Monthly Archives

March 2018

11 outsourcing myths debunked | In the News

By | In The News

Even as CIOs enter their third generation of IT services deals, misconceptions persist about the practice of IT outsourcing. Worse, new illusions have begun to emerge as outsourcing approaches have evolved. Achieving desired outcomes when working with third-party providers depends on clear-eyed understanding of what’s possible and what’s not, what responsibilities remain with the buyer and what new capabilities are required, what’s changed about outsourcing models and what remains the same.

CIO.com talked to IT outsourcing experts who work with IT buyers and vendors to help bust some of the most common myths around outsourcing today — and to aid IT leaders in setting up their outsourcing engagements for success.

Myth: The old ways still rule

Third-generation outsourcers may think they know everything there is to know about structuring engagements for success, but the reality is that the fundamentals of value creation from outsourcing have changed significantly. Consumption-based pricing is replacing fixed-price models. Contracts designed for efficiency and cost reduction have given way to deals aligned to business outcomes and growth.

“The fundamental mindset needed to succeed is very different, and a contract written for efficiency does not align with a contract that needs to drive growth,” says Jimit Arora, partner in Everest Group’s IT services research practice.

Read more in CIO

AI Helping DevOps: Don’t Ask, Don’t Assume – KNOW What Users Really Want | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

With DevOps’ core goal of putting applications in users’ hands more quickly, it’s no surprise that many enterprises have started to release and deploy software up to five times a month, instead of their earlier once-a-quarter schedule. Everest Group research suggests that over 25% of enterprises believe DevOps will become the de-facto application delivery model.

However, there continues to be a disconnect between what business users want and what they get. To be fair to developers and IT teams, this disconnect is due, in part, to end-users’ difficulty in articulating their needs and wants.

Enter AI Systems

AI Systems have strong potential to help product management teams cut through the noise and zero-in on the features their users truly find most valuable. Consider these areas of high impact:

  1. Helping developers at run time: Instead of developers having to slog through requirements, feature files, and feedback logs – and likely miss half the input – AI-led “code assister” bots can help them, during the actual coding process, to ensure that the requested functionality is created
  2. Prioritizing feedback: Rather than wasting time on archaic face-to-face meetings to prioritize features requested in the dizzying amount of feedback received from users, enterprises should build an AI system to prioritize requests from high to low, and dynamically change them as needed based on new incoming data
  3. Stress testing feedback: After prioritization, AI systems should help enterprises segregate the features users really want, versus those they think they want. AI can do this by crunching the massive volume of feedback data though machine learning and finding recurring patterns that suggest consensus. The feedback data should also be fed back to business users to educate them on market alignment of demanded and desired features
  4. Aligning development, QA, and production: Through its inherently neutral perspective, an AI system can smooth through the dissonance among the different teams by crunching all the data across the feedback systems to outline disconnects and create the alignment needed to satisfy end-user needs
  5. Predicting features: While this is still far-fetched, enterprises and technology vendors should work toward AI solutions that can predict features that will be requested in the next sprint based on historical data. In fact, AI systems should be able to analyze data across other enterprises as well to suggest relevant features to developers. The predictions could then be validated with real feedback from beta users, and the AI system further trained based on the validations

There are multiple other areas in which AI can potentially assist in understanding what the users want. For example, as we discussed in earlier research, AI can help developers create secure, performance-tuned, and production-ready code without being bogged down by typical feedback on features from the field.

What about Budget?

The good news is such an AI system will not burn a massive hole in enterprises’ budgets and should not require the zillions of data points that most typical, complex AI systems do. I believe these systems can be based on simple log data, performance feedback cycles, feature files databases, requirements catalogues, and other already existing assets. If that’s the case, they have great potential to help enterprises develop software their end-users really want.

Have you deployed AI in your Agile DevOps delivery cycle? I’d love to hear about it at [email protected].

Talent Management in Global In-house Centers: Are You Future-Ready? | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

There’s no question that digital technological advancements, evolving business requirements such as changing consumer needs and faster time to market, and a heightened focus on customer experience are significantly changing the profile of skills needed to deliver services. As most global in-house centers (GIC) are already facing challenges in hiring people with the right skills for the future, it is concerning that their talent-related preparation for such a tectonic shift is lacking.

