they come out to ensure that any investment in ITIL 2018 is worthwhile and ready for future developments. It is not enough to take on such an involved ITSM framework as a short-term, tactical solution.

Source: searchitoperations.techtarget.com-The ITIL 2018 update better catch up to modern IT

Legal, ethical issues could slow adoption of AI for finance

The short answer to the longstanding question about whether the use of artificial intelligence in business could create intractable ethical, legal and regulatory issues just might be: It depends on the humans.

Businesses have started using AI for finance applications that are powered by machine learning processes, but their embrace of AI technology begs the question of whether computers will follow the same standards and principles that humans are expected to follow. For some in finance and technology, the answer does indeed boil down to how people program and oversee AI tools.

“One key aspect of artificial intelligence is that it is just technology, which is an extension of human practices and thinking,” said Lex Sokolin, global director of fintech strategy at Autonomous Research in London. “It may automate and make faster certain decision-making — for example, requiring one person [assisted] by AI to do the work of 50 people previously — but that decision-making will reflect all the biases and mistakes of human society.”

Using AI for finance holds the potential of having the computer find valuable information that will allow companies to see previously unseen patterns and use that insight to make more informed decisions and pursue bold strategies. Using algorithms and machine learning, AI-powered tools “learn” from “experience” what their human programmers want them to learn.


For businesses that need help making sense of trends affected by the requirements of financial regulations, using AI for finance could be a boon, allowing computers to do the work of scores of employees. But the flip side of relying on AI for finance regulations is that the technology could fail to discern legal or ethical issues that a human would otherwise recognize. This means for now, with mainstream AI technology still at a foundational level, human programmers will need to stay on top of how a machine is learning to ensure that boundaries aren’t crossed.

“The European data privacy rules, GDPR, speak about the ‘right to an explanation,'” said Gartner research fellow Frank Buytendijk, who specializes in digital ethics. “But with some types of machine learning, using stacks of neural networks, it is not always easy or even possible to fully retrieve where a decision comes from. We just need to trust it works in a way. This will need some attention figuring it out.”

Need for human oversight puts limits on using AI for finance

Referring to autonomous vehicles and systems, Buytendijk said that for the first time in the digital era, the potential ethical repercussions of a new technology are being discussed openly before widescale implementation.

“It is a bit of a paradox that one would want to be careful with exposing AI to the real world until you get it right, but that AI needs to be in the real world for all the data [it needs] to learn. This problem hasn’t been solved yet.” He added: “As we figure out how machine learning works, maybe as consumers we should be more tolerant as well, and give the market some time and space in order to get it right.”

Frederic Laluyaux, CEO of the business intelligence software company Aera, believes that for the foreseeable future, AI technologies will help with black-and-white decisions, but “the shades of gray will be decided by humans.”

The need for a human touch could complicate AI’s promise to autonomously analyze unstructured data that is interwoven with complex laws and regulations. To ensure that companies stay above board, a human should be kept in the loop, said Sokolin of Autonomous Research. “That means automated technology should have a human copilot that can course-correct what the algorithm is doing,” he said.

Businesses should rely on vendors for guidance on how to use AI for finance processes, but they also need to learn on their own how to audit the software to understand how it works and see the implications of its decisions, Sokolin said.

“AI needs parental oversight,” said Gartner’s Buytendijk. “We don’t have to be afraid that the robots will wipe us all out, or big dystopian visions like that. But we need to make sure that applications that use AI techniques have some kind of rollback or override as part of the reinforcement learning process. And we need to make sure we arrange accountability and responsibility — and ownership of the data and the algorithms. In short, just get our digital governance right.”

Source: searcherp.techtarget.com-Legal, ethical issues could slow adoption of AI for finance

Robotic Process Automation changing the spectrum of business processing, to witness a CAGR of 33.3%

The global robotic process automation market is expected to grow at a CAGR of 33.3%during this year up to 2023 to reach 2,821.0 USD by 2023. Factors propelling the growth of robotic process automation market include increasing adoption of RPA technology for enterprise scale deployments, implementation at broader scale enabling easy implementation and high return on investment. The report segments the robotic process automation market by solution (interaction solution, automated solution (business process, industry specific, infrastructure automation, others), decision support and management solution) by Process (rule based and knowledge based), by Type (software tools and services), by Application Services (BFSI, healthcare and life sciences, IT & telecom, transaction intelligence, consumer services, others), and by region (North America, Europe, Asia-Pacific, Rest of the world (ROW)). The report studies the global robotic process automation market over the forecast period (2017-2023).

