Why Digital Transformation is a Must for Organizations in 2018 | Analytics Insight

With innovation cycles getting shortened accompanied by intense competition and globalization related challenges, the analytics-driven transformation has become go-to for almost all businesses. With challenges also come opportunities from which the companies can benefit. HCL’s corporate vice president, Anand Birje says, “Over the past four or five years, enterprises were pushed hard to do anything in the field of analytics, big data and digital transformation. They were being pushed because there was this fear about what their competitors might be doing, so there was this feeling that they had to do something digital.” Digital transformation presents rich opportunities and developing a strategic plan to manage data assets can lead to long-term success.

Customers now have a wide range of providers, thanks to globalization that has made it possible for competitors to emerge from anywhere and with any kind of price range. To maintain a value-driven relationship with customers, companies are expected to operate with a slim margin, balancing both profits and product innovation. According to a Gartner report, almost 32 percent of top leaders in big organizations have confirmed to be undergoing a digital transformation in their processes.

Rather than simply enhancing or supporting traditional methods, the transformation stage of digital signifies new types of innovation using software and computerized technologies strategically. Industry 4.0, also referred to as the fourth industrial revolution, emphasizes the importance of bridging the gap between the physical and digital realms. Technologies like cloud computing, cyber-physical systems, Internet of Things (IoT), cognitive computing together help create what is called as a ‘smart factory’.

One of the major banks was using an agile and scrum method for proof of concepts with a timeframe between 8 to 12 weeks. With numerous product cycles and users not willing to wait for final products, the entire process got confusing. An organization must first develop a business value chain which specifies the objectives and goals clearly and then proceed to build its big data and analytics capabilities.

Large volumes of data can be turned into assets for organizations with proper digital efforts and value chain development. Data related to research and development, product, engineering, supply chain, manufacturing, production keep on piling up. A unified view of the business helps extract data of significance from disparate systems like ERP, SCADA, and CRM. This helps gain useful insights that further helps in the planning and decision making course for a company.

In addition to the big data an organization owns, IoT data in the data cloud adds significant volume to datasets. Effective big data analytical solutions need to be deployed to manage the datasets and generate perishable insights to take actions at the moment. Variances and consequence of any kind of business processes can be linked using predictive analytics tools. For instance, production lines slowing down is a consequence which can be attributed to say a variance in a supplier’s component having a design defect that doesn’t match what is required in the product assembly. Most importantly business processes are time sensitive and big data provides a real-time decision-making opportunity that can strategically improve a company’s performance and take it above other competitors.

As is true for any kind of change, re-architecting the business structure also means changing the way employees work, changing their responsibilities, reporting relationships and overall changing the organizational culture. Training and support of those involved in transformation efforts should be taken care of by the human resources department for a smooth and effective transition to take place.

Now the hype surrounding big data, analytics and digital transformation has reached a dead end. Companies can be sure of success only when they do their homework on sound strategic planning and align project initiatives with a long-term vision and deploy the best available tools and resources in line with absolute strategic clarity.

Source: Analytics Insight-Why Digital Transformation is a Must for Organizations in 2018


In a world of bots, AI and big data, how can employees and businesses survive?

With the Fourth Industrial Revolution hailed as bringing about a digital boom on the global economy, many may think: “Are we not we already well into the digital economy era?”.

It is true that there are now countless apps and computing technologies that allow people to conveniently hail a taxi, book a hotel, or clean floors with a robot. Smart machines can also already drive cars, diagnose patients, and manage finances more effectively than humans. But in a new analysis – What to do when Machines do Everything – we found the real boom is only just beginning.

In the years to come, AI will create further value, for example around safeguarding financial health, insuring families, and enabling people to heal and govern themselves – and this is just the beginning. Systems of intelligence, which combine hardware, AI software, data, and human input will help improve countless customer experiences, business processes, products and organisations.

Jobs and businesses will undoubtedly be impacted. One of the most common concerns is that the bots will take over everything. While it is true that machines will replace some occupations, and make some current skills irrelevant as robots do more of the everyday, mundane tasks, people will also become even more vital to helping an organization innovate and grow.

Machines are getting smarter every day and doing more and more; they will soon change our lives and our work in ways that are easy to imagine but hard to predict. The debate has, thus far, been in the hands of theoreticians: it is now time for pragmatists to take over. These pragmatists – whether companies or individuals realize that machines will replace some occupations, putting pressure on wages for some jobs and making some current skills irrelevant. However, machines will also enhance the human element of work. In fact, more than 80 percent of teaching, nursing, legal and coding jobs will be made more productive, beneficial and satisfying through artificial intelligence. While machines will learn to do more things, and will perform tasks more economically, more efficiently and with fewer errors, this will augment the human experience, generating more jobs, even creating professions that do not even exist yet.

As we expect 20 percent of the more administrative portions of a job go to a machine, the future workforce will require more people to fill jobs currently in short supply: data scientists, designers, technologists, and strategists, as well as create jobs that do not even exist yet.

Materials, Machines and Models – the formula to ‘win’ the Fourth Industrial Revolution

The digital revolution is fundamentally a growth story. While the future of an automated workforce can be frightening, the artificial intelligence (AI) revolution will create a huge wave of opportunity for businesses and individuals who are prepared. Typically, every previous revolution has followed such a pattern: innovation bubble, stall, and then boom. The Fourth Industrial Revolution will be no different. Early digital economy winners have aligned the Three Ms – materials, machines and models – and use them to their advantage.