Talent Management GIC_1

Here are four talent management imperatives for GICs to develop the workforce of the future.

1. Identification of Skills Gap

As automation and other technological advancements kick in, human skills, such as innovation, design thinking, problem solving, empathy, and ethical thinking will become more critical. Identification of skills gap will be pivotal for GICs’ talent acquisition and development strategy. A recent Everest Group study of 80+ GICs across India, Philippines, and Poland identified multiple, and difficult to hire, skills that are likely to become more important in the future.

Talent Management GIC_2

2. Upskill/Reskill Current Workforce

Firms’ talent challenges will intensify with the automation of transactional services. They will face the dual risks of a large existing workforce with many skills that are likely to become redundant, while struggling to find talent with the right skills for their future needs. Upskilling/reskilling existing talent is an important lever for GICs to address these challenges while preserving their trained workforce with string domain/industry know-how. (See our detailed report on upskilling/reskilling in GICs for additional perspectives.)

3. Evolve Talent Acquisition and Development Strategy

As GICs look to develop a future-proof talent strategy, they will need to think outside the box to tap into alternative sources of talent. Opportunities include hackathons, hiring from startups and other industries, project-based partnerships with specialist agencies, and flexible resourcing. From an L&D perspective, traditional classroom model needs to evolve as learning is becoming more real-time, customized, and digitized, e.g., MOOCs, simulation, and gamification.

4. Agile Human Capital Planning

With a dramatic decline in skills’ half-life, particularly in the technical space, GICs need to identify and focus on skills that are more likely to be critical for their growth. A more frequent approach to human capital planning might be essential to account for rapid changes in these skills.

While many GICs are still taking a wait and watch approach to the talent management issue, some have already embarked on this transformational journey. And those that are proactively addressing it are reaping big rewards.

Watch this space for more insights and success stories. And if you’d like to share your challenges, successes, or questions with us, please feel free to write us at [email protected] or [email protected].

The Threats of Data Harvesting Combined with Malicious Use of AI | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

For 20 years, the Internet has democratized access to information and learning, and allowed us to have a public voice and become part of online communities. Today, we’re at risk of losing out to those who wish to abuse our personal information and create divisions and havoc in the world.

The Cambridge Analytica / Facebook data harvesting case is the latest scandal to make the headlines, with much of the current debate focused on data harvesting for political or marketing purposes. But it ignores other serious threats we expose ourselves to by sharing information online.

One of these threats is data harvesting combined with malicious use of Artificial Intelligence (AI). It’s already here and has significantly increased personal and business risks. But due to lack of awareness about the threats, people innocently continue to share information on social media.

What are the Threats?

A recent report by 26 risk experts, including researchers from Cambridge and Oxford universities, cited a wide range of serious threats that could result from the malicious use of AI, including:

  • Automated hacking
  • Speech synthesis for impersonating victims on video and voice recordings
  • ID theft
  • Exploiting the vulnerabilities of AI systems for adversarial uses and data poisoning (fake news and Denial of Truth Attacks (DTA))
  • Repurposing of drones and cyber-physical systems for harmful ends, such as crashing fleets of autonomous vehicles, turning commercial drones into face-targeting missiles, or holding critical infrastructure for ransom

When the BBC asked me to comment on the report, I could think of some of the risks that are already possible.  By carelessly sharing information about ourselves and our work, we are simply increasing them:

  • Digital ID theft of family members and friends, much of which will be based on what is known about us on social media
  • Targeting of employees of businesses in key positions for criminal activities
  • DTA that turns truth into lies and vice versa. Much has already been said about fake news, but training AI to do wrong or suggest untruths is already going on. For example, the following graphic illustrates that Google and Bing searches for information about the Welsh language may have been manipulated by frequent use of search strings with negative connotations. These could be misleading for the young and the naïve

Data Harvesting FB - Blog

While global government action is being taken to mitigate these risks, each of us needs to take personal responsibility by, for example:

  • Questioning what we read online, particularly political ads veiled in community-style messaging
  • Being cautious about what and how much we share about ourselves, family, friends, and work online
  • Using alternatives such as search and social media that share less information with third parties. DuckDuckGo already offers search privacy, and the issues with Facebook may well lead to other platforms that offer smaller and protected social networks

Implications for RPA and AI-based Process Automation

As organizations increasingly focus on client data protection, we may see a tightening of policies against robots connecting to both web sites and enterprise systems. Some organizations frequently change the URL of specific web pages for exactly this reason – to make it difficult for robots to find those pages and access the information that they purvey. Other measures include visual and sound-based checks to separate robots from humans when signing up for online services.

We may well see technology companies make it more difficult for robots to access their software, for example, through human-only user licensing models, with checks to ensure that the user is a human and not a robot. However, after decades of efforts to make enterprise system integration easier, this would be a seriously backward step.

Interestingly, the fight against malicious AI is leading some companies, including Facebook, to hire thousands of people to check for fake or malicious content. Demand for cyber security skills continues to rise as well. These new hires will, in effect, augment the existing AI-based defense systems that on their own are not good enough to tell fake from real or outsmart malicious AI. Far from AI replacing people, it is creating new roles.

Implications for Customer Contact and Experience Services

A few years ago, service providers in this market segment added social media monitoring and management to their portfolio of services. Today, they will have to add social media truth management to their catalogues. Defending organizations against fake news and media will also expand the range of customer experience (CX), public relations, and marketing requirements. Consequently, there is likely to be a net increase in demand for CX and marketing management services. Service providers that can deliver differentiated authentication solutions, e.g., AI and people combinations that can find and differentiate fake from real and perform other tasks such as context analysis, will be in demand.

Another consequence would be that social media as a source of personal data for customization of products and services will shrink as more people opt out of data sharing.

While we’re a long way from the dystopian futures that have been depicted in many sci-fi movies, people and governments need to act now to mitigate risks and help us keep our freedoms and security.

GICs Accelerating the Automation Gear in Their Digital Drive! | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

In the beginning of the digital revolution, GICs were primarily used as hotspots for analytic services. But in their quest to deliver more value-added services to the parent organization, many are accelerating their ability to serve as strategic innovation partners by significantly expanding their portfolio of digital-focused activity. In fact, our most recent Market VistaTM report showed that digital activity in new setups and expansions jumped 900 basis points between Q4 2016 and Q4 2017.

Automation GIC blog_1

Like most organizations dipping their toe into the digital pool for the first time, GICs initially focused on automating processes through technologies such as Robotic Process Automation (RPA). However, in last couple of years, they have also started leveraging Artificial Intelligence (AI) to improve in areas such as customer experience, operational efficiency, risk management, and development of digital products and services for the market. After realizing the benefits of RPA and AI, some of the mature GICs are also now testing the waters for cognitive computing.

Here is a sampling of the digital use cases coming out of today’s GICs:

Automation GIC blog_2

Of course, changes and challenges abound in the rapidly evolving digital environment. Here are several that will impact GICs in 2018.

  • War for talent: Although they’re upskilling/reskilling their existing workforce, GICs will still need external talent for critical skills such as intuition and innovation, design thinking, pattern recognition, leadership, and problem solving. They’ll struggle to find this talent due to demand-supply imbalances.
  • Ecosystem partnerships: We expect GICs to accelerate their technology adoption through increased partnerships with service providers, technology vendors, start-ups, and educational institutions to deliver new forms of value, such as innovation, automation, and speed to market.
  • Delivery locations beyond India: While India will remain a favored location for enterprises to introduce new technologies, our GIC market activity tracking (see our recently released Market VistaTM report) suggests that other locations such as Brazil, Ireland, Israel, Romania, and Singapore may gain traction in near future. Israel is already progressing to support a range of digital functions such as IoT, AI, and data analytics for customer experience and cybersecurity services.