Robotic process automation technology involves application of smart software to perform high-volume, repeatable tasks such as data processing, entry and integration by reducing humans intervention offering quality, reduced time thus, increasing profit margin. Unlike traditional application processing software, robotic automation offers a platform easing the business processes.

Browse full research report with TOC on “Global Robotic Process Automation Market Outlook, Trend and Opportunity Analysis, Competitive Insights, Actionable Segmentation & Forecast 2023”

Key findings from global robotic process automation market

  • The automated solution is accounted to hold for largest share of robotic process automation market in 2016. Further, the infrastructure automation is expected to register high growth rate on account of increasing implementation of RPA technology in shared service organizations such as BPOs
  • Banking financial services and insurance (BFSI) application services is expected to grow at highest rate. The BFSI sector is in continuous effort to reduce the operation cost and increasing profit margins increasing the adoption rate of RPA technology
  • Geographically, North America is the largest market adopting RPA technology in the small and large scale businesses. The growth in the region is primarily due to presence of large players and continuous development of the RPA technology over the past few years
  • The adoption of RPA technology in Asia-Pacific region is set to register high CAGR over the forecast period. The increasing adoption and spending in healthcare, automotive and retail services drives the demand for the implementation of RPA in the region
  • Key players in robotic process automation Market are Peg systems Inc., Blue Prism PLC, Verint System Inc., Xerox Corporation, IBM, Arago Us, Inc., Accenture, Thoughtonomy Ltd., Ipsoft, Inc., Soft motive Ltd. among others.

Robotic Process automation – Alternate to outsourcing

RPA being an emerging technology is being adopted across various business processes across the globe. Robotics process automation (RPA) is a further step to the evolution of business process outsourcing. The technology enables to reduce the cost of operations by reducing requirement of employees to perform high volume rule based task. RPA technology offers companies an alternative to outsourcing and has high impact on reduced cost, making organizations to adopt the technology at high rate and broader scale across the globe.

Robotic Process automation Market – Regional Insight

North America region held the major market share in robotics process automation market. The growth in the region is attributed to adoption of RPA technology at broader scale. Further, the presence of major players in the region propels the growth for the robotics process automation implementation. The implementation of RPA software by small and medium enterprises at higher rate led to an increasing market share in the region. The implementation of RPA software and tools in BFSI sector is increasing rapidly in U.S. increasing the market size in the region. The greater adoption by financial, healthcare, human resource and banking sector drives the growth of RPA market in Asia-Pacific region. Further, Robotic Process Automation (RPA) software continues to grow significantly in the Asia-Pacific region, driven by trend opted by enterprises to create more of digital workforce in order to reduce the cost.

About Energias Market Research

Energias Market Research launched with the objective to provide in-depth market analysis, business research solutions, and consultation that is tailored to our client’s specific needs based on our impeccable research methodology.

With a wide range of expertise from various industrial sectors and more than 50 industries that include energy, chemical and materials, information communication technology, semiconductor industries, healthcare and daily consumer goods, etc. We strive to provide our clients with a one-stop solution for all research and consulting needs.

Our comprehensive industry-specific knowledge enables us in creating high quality global research outputs. This wide-range capability differentiates us from our competitors.

Source: globenewswire.com – Robotic Process Automation changing the spectrum of business processing, to witness a CAGR of 33.3%

IT isn’t the holy grail of GDPR – it’s an enabler

The GDPR saga rumbles on, with a degree of GDPR fatigue becoming apparent. IT departments were thrown the challenge of working out what was needed to meet GDPR guidelines as it was thought to be a security issue. It swiftly became apparent it was a people and process issue and not a technology one. So the IT departments passed the buck on to the legal, HR and finance departments. But as companies gain a handle on the policies and procedures they need in place to meet GDPR guidelines, they are now throwing it back over the fence to IT asking how they can help.