Firstly, sensors will be required on nearly every “thing” – IoT devices, RFID sensors, accelerometers, motion sensors, etc. – to create massive amounts of data that is the new raw material of the digital economy. Secondly, systems of intelligence (machines) will be required to “process” this new raw material data to improve business productivity and customer. Finally, new commercial models will emerge that monetise services and solutions based on these systems of intelligence.

However, without the right business model to support data-fuelled machines, companies will struggle to be successful. Business leaders will need to decide how to instrument everything, how to harvest all the resulting data, how to ask the right questions of the data, and to “teach” the AI systems what to look for, what is meaningful, and what is immaterial.

Five essential plays for winning with AI

Each of the Three Ms in today’s business success formula must be activated to move AHEAD. There are five distinct approaches for not only winning with AI but surviving and thriving in this time of transition – automation, halos, enhancement, abundance and discovery.

1. Automation: Outsource rote, computational work to the new machine. This is how Netflix automated away Blockbuster.

2. Halos: Maximise the data products and people generate – via their connected and on-line behaviours – to create new customer experiences and business models. GE and Nike are instrumenting their products, surrounding them with halos of data, creating more personalised customer service and products as a result.

3. Enhancement: View the computer as a colleague that can help increase job productivity and satisfaction. For example, a car’s GPS system improves driver performance by enhancing navigation, providing alerts for road hazards, and ensuring the fastest route is taken on any given journey.

4. Abundance: Use the machine to open up vast new markets by dropping the price-point of existing offers. For example, UK-based start-up, Brolly, has created an AI enabled insurance advisor to allow customers to understand, manage and buy the insurance they need.

5. Discovery: Maximise use of AI to conceive new products, new services, and new industries. Just as Edison’s light bulb led to discoveries in radio, television, and transistors, today’s new machines will lead to the next generation of invention.

The world is changing faster than ever before. Our children and grandchildren will study the advances of the Fourth Industrial Revolution, just as we studied the great technological innovations of Albert Einstein and Thomas Edison. Automation and the rise of AI are truly deep and unstoppable forces – they are the core of this incredible pace of change. The shift to the new machine and AI is inevitable but if managed wisely, it will ultimately be a positive force for companies, individuals, and society. Leaders can compete and win in the next phase of global business by driving productivity, customer intimacy, and innovation if they align the three Ms and think AHEAD.

It is time to build our own future, complete with a sense of optimism and confidence. When machines do everything, there will still be a lot for companies to do. It is time to start now or risk being left behind.

Ben Pring, Vice President, Cognizant’s Center for the Future of Work and co-author of What to do when Machines do Everything

Source: itproportal-In a world of bots, AI and big data, how can employees and businesses survive?

How to institute an agile IT outsourcing process

Traditionally, IT organizations have spent six months to a year or more on the IT outsourcing transaction process, finding the right providers and negotiating a suitable contract. But as IT services — and, increasingly, as-a-service— deals have gotten shorter, that lengthy process may no longer make sense.

Industry advisors and consultants have debated the potential benefits of speedier sourcing for several years. In today’s rapidly changing business and technology landscape, it may become an imperative. But an effective outsourcing engagement demands more than just an accelerated version of the traditional IT services transaction process.

“Typical attempts to speed up the process include leaving out important activities or rushing to a solution to meet completion dates or budget objectives. In some cases activities that are skipped can be picked up and completed during transition,” says Michele M. Miller, director of KPMG’s Shared Services and Outsourcing Advisory. “However, we find that in most cases these activities are never completed and result in lost value and dissatisfaction in the outcome of the outsourcing project.”

Preparing for an agile approach to outsourcing

CIOs must take four steps to make sure they prepare their organizations for a new, agile approach to outsourcing, Miller says. First, they must define their business strategy, including the future state of IT and business services, in order to accurately asses how outsourcing will impact their companies down the road. Second, they need a clear understanding of their base case — the current cost of doing business today and down the road. Third, they need to define their target operating model (aligned with business strategy) in order to calculate the potential benefits of internal optimization vs. outsourcing or resourcing.

Finally, they must assemble a dedicated and experience outsourcing transaction team that was involved in building the strategy and is empowered to work closely with providers on day-to-day planning, design, and documentation of the solution as well as oversight of desired business outcomes. This preparation takes time an effort. However, “these steps are required for a successful outsourcing engagement,” says Miller, “and most companies are willing to put in the effort.” In fact, part of the reason Miller’s group began to document this agile approach to outsourcing was the fact that some companies had already established these key components.


With that foundation in place, IT leaders can attempt a more agile approach to outsourcing. Like its namesake software development approach, an agile outsourcing transaction process involves constant communication and collaboration between the IT organization and its providers throughout the outsourcing lifecycle, adapting as needs change. Unlike the traditional sourcing approach in which IT service customers approach the process in a linear fashion — gathering requirements, creating an RFP, engaging providers, and drawing up a contract — agile outsourcing transactions are more fluid.

Agile outsourcing starts with a series of sprints. “The sprints focus on collaborative ‘solutioning’ vs. the traditional approach, where the client outlines a solution up-front, often excluding other potentially beneficial alternatives from serious consideration,” Miller says. “Via these sprints, the parties consider alternatives together and jointly build a solid, viable solution. This results in a more-accurate RFP response, less time required in the due diligence phase, and more precise pricing during final pricing submissions or best and final offer.”