There’s no question that GICs have the ability to drive the digital agenda for their enterprises. To gain a deep-dive understanding of how they’re doing so today, and what they plan to do in the near future, Everest Group is conducting an online survey. This first-ever assessment will be based on our proprietary Pinnacle ModelTM, which identifies what the best performers are doing to achieve strategic business objectives and deliver increased value. We invite you to participate in this survey.

RPA in financial services – steady progress, more to do | In the News

By | In The News

Following my initial review of how financial services firms are getting on with artificial intelligence (AI), I was interested in finding out more about adoption of AI and related technologies such as RPA and the technical challenges companies currently face, as well as near-future evolution at sector organizations.

According to the study Digital Pinnacle Enterprises by analyst firm Everest Group, of the 55 financial services organizations polled, 16% adopted AI most effectively while 89% of those had already invested in AI in some form or other.

The most common AI uses in the sector were for sentiment analysis for marketing, personal finance virtual agents and financial and advisory virtual agents. Another Everest study of 12 property and casualty insurance companies last year showed that 29% were running AI pilots and 50% were seriously considering it.

RPA is much more pervasive than AI in the sector: Everest data shows that banks and financial firms account for 40% of the RPA independent software vendor market. In the insurance study, 93% of the sample had already deployed RPA – by comparison, some 29% had implemented AI. There is a number of ways in which RPA can support automation in financial services, according to Sarah Burnett, research vice president at Everest Group.

Read more in Diginomica

Video: The Truth about Enterprise RPA Adoption | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

Chief Research Guru Michel Janssen shares three sneak peeks from the forthcoming report: Enterprise RPA Adoption | Pinnacle Model™ Assessment for 2018.  The full report – featuring survey results from several enterprises adopting RPA – will be released soon and will challenge multiple assumptions and myths circulating around the industry today.

After surveying enterprises about RPA adoption across a wide swath of industries, we have finalized the analysis and are about to release a goldmine of data. The new research is full of insights for enterprises looking to take a confident step forward in their journey toward Pinnacle RPA status. In this video, Chief Research Guru Michel Janssen shares three sneak peeks from the forthcoming report: Enterprise RPA Adoption | Pinnacle Model™ Assessment for 2018.

After surveying enterprises about RPA adoption across a wide swath of industries, we have finalized the analysis and are about to release a goldmine of data. The new research is full of insights for enterprises looking to take a confident step forward in their journey toward Pinnacle RPA status. In this video, Chief Research Guru Michel Janssen shares three sneak peeks from the forthcoming report: Enterprise RPA Adoption | Pinnacle Model™ Assessment for 2018.

After surveying enterprises about RPA adoption across a wide swath of industries, we have finalized the analysis and are about to release a goldmine of data. The new research is full of insights for enterprises looking to take a confident step forward in their journey toward Pinnacle RPA status. In this video, Chief Research Guru Michel Janssen shares three sneak peeks from the forthcoming report: Enterprise RPA Adoption | Pinnacle Model™ Assessment for 2018.

Salesforce Acquires MuleSoft Proving APIs Hold the Key to the Digital Enterprise Kingdom | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

In a major statement that reaffirms its vision of becoming the backbone of the modern digital enterprise, Salesforce acquired MuleSoft, a leading application network platform, for a hefty US$6.5 billion. This is the software giant’s largest ever acquisition.

Strategic Intent Behind the Deal

It is evident that MuleSoft will complement Salesforce’s PaaS agenda, per Salesforce’s statement that it will leverage MuleSoft to create the “Salesforce Integration Cloud.” MuleSoft’s AnyPoint Platform, which connects different cloud applications via APIs, is a good fit with Salesforce’s platform offerings.

In addition to strengthening Salesforce’s PaaS portfolio, the acquisition will enable the combined entity to:

  • Enhance its value proposition: Drive a more compelling digital transformation story across enterprises around personalized customer experiences, a single platform for a 360˚ enterprise view, and an enhanced industry-specific suite of solutions
  • Derive synergies from focus on the API economy: Aid enterprises’ need for faster time-to-value by enabling ease of data access across cloud and legacy systems, as well as enhance revenue by cross-selling / bundling across MuleSoft’s 1,200+ customers

Gain a stronger competitive foothold: Salesforce has been competing with Oracle and Microsoft in the CRM space. With players such as ServiceNow and Workday pivoting towards platform services, this deal enhances Salesforce’s platform play.