There are many IT vendors making many claims as to what IT can do to help with GDPR, but really it’s quite simple. It isn’t a security play; this should be being done already. It’s an enabler to get your processes right. IT departments have some excellent tools that they can deploy to help ensure business processes meet the GDPR guidelines, but the IT department can’t meet GDPR guidelines by itself. Here is a list of IT tools that can help, and indeed will make life simpler in the new GDPR world.

1. Data Discovery Tools

There are data discovery tools that help you understand what data is flowing through your organisation and where it is. These tools can help identify unstructured personal data, but also offer the analytics, tracking and reporting necessary to deliver accountability for file use and security.

2. Mapping Tools

Data mapping may not be an essential requirement of the GDPR, but meeting the requirements of the regulation would be very hard without a clear picture of the lifecycle of personal data in your organisation. Mapping tools allow companies to identify areas where there is a risk to the rights and freedoms of data subjects in order to specify and implement appropriate technical and organisational measures to mitigate the risk. They also allow for ongoing maintenance of data which is important.

3. Encryption Tools

These can be used in a variety of ways to support the guidelines, including protecting data in transit or at rest, providing verification of data integrity and authenticity, and even offering a means of secure destruction. It’s important to keep in mind though, that the encryption may need to be reversible and those responsible for your data must ensure that the technologies selected are appropriate for the formats needed.

4. Protection of Data in Transmission

The guidelines require that organisations implement adequate technical measures to protect personal data during transmission, over and between networks. This is to further protect confidentiality and integrity. You can do this through a combination of network protection (ensuring attackers are unable to intercept data) and encryption (to render the data unintelligible). Controls could include the use of virtual private network (VPN) solutions, disabling insecure protocols, supporting strong protocols and even private point-to-point connections between data centres.

5. Hosted Solutions

For smaller organisations the use of hosted solutions give access to high level security tools, thereby supporting their efforts to comply with the secure processing requirements of the GDPR. These could include robust firewalls, enterprise quality antivirus and web filtering, encryption of emails and management of all endpoints. By outsourcing the storage, backups, security, and processing of data, and provided they meet the requirements for appointing a data processor, organisations are able to significantly reduce their compliance burden.

6. Data Visualisation Tools

With companies generating more and more data, year on year, effective data management i.e. the use of architectures, policies and procedures to manage the information lifecycle needs of organisations, is becoming increasingly challenging. Data visualisation tools that are simple to use can help organisations uncover what personal data is hidden, identify risks, and accurately classify all personal data, providing the intelligence to demonstrate many obligations for GDPR compliance.

7. Monitoring Tools

No later than 72 hours after having become aware of a data breach your company must notify the supervisory authority (ICO). With the time involved in detecting a breach currently being measured in months, this requirement presents a significant challenge to companies. But there are IT tools that monitor and log activity, and create alerts when anomalous events are detected, and support reporting both for the purpose of breach notification and continuous improvement.

8. Retrieval of Data Tools

Under the new guidelines, organisations should be able to locate and retrieve personal data at the request of the data subject. Tools that support the effective retrieval of data from systems in common machine-readable formats should be used, in order to minimise the overheads that might be incurred as individuals exercise their rights.

9. Disposal of data and IT equipment

Your organisation needs to be able to clean and dispose of data and IT equipment previously used for the processing of personal data to ensure permanent erasure, for example, through the use of electronic file shredding programmes.

10. Robotic Process Automation

Finally, companies might also like to consider using robotic process automation if they aren’t already, as this is an effective way of helping to maintain compliance. RPA ensures greater accuracy of processing, and thereby compliance by removing human error. It also ensures greater security of data and information. RPA can be used to improve compliance and security in many areas including, HR, legal, finance and IT.

Technology is a great enabler for the correct use of information within a company’s business processes. IT will help find the information, sort it, store it correctly and put security around it, and then ensure it is deleted correctly when a business no longer requires it, helping you meet your GDPR requirements.

Source: itproportal.com-IT isn’t the holy grail of GDPR – it’s an enabler