Because the process is collaborative, with both parties knowledge of requirements and solutions early in the process, timelines can shrink significantly. In fact, business requirements and solutions are so well understood that a traditional 26-week timeline can be condensed to as little as 12 weeks, Miller says. But increased speed is just one of many benefits. Agile outsourcing can sharpen the focus on business outcomes and instill greater collaboration not just between client and provider, but also among a company’s ecosystem of suppliers, in delivering those outcomes, according to KPMG.

Most companies are drawn to the agile outsourcing concept, but not all can make it work. “These projects are not shorter because we leave out critical processes; the client needs to have completed the four key requirements mentioned and be willing to work in the fast-paced iterative environment and make decisions quickly throughout the project,” Miller says. “Similar to many components of outsourcing there isn’t a single approach which works in all situations.”

IT service providers are game for the new approach, according to Miller. “They understand that a collaborative approach to sourcing tends to result in a more successful outcome for both parties because each shares in the responsibility for the design of the solution.” However, it does require that they, too, have done the upfront work of designing and documenting their solutions for ease of integration into the process.

Source: cio.com-How to institute an agile IT outsourcing process

Automation & AI – the human workforce’s new best friend?

Could AI and automation become the employee’s new best friend at work? Gareth Hole at NICE answers that question in this exclusive op-ed for CBR.

Robotic Process Automation is a huge trend with businesses across the world. By combining artificial intelligence with other technologies, organisations are automating routine, repetitive businesses processes to improve efficiency and drive better results. According to the National Association of Software and Services Companies, RPA can already reduce operations costs as much as 65 per cent, with ROI within as little as half a year.

Every business has processes that can be automated from start to finish by an unattended robot, working without intervention, 24/7, without errors, collecting and executing tasks from a queue. But what about the business processes that have decision points requiring human intervention or communication skills?

This is where attended desktop automation comes into play. Attended desktop automation allows a dedicated, smart desktop robot to help a human with certain tasks. This robot can mimic human actions, from copying and pasting information, to data inputting and even opening up applications and performing actions. It can even exceed what a human could achieve on their own, by gathering and analysing large amounts of data 100% accurately and rapidly in real-time and taking actions based on the results. All of these activities can occur on an employee’s desktop, in the background, triggered by any type of event, such as a button click, switching tabs, checking a field has specific data or even a complex combination of multiple events.

Recent improvements in algorithmic techniques and the expansion in the use of deep neural networks have also enabled significant improvements in the technology’s ability to deliver value.

In the contact centre industry, for example, where agents often have to juggle multiple tasks, (talking to customers, sourcing information, inputting data etc), attended automation certainly lightens the load. It allows those agents to focus on talking to a customer whilst tasks like looking for relevant data in multiple applications or figuring out what the best next step to take is, are done for them in real-time.

With this approach, the human and the desktop robot are working side by side, in full collaboration, with humans overseeing the execution of each activity. Humans can then focus on more interesting, valuable work, while also being empowered to make the best decisions in real-time.

Large businesses that run attended desktop automation robots, enabling their employees to make the most of their expertise and focus on the essence of their jobs, report high customer and employee satisfaction and operational efficiency which leads to a better bottom line. One of the UK’s largest mobile network provider, has automated 32 processes across a wide variety of process types, realising a saving of over 4 million seconds per month in automations alone. Using both attended and unattended automations, there is also the expectation of delivering about £1 million per year of additional benefits from these processes.

Attended automation can also identify events and processes that require training, enabling managers to take the necessary steps to improve the employee’s performance. For example, if the employee is required to read a disclaimer as part of the call but the disclaimer text was only open for two seconds, the system can detect that it is most likely that the employee did not read the disclaimer, and an alert will be sent to the manager.

Managers, in turn, will be better equipped to focus their limited time on delivering tailored coaching and support. This will help employees further hone their customer service skills, as they focus on delivering the sort of service that builds loyalty and satisfaction, and not on mundane, routine tasks.

Deciding on what to automate can be a huge challenge. With customer expectations constantly changing and new channels of engagement emerging, deciding on where to begin, as well as the long-term plan is not always straightforward. This is where attended desktop automation can again help, this time by gathering process information to uncover further opportunities to optimise those processes in real-time.

There is also the issue of how automation fits in with existing systems and processes. For example, does process automation still have value against a backdrop of investing in ‘best of breed’ IT systems? With traditional automation, the value can often be challenged but with attended desktop automation, a smart desktop robot can leverage even more value out of those systems to help their users in real-time.

Every organisation, in every vertical, has repetitive, time-consuming, error-prone processes which demand accuracy and speed, and don’t necessarily rely on human ‘out of the box’ thinking. The automation of these processes has become a reality but there is a growing realisation that humans can add more value to an organisation when freed from this repetitive and mundane work.

Attended desktop automation does not just save organisations valuable employee time. You could go as far as calling it the employee’s new best friend, keeping them engaged in the most important and valuable tasks for the business. After all, who wouldn’t want their own smart robot helper?

Source: cbronline.com-Automation & AI – the human workforce’s new best friend?