Crunching the Numbers

Salesforce CEO Marc Benioff has been chasing hyper-growth, with ambitions to nearly double the company’s current revenue to US$20 billion by 2022. While Salesforce’s growth has been relatively muted growth recently (~25%), he application network platform business grew by an impressive 37 percent YoY in Salesforce’s Q418. This presents a strong opportunity for Salesforce to enhance its PaaS portfolio, beyond the headway it’s been making in infusing AI and IoT capabilities across its platform to deliver a more personalized experience for customers.

SFDC blog

Naturally, the next smart move for Salesforce would be building or acquiring a strong API integration engine that helps it access and connect data across enterprises, regardless of its location. Evaluating its acquisition chronology, it was time for Salesforce to start owning the integration experience as well, while also trying to stitch together an integration cloud and potential iPaaS offering. The acquisition of MuleSoft gives it just that, with the added advantage of ensuring a faster time to market and a broader customer base. Additionally, MuleSoft was growing at a fast clip, clocking revenue of US$297 million for FY2017, 58% YoY growth, with guidance of US$405-415 for FY2018 (with an aim to reach US1 billion in revenue by 2021).

The growth story notwithstanding, Salesforce is paying a premium for MuleSoft, with an enterprise value to sales multiple over 20x, which is a reasonably high compared to typical deals in the segment. Salesforce is not alone to tap into the API ecosystem. Google acquired Apigee in 2016 for US$625 million, while Red Hat acquired 3Scale in 2016.

You Can’t Just Patch-fix in the Digital Era

This interest in tapping into the API and integration economy is not accidental. Enterprises have realized that they cannot move the needle meaningfully when it comes to digital transformation if they don’t get their technology estate in order. As we’ve opined before, creating the next breakthroughs in digital requires collapsing the stack to eliminate friction across the value chain. Digital needs to be enabled through convergence of emerging technology themes to drive efficiencies across back-office and core mid-office business processes and enhance competitive advantage by impacting market-facing front-office processes. To do this, it is not enough to invest in a solitary mobile app for customers or an internal gamification initiative, it requires efficient plumbing (e.g. DW/BI, creating data lakes, etc.) as a precursor to meaningful digital transformation. Our recent enterprise research also indicates that front office digitalization or Digital for Growth (DfG) is just the tip of the proverbial iceberg (less than a fourth of the spend), while a significant share is focused on the nuts and bolts (Digital for Efficiency / DfE and Digital enablement).

SFDC-DfG blog

A Word of Caution for Ecosystem Stakeholders

Although there is a general optimism around the business value of the acquisition, the stakeholders need to be wary of some of the potential roadblocks that will emerge:

  • Enterprises: With Salesforce aiming to be their digital transformation partner, the threat of lock-in becomes stronger and their bargaining power dynamics change
  • Competitors: The deal allows Salesforce to look beyond the CRM landscape and aid the digital transformation push, increasing competition with Microsoft, Oracle, ServiceNow, etc. MuleSoft’s peers, such as Sensedia and WSO2,will also be looking to compete with the might of the merged entity and evaluate their strategic growth options
  • Salesforce-MuleSoft: Managing enterprise lock-in concerns, anti-incumbency, and talent integration will be crucial to unlocking significant value through this ambitious deal. Also, integration in the modern enterprise, while a fundamental success requirement, is often riddled with tricky organizational inertia, data silos, fragmented systems, and change resistance

The Way Forward

The size and intent of the deal has certainly piqued the market’s interest. With the aggressive stance Salesforce is taking to expand its PaaS portfolio while playing the customer experience card, it wouldn’t be surprising if we see it forging more acquisitions and/or partnerships, including other companies in the API economy. Enterprises will need to keenly evaluate this landscape to choose the right partner in their digital transformation journey.

What is your take on the Salesforce-MuleSoft deal? We would love to hear from you at [email protected] and [email protected].