Robots May Not Take ­­­Your Job After All

Over 150 years ago, British author Samuel Butler predicted the rise of artificial intelligence, calling for a “war to the death” against machines – and arguing that that “the time will come when the machines will hold the real supremacy over the world and its inhabitants.”

Today, the inevitable conflict between man and AI-powered machines permeates our national discourse, as the threat of technological unemployment looms large. Elon Musk recently told a gathering of governors that AI is “the greatest risk we face as a civilization.”

Photo by Chris McGrath/Getty Images

But while the national narrative tends to reflect Butler’s dystopian fears for the 3.5 million truck drivers rendered obsolete by autonomous vehicles, or Mark Zuckerburg’s often mischaracterized vision of an educational future devoid of teachers – early adoption of AI suggests a far more collaborative reality.

Because in practice, AI often shines a light on areas where replacing humans with robots leads to suboptimal results – but cooperation between humans and machines, create outcomes that are better than either might achieve independently. Google Translate results may be technically accurate, for example, but fail to transpose idioms or slang that human translators can interpret. Interactive voice response (IVR) systems, unable to deal with the breadth and complexity of customers’ needs, trap frustrated consumers within the endless computerized loops until a human, armed with information gathered by computers, can direct them toward a solution. And in the education context, outcomes for AI-driven courses have failed to produce results, at scale – without the thoughtful support and encouragement of real-world teachers.

Of course, the concept of human-machine symbiosis isn’t entirely new. Average chess players paired with laptops famously took down chess masters and supercomputers in one 2005 match. PayPal’s founders paired human analysts with sophisticated algorithms to tackle complex fraud challenges – giving birth to the technology that undergirds mercurial tech titan, Palantir.

At American colleges and universities, human-computer symbiosis is allowing faculty like University of Michigan Professor Perry Samson to leverage students’ mobile phones to collect real-time information about student behaviors, and modify instructional strategies to improve learner outcomes. Technology helps teachers understand how students answer problem questions, whether they take notes, get confused, tag content in books, or review lecture material after class. Rather than replace them, technology is making human teachers more effective, at a time when even the most advanced AI isn’t able to data mine its way to non-obvious hypotheses that improve student learning. Educators, empowered by data, are drawing on human intuition and creativity to identify correlations between student behavior and outcomes. Technology isn’t just making teachers more effective, it’s enabling a new era of pedagogical innovation as a growing number of educators experiment with flipped, blended, and adaptive courses.

This approach is not unique to education. In customer service, the failure of IVR to deliver a positive customer experience has led to a blended approach that leverages AI to match customers with the customer service reps most likely to address their content needs – or even personality. Rather than replace call center operators, companies like T-Mobile are using AI platforms (like little-known “unicorn” Afiniti) to drive improved results of existing employees – by simply using AI to learn from historic interactions to better pair customers with their call center representatives. Same team, same customers, but upwards of 5% improvement in sales outcomes and retention with significant impact on the bottom line.

The applications of blended AI are broad. Stanford researchers have used advances in machine learning to develop a human-machine hybrid for translation, allowing bilingual human translators to move faster than they could if translating everything manually, while also improving the accuracy of machine translation. The blended approach allows for quicker translation on the basic language and uses humans to finalize the more subtle portions of the translation for context and culture.

A final dimension that most futurists are missing in discussing AI is that it actually creates whole new categories of jobs in training AI technology, explaining the contextual situations that AI machines don’t handle well (sarcasm) and measuring efficacy. Just as computers never really eliminated paper, we realize that AI – like the internet and renewable energy – will create whole new career paths.
In each case, AI is transforming the way humans interact with each other, in ways that make those interactions more efficient, effective, and even more meaningful. Could it be that AI might actually facilitate more authentic connections between individuals? The robots may still be coming for our jobs. But rather than competing with people, AI may turn us into the real supercomputers – and, in an ironic twist, make human interaction even more human

Source: Forbes-Robots May Not Take ­­­Your Job After All

What is outsourcing? Definitions, best practices, challenges and advice

What is outsourcing?

Outsourcing is a business practice in which services or job functions are farmed out to a third party. In information technology, an outsourcing initiative with a technology provider can involve a range of operations, from the entirety of the IT function to discrete, easily defined components, such as disaster recovery, network services, software development or QA testing.

Companies may choose to outsource IT services onshore (within their own country), nearshore (to a neighboring country or one in the same time zone), or offshore (to a more distant country). Nearshore and offshore outsourcing have traditionally been pursued to save costs.

Outsourcing benefits and costs

The business case for outsourcing varies by situation, but the benefits of outsourcing often include one or more of the following:

  • lower costs (due to economies of scale or lower labor rates)
  • increased efficiency
  • variable capacity
  • increased focus on strategy/core competencies
  • access to skills or resources
  • increased flexibility to meet changing business and commercial conditions
  • accelerated time to market
  • lower ongoing investment in internal infrastructure
  • access to innovation, intellectual property, and thought leadership
  • possible cash influx resulting from transfer of assets to the new provider

Some of the risks of outsourcing include:

  • slower turnaround time
  • lack of business or domain knowledge
  • language and cultural barriers
  • time zone differences
  • lack of control

Outsourcing services

Business process outsourcing (BPO) is an overarching term for the outsourcing of a specific business process task, such as payroll. BPO is often divided into two categories: back-office BPO, which includes internal business functions such as billing or purchasing, and front-office BPO, which includes customer-related services such as marketing or tech support. Information technology outsourcing (ITO), therefore, is a subset of business process outsourcing.

While most business process outsourcing involves executing standardized processes for a company, knowledge process outsourcing (KPO) involves processes that demand advanced research and analytical, technical and decision-making skills such as pharmaceutical R&D or patent research.

IT outsourcing clearly falls under the domain of the CIO. However, CIOs often will be asked to be involved in — or even oversee — non-ITO business process and knowledge process outsourcing efforts as well. CIOs are tapped not only because they often have developed skill in outsourcing, but also because business and knowledge process work being outsourced often goes hand in hand with IT systems and support.

Outsourcing IT functions

Traditionally, outsourced IT functions have fallen into one of two categories: infrastructure outsourcing and application outsourcing. Infrastructure outsourcing can include service desk capabilities, data center outsourcing, network services, managed security operations, or overall infrastructure management. Application outsourcing may include new application development, legacy system maintenance, testing and QA services, and packaged software implementation and management.

In today’s cloud-enabled world, however, IT outsourcing can also include relationships with providers of software-, infrastructure-, and platforms-as-a-service. In fact, cloud services account for as much as one third of the outsourcing market, a share that is destined to grow. These services are increasingly offered not only by traditional outsourcing providers but by global and niche software vendors or even industrial companies offering technology-enabled services.

IT outsourcing models and pricing

The appropriate model for an IT service is typically determined by the type of service provided. Traditionally, most outsourcing contracts have been billed on a time and materials or fixed price basis. But as outsourcing services have matured from simply basic needs and services to more complex partnerships capable of producing transformation and innovation, contractual approaches have evolved to include managed services and more outcome-based arrangements.

The most common ways to structure an outsourcing engagement include:

Time and materials: As the name suggests, the clients pays the provider based on the time and material used to complete the work. Historically, this approach has been used in long-term application development and maintenance contracts. This model can be appropriate in situations where scope and specifications are difficult to estimate or needs evolve rapidly.

Unit/on-demand pricing: The vendor determines a set rate for a particular level of service, and the client pays based on its usage of that service. For instance, if you’re outsourcing desktop maintenance, the customer might pay a fixed amount per number of desktop users supported. Pay-per-use pricing can deliver productivity gains from day one and makes component cost analysis and adjustments easy. However, it requires an accurate estimate of the demand volume and a commitment for certain minimum transaction volume.

Fixed pricing: The deal price is determined at the start. This model can work well when there are stable and clear requirements, objectives, and scope. Paying a fixed priced for outsourced services can be appealing because it makes costs predictable. It can work out well, but when market pricing goes down over time (as it often does), a fixed price stays fixed. Fixed pricing is also hard on the vendor, which has to meet service levels at a certain price no matter how many resources those services end up requiring.

Variable pricing: The customer pays a fixed price at the low end of a supplier’s provided service, but this method allows for some variance in pricing based on providing higher levels of services.

Cost-plus: The contract is written so that the client pays the supplier for its actual costs, plus a predetermined percentage for profit. Such a pricing plan does not allow for flexibility as business objectives or technologies change, and it provides little incentive for a supplier to perform effectively.

Performance-based pricing: The buyer provides financial incentives that encourage the supplier to perform optimally. Conversely, this type of pricing plan requires suppliers to pay a penalty for unsatisfactory service levels. Performance-based pricing is often used in conjunction with a traditional pricing method, such as time-and-materials or fixed price. This approach can be beneficial when the customers can identify specific investments the vendor could make in order to deliver a higher level of performance. But the key is to ensure that the delivered outcome creates incremental business value for the customer, otherwise they may end up rewarding their vendors for work they should be doing anyway.

Gain-sharing: Pricing is based on the value delivered by the vendor beyond its typical responsibilities but deriving from its expertise and contribution. For example, an automobile manufacturer may pay a service provider based on the number of cars it produces. With this kind of arrangement, the customer and vendor each have skin in the game. Each has money at risk, and each stands to gain a percentage of profits if the supplier’s performance is optimum and meets the buyer’s objectives.

Shared risk/reward: Provider and customer jointly fund the development of new products, solutions, and services with the provider sharing in rewards for a defined period of time. This model encourages the provider to come up with ideas to improve the business and spreads the financial risk between both parties. It also mitigates some risks by sharing them with the vendor. But it requires a greater level of governance to do well.

IT organizations are increasingly looking for partners who can work with them as they embrace agile development and devops approaches. “Organizations are rapidly transforming to agile enterprises that require rapid development cycles and close coordination between business, engineering and operations,” says Steve Hall, a partner with sourcing consultancy Information Services Group (ISG). “Global delivery requires a globally distributed agile process to balance the need for speed and current cost pressures.”

Outsourcing and jobs

The term outsourcing is often used interchangeably — and incorrectly — with offshoring, usually by those in a heated debate. But offshoring (or, more accurately, offshore outsourcing) is a subset of outsourcing wherein a company outsources services to a third party in a country other than the one in which the client company is based, typically to take advantage of lower labor costs. This subject continues to be charged politically because unlike domestic outsourcing, in which employees often have the opportunity to keep their jobs and transfer to the outsourcer, offshore outsourcing is more likely to result in layoffs.