Six RPA Implementation Pitfalls GICs Must Avoid | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

Enterprises are increasingly leveraging their Global In-house Centers (GICs) to drive automation efforts across the globe. Per recent interactions with over 100 enterprises, GICs, and technology vendors to develop our new report, “RPA Implementation in GICs – Learnings and Best Practices,” we determined that more than 50 percent of enterprises are already driving or plan to drive their global RPA initiatives from Centers of Excellence in offshore/nearshore GICs.

While GICs are well positioned to drive RPA, the extent of success varies and the journey is not easy. To succeed, GICs need to avoid the following six pitfalls, and follow the lead of best-in-class GIC adopters of RPA.

Driving RPA without Enterprise Support

Successful RPA initiatives are a result of strong collaboration between enterprise and GIC leadership. Best-in-class GICs involve enterprise leadership from the beginning of their RPA journey.

Driving RPA in Functional Silos

Successful RPA initiatives involve stakeholders from relevant functions – e.g., IT, operations, risk, and legal – not just the operations team (recipients of automation solutions.) RPA initiatives in some organizations reside under the strategy and innovation function, rather than being led by IT or operations.

Driving RPA in a Decentralized Manner

Through centralized efforts, GICs are able to document and share knowledge across the enterprise, thereby, reducing cost, effort, and time to implementation.

Relying Excessively on Third-Party Vendors

Best-in-class adopters have a strong emphasis on developing in-house capabilities, for example, product development / customizing RPA solutions to suit process requirements.

Selecting Complex Processes at the Start

Successful GICs have avoided the temptation to automate high complexity processes or explore end-to-end automation, and instead have focused on transactional/repetitive/rule-based processes that are easier to implement.

Viewing RPA as a Silver Bullet

Successful GICs view RPA as one of the tools to improve operations by way of error reduction, productivity enhancement, and SLA compliance improvement. Process standardization and reengineering both play key roles in driving the effectiveness of RPA solutions.

Best-in-class GICs have evolved from execution to enabling business units across multiple locations to implement RPA solutions independently. To learn more about the best practices employed by mature GIC adopters of RPA, read our report, “RPA Implementation in GICs – Learnings and Best Practices.” And if you are driving RPA from your GIC, we’d love to hear your story. Feel free to share your opinions and stories on how your GIC is evolving in its RPA journey with [email protected] or [email protected].

Also, keep a lookout for our upcoming report on Enterprise RPA adoption, which leverages our robust Pinnacle Model™ methodology to compare enterprise performance on RPA adoption.

Finally, we’re in the process of conducting a first-of-its-kind survey, the results of which will reveal the state of digital adoption and what separates Pinnacle GICs™ from others. We invite you to join your peers and participate in this survey, today!

Top 5 RPA Myths Dispelled: Insights from our RPA Pinnacle Model™ Analysis — On-Demand | Webinar

By | Webinars

Thursday, April 12, 2018 | 9 a.m. CDT, 10 a.m. EDT, 3 p.m. BST, 7:30 p.m. IST

Download Presentation Slides and View On-Demand Recording

Robotic Process Automation (RPA) is all the rage these days; however, while adoption continues to accelerate, myths persist.

In this fact-based webinar, we’ll dispel the five most common myths based on our recent in-depth research into the practices of the Pinnacle (or best performing) Enterprises™.

In this insightful 60-minute session, we will uncover the truth behind these myths and reveal how the best performing organizations are realizing a 50% improvement in operational metrics through RPA implementation, and 30% cost savings on RPA investments.

In this session, you will learn:

  • What differentiates RPA Pinnacle Enterprises™ from their peers
  • The implications for RPA adoption in your enterprise
  • How to begin the journey to drive RPA adoption within your organization

Who should attend?
Enterprises: CIOs, CTOs, CEOs, CDOs, CMOs, and other senior executives leading RPA/automation programs

Presenters

  • Michel Janssen, Chief Research Guru, Everest Group
  • Sakshi Garg, Practice Director, Global Sourcing, Everest Group

Moderator

  • Alan Wolfe, Senior Vice President, Everest Group

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