Estimates of jobs displaced or jobs created due to offshoring tend to vary widely due to lack of reliable data, which makes it challenging to assess the net effect on IT jobs. In some cases, global companies set up their own captive offshore IT service centers to to reduce costs or access skills that may not result in net job loss but will shift jobs to overseas locations.

Some roles typically offshored include software development, application support and management, maintenance, testing, help desk/technical support, database development or management, and infrastructure support.

In recent years, IT service providers have begun increasing investments in IT delivery centers in the U.S. with North American locations accounting for more the a third of new delivery sites (29 out of a total of 76) established by service providers in 2016, according to a report from Everest Group, an IT and business sourcing consultancy and research firm. Demand for digital transformation–related technologies specifically is driving interest in certain metropolitan areas. Offshore outsourcing providers have also increased their hiring of U.S. IT professionals to gird against potential increased restrictions on the H-1B visas they use to bring offshore workers to the U.S. to work on client sites.

Some industry experts point out that increased automation and robotic capabilities may actually eliminate more IT jobs than offshore outsourcing.

The challenges of outsourcing

Outsourcing is difficult to implement, and the failure rate of outsourcing relationships remains high. Depending on whom you ask, it can be anywhere from 40 to 70 percent. At the heart of the problem is the inherent conflict of interest in any outsourcing arrangement. The client seeks better service, often at lower costs, than it would get doing the work itself. The vendor, however, wants to make a profit. That tension must be managed closely to ensure a successful outcome for both client and vendor.

Another cause of outsourcing failure is the rush to outsource in the absence of a good business case. Outsourcing pursued as a “quick fix” cost-cutting maneuver rather than an investment designed to enhance capabilities, expand globally, increase agility and profitability, or bolster competitive advantage is more likely to disappoint.

Generally speaking, risks increase as the boundaries between client and vendor responsibilities blur and the scope of responsibilities expands. Whatever the type of outsourcing, the relationship will succeed only if both the vendor and the client achieve expected benefits.

Service levels agreements

A service level agreement (SLA) is a contract between an IT services provider and a customer that specifies, usually in measurable terms, what services the vendor will furnish. Service levels are determined at the beginning of any outsourcing relationship and are used to measure and monitor a supplier’s performance.

Often, a customer can charge a vendor a penalty fee if certain SLAs are not met. Used judiciously, that’s an effective way to keep a vendor on the straight and narrow. But no CIO wants to be in the business of penalty-charging and collecting. Bad service from an outsourcing vendor, even at a deep discount, is still bad service, and can lead to greater problems. It’s best to expend energy on finding out why the SLAs are being missed in the first place and working to remedy the situation. Strong SLAs alone will not guarantee success when outsourcing IT services. They’re one of many tools to help manage an IT outsourcing deal.

For a more in-depth discussion of SLAs, see “What is an SLA? Definition, best practices and FAQs.”

Outsourcing deal lengths

What’s the best length for a skirt? While the outsourcing industry is not quite as fickle as fashion, the prevailing wisdom about the best length for an outsourcing contract has changed over the years. When outsourcing first emerged as a viable option, long contracts — as many as 10 years in length — were the norm. As some of those initial deals lost their shine, clients and vendors moved to shorter contracts.

As with most questions about outsourcing, the optimal answer depends on what’s being outsourced and why. While decade-long deals have largely gone by the wayside, a transformational outsourcing deal may require more time to reap benefits for both client and vendor. But when outsourcing desktop maintenance or data center support, a shorter relationship may work better. Generally speaking, overly long contracts (more than seven years) should be avoided unless there is a great deal of flexibility built into the contract.

Choosing the right outsourcing provider portfolio

Many years ago, the multi-billion-dollar megadeal for one vendor hit an all-time high, and the big IT service providers of the world couldn’t have been happier. But wholesale outsourcing has proved difficult to manage for many companies. These days, CIOs have embraced the multi-vendor approach, incorporating services from several best-of-breed vendors to meet IT demands. Most major IT services players have done their best to adjust to this trend. In fact, some leading CIOs not only work with a cadre of competing outsourcers, but expect them to meet joint deliverables.

Multisourcing, however, is not without great challenges. The customer must have mature governance and vendor management practices in place. In contract negotiations, CIOs need to spell out that vendors should cooperate and refrain from blaming each other, or else risk losing the job. CIOs need to find qualified staff with financial as well as technical skills to help run a project management office or some other body that can manage the outsourcing portfolio.

The rise of digital transformation has initiated a shift not back to megadeals but away from siloed IT services. As companies embrace new development methodologies and infrastructure choices, many standalone IT service areas no longer make sense. Some IT service providers seek to become one-stop shops for clients through brokerage services or partnership agreements, offering clients a full spectrum of services from best-in-class providers.

How to select a service provider

Selecting a service provider is a difficult decision. But start by realizing that no one outsourcer is going to be an exact fit for your needs. Trade-offs will be necessary.

To make an informed decision, articulate what you want from the outsourcing relationship to extract the most important criteria you seek in a service provider. It’s important to figure this out before soliciting any outsourcers, as they will undoubtedly come in with their own ideas of what’s best for your organization, based largely on their own capabilities and strengths.

Some examples of the questions you’ll need to consider include:

  • What’s more important to you: the total amount of savings an outsourcer can provide you or how quickly they can cut your costs?
  • Do you want broad capabilities or expertise in a specific area?
  • Do you want low, fixed costs or more variable price options?

Once you define and prioritize your needs, you’ll be better able to decide what trade-offs are worth making.

Traditionally, IT organizations have spent six months to a year or more on the IT outsourcing transaction process, finding the right providers and negotiating a suitable contract. But as IT services — and, increasingly, as-a-service — deals have gotten shorter, that lengthy process may no longer make sense. While the selection process still demands diligence, there are some more iterative transaction processes that can reduce the time required to procure IT services.

Outsourcing advisers

Many organizations bring in an outside sourcing consultant or adviser to help figure out requirements and priorities. While third-party expertise can certainly help, it’s important to research the adviser well. Some consultants may have a vested interested in getting you to pursue outsourcing rather than helping you figure out if outsourcing is a good option for your business. A good adviser can help an inexperienced buyer through the vendor-selection process, aiding them in steps like conducting due diligence, choosing providers to participate in the RFP process, creating a model or scoring system for evaluating responses, and making the final decision.

Help can also be found within your organization, from within IT and the business. These people can help figure out your requirements. There is often a reluctance to do this because any hint of an impending outsourcing decision can send shivers throughout IT and the larger organization. But anecdotal evidence suggests that bringing people into the decision-making process earlier rather than later makes for better choices and also creates an openness around the process that goes a long way toward allaying fears.

Negotiating the best outsourcing deal

The advice given above for selecting a provider holds true for negotiating terms with the outsourcer you select. A third-party services provider has one thing in mind when entering negotiations: making the most money while assuming the least amount of risk. Clearly understanding what you want to get out of the relationship and keeping that the focus of negotiations is the job of the buyer. Balancing the risks and benefits for both parties is the goal of the negotiation process, which can get emotional and even contentious. But smart buyers will take the lead in negotiations, prioritizing issues that are important to them, rather than being led around by the outsourcer.

Creating a timeline and completion date for negotiations will help to rein in the negotiation process. Without one, such discussions could go on forever. But if a particular issue needs more time, don’t be a slave to the date. Take a little extra time to work it out.

Finally, don’t take any steps toward transitioning the work to the outsourcer while in negotiations. An outsourcing contract is never a done deal until you sign on the dotted line, and if you begin moving the work to the outsourcer, you will be handing over more power over the negotiating process to them as well.

Outsourcing’s hidden costs

The total amount of an outsourcing contract does not accurately represent the amount of money and other resources a company will spend when it sends IT services out to a third party. Depending on what is outsourced and to whom, studies show that an organization will end up spending at least 10 percent above that figure to set up the deal and manage it over the long haul.

Among the most significant additional expenses associated with outsourcing are:

  • the cost of benchmarking and analysis to determine whether outsourcing is the right choice
  • the cost of investigating and selecting a vendor
  • the cost of transitioning work and knowledge to the outsourcer
  • costs resulting from possible layoffs and their associated HR issues
  • costs of ongoing staffing and management of the outsourcing relationship

It’s important to consider these hidden costs when making a business case for outsourcing.

The outsourcing transition

Vantage Partners once called the outsourcing transition period — during which the provider’s delivery team gets up to speed on your business, existing capabilities and processes, expectations and organizational culture — the “valley of despair.” During this period, the new team is trying to integrate any transferred employees and assets, begin the process of driving out costs and inefficiencies, while still keeping the lights on. Throughout this period, which can range from several months to a couple of years, productivity very often takes a nosedive.

The problem is, this is also the time when executives on the client side look most avidly for the deal’s promised gains; business unit heads and line managers wonder why IT service levels aren’t improving; and IT workers wonder what their place is in this new mixed-source environment.

IT leaders looking to the outsourcing contract for help on how to deal with the awkward transition period will be disappointed. The best advice is to anticipate that the transition period will be trying, attempt to manage the business side’s expectations, and set up management plans and governance tools to get the organization over the hump.

Outsourcing governance

The success or failure of an outsourcing deal is unknown on the day the contract is inked. Getting the contract right is necessary, but not sufficient for a good outcome. One study found that customers said at least 15 percent of their total outsourcing contract value is at stake when it comes to getting vendor management right. A highly collaborative relationship based on effective contract management and trust can add value to an outsourcing relationship. An acrimonious relationship, however, can detract significantly from the value of the arrangement, the positives degraded by the greater need for monitoring and auditing. In that environment, conflicts frequently escalate and projects don’t get done.

Successful outsourcing is about relationships as much as it is actual IT services or transactions. As a result, outsourcing governance is the single most important factor in determining the success of an outsourcing deal. Without it, carefully negotiated and documented rights in an outsourcing contract run the risk of not being enforced, and the relationship that develops may look nothing like what you envisioned.

For more on outsourcing governance, see “7 tips for managing an IT outsourcing contract.”

Repatriating IT

Repatriating or backsourcing IT work (bringing an outsourced service back in-house) when an outsourcing arrangement is not working — either because there was no good business case for it in the first place or because the business environment changed — is always an option. However, it is not always easy to extricate yourself from an outsourcing relationship, and for that reason many clients dissatisfied with outsourcing results renegotiate and reorganize their contracts and relationships rather than attempt to return to the pre-outsourced state. But, in some cases, bringing IT back in house is the best option, and in those cases it must be handled with care.

Source: cio.com-What is outsourcing? Definitions, best practices, challenges and advice

Unlocking the business opportunity of artificial intelligence

Today, if someone asked for thoughts on artificial intelligence (AI), your mind might paint a pop culture informed picture of a dystopian machine-ruled future or a chatbot with the lexicon of a seven year old.

That’s the problem with new technology. Our vision of the future is coloured by the realities of today, or in many cases, what we witnessed fifteen years ago in Minority Report.

Viewing AI through the lens of a futures market

It’s not a risky proposition to think that the value of AI will rise in the future. IDC suggests that $41 billion will be invested in AI systems for enterprises by 2024, and Forrester projects 13.6 million new AI jobs will be created in the next decade.

If you believe that AI will play a bigger role in business in the future, yesterday was a good time to begin the journey. Some businesses justify inaction by suggesting the technology is unproven; it introduces reputational and financial risk to a business. Why not sit on your hands for three years, and wait for the technology to mature.

Doing nothing is a high risk strategy. To begin with, first movers benefit massively from scaling their internal capabilities ahead of their competitors, particularly in a white hot recruitment market.

Second, to do nothing and to be seen doing nothing invites aggressive competitors to actively target those companies and their customers. Third, allowing competitors to shape the market is to defer to a process you have no control over.

Three areas of AI application

There are three immediate areas of business application for AI. The first is development of virtual assistants, designed to act on behalf of humans in order to better achieve our goals.

Today, there is a fast-growing trend for chatbots. This is perhaps unsurprising given the global popularity of instant messaging (IM) platforms. The format is familiar to anyone who has used IM, and with IM platforms being more popular than their social media equivalents, there is a large tech savvy audience.

WhatsApp alone has sends more messages than SMS globally. Consumers like the fact that messaging works both as an instantaneous, as well as an asynchronous, channel.

Today, chatbot adoption is fighting on two fronts. From a consumer perspective, if a chatbot is not a convenience upgrade on existing alternatives (such as Google search or mobile app functionality) the novelty value of chatbots will soon wear off. From a usefulness perspective, companies struggle to keep up with consumer expectations.

When Capital One launched one of the first Alexa skills in March 2016, customers immediately thought that they could conduct all their banking needs through it.

Capital One are early adopters of the platform and have learned a great deal in the last 18 months, pushing Amazon and the limits of the platform, in terms of ontology size and complexity, along the way.

Whilst chatbots may fade in time, the role of virtual assistants is here to stay. Whilst today many chatbots are merely the equivalent of a call center, interactive voice response (IVR) menu system or an FAQ knowledge retrieval system, over time their ability to handle more nuanced requirements and provide informed advice will grow.

Building successful virtual assistants requires a combination of magic and logic. Magic to build compelling experiences that change consumer behavior, and logic to build smart algorithms that continue to learn and improve decision making.

A second area of immediate business benefit is automation and augmentation. Automation of manual processes, particularly in legacy businesses with legacy technology, has significant cost base implications.

Whilst robot process automation (RPA) is nothing new, the smart application of machine learning to not just convert a manual process into an automated one, but to do so in an autodidactic way, constantly improving the effectiveness and efficiency of the process, is a prime application for AI.

Augmenting workforces with AI driven applications is another source productivity gain. Many forms of customer service interaction are now a combination of human and machine response.

Machines can make individual service representatives more productive by automating repetitive tasks and automatically prompting responses to commonly asked questions.

Inhibitors to value creation

Ultimately, the killer application of AI is the invention of new business models, products and services. It is alluring to think that a firm’s data contains a map to some hidden treasure of a previously undiscovered business model.

The reality is somewhat more mundane. Only those companies with access to the right analytical firepower, coupled with an ability to free their data from the shackles of legacy siloed databases, have a shot at legitimately creating new value from data. Both are serious undertakings with minimal shortcuts.

Talent availability is a serious inhibiter of AI growth. Without a sustainable capability model, businesses are struggling to attract people with the relevant skills, particularly when trying to compete with Google, Amazon and Facebook. Given the low supply, high demand nature of the AI labor market, workers are well compensated, with average salaries of $170k according to Paysa.

Legacy technology is the other hindrance to the implementation of AI applications. Identifying previously unknown relationships within data requires the integration of disparate data sources. Silos are the enemy of integration.

Those companies that have migrated their data to the cloud, have built robust APIs and have reached a higher degree of digitisation are generally in a better place to generate value from their data.

The clock is ticking

There are two ways of looking at generating business value today from AI. One is to get tactical. Developing proof of concept prototypes, getting real consumer feedback, and developing the opportunity to upskill colleagues and learn by doing.

The process of creating a backlog of prioritised use cases along with their respective business cases can help to focus development in small achievable chunks, with each new application building on the underlying knowledge model.

>See also: Is business data AI compatible?

The other is to take a longer term view, and begin to create the structure required to exist in a more AI mature world in three to five years’ time. While developing internal data analytics capabilities, migrating data from silos into an extensible cloud solution and building key strategic partnerships may not provide visceral evidence of progress in the short term, it is vital to long term sustainable success.

Either way, inaction is risky. As the world has been digitised, AI has begun to take off due to the exponential growth of data, reductions in costs of cloud computing and the scalability of virtual machines. Those that adopt an AI first mind-set early are in the best possible position to take advantage of this burgeoning field.

Source: information-age-Unlocking the business opportunity of artificial intelligence