Blue Prism & Google talk about Intelligent Automation and AI

Google’s look into the “next big thing” and the future of AI with Shail Khiyara, Chief Marketing & Experience Officer, Blue Prism, Naresh Venkat, Head of AI partnerships, Google Cloud and David Moss, CTO & Co-founder, Blue Prism.

Source: Prism & Google talk about Intelligent Automation and AI


Magic Quadrant for Workforce Engagement Management


Having truly engaged contact center employees presents an opportunity for differentiation and risk mitigation, and requires adjusting the mindset and technologies to manage agents’ day-to-day roles. This vendor evaluation will help application leaders committed to this change make the right choice.

Market Definition/Description

Workforce engagement management (WEM) solutions expand on the already mature workforce optimization (WFO) market by also accommodating technologies that help drive employee engagement within the customer engagement center.

WFO is an established multibillion dollar software market. Its emphasis during the past decade has primarily been to help improve the operational performance of the contact center. Key functional domains facilitate the recording and assessment of employee performance, combined with the ability to forecast and schedule staffing levels to ensure that operational service-level targets are met. Its core value proposition arises from the tight integration and workflow across these various functional domains (see “The Top 10 Cross-Function Workforce Optimization Processes” ).

This need to be operationally “well run” is still an important consideration and is at the heart of a WEM solution. But various key market shifts have occurred since the inception of WFO that now need to be factored in. Each of these factors requires much more emphasis to be placed on the employee (see “The Essential Shift From Workforce Optimization to Workforce Engagement Management” ).

Key areas of WEM functionality include:

  • Recruitment and onboarding
  • Evaluation and improvement
  • Time management
  • Assistance and task management
  • Metrics and recognition
  • The voice of the employee (VoE)

In addition to the vendors that provide a suite of functions eligible for analysis in this Magic Quadrant, there are vendors that are active in each of the individual submarkets, such as WFM or performance management (see “The Gartner CRM Vendor Guide, 2017” ).

Magic Quadrant

Figure 1. Magic Quadrant for Workforce Engagement Management

Source: Gartner

Vendor Strengths and Cautions


Aspect, based in the U.S., is a privately held company focusing on communications infrastructure and complementary WFO/WEM capabilities (it was included in the 2017 Magic Quadrant for contact center infrastructure). Gartner estimates that Aspect generated $110 million in revenue from WEM in 2017, reflecting a similar number to 2016. This can be partly attributed to an increase in the percentage of cloud bookings. Aspect is embracing the complementary aspects of WEM, and offers several capabilities. One example is the Aspect Mila natural-language interface, which allows agents to ask for information (such as the start time of their next shift) or to make requests (for example, a shift swap or vacation booking) by speaking/typing into their phone. Aspect is positioned as a Niche Player.

  • WEM commitment: Aspect is committed to balancing the needs of the enterprise with the agent and the customer. Beyond the traditional WFO features that help drive operational performance, the company also offers engagement-centric features such as mobile support, gamification, real-time assistance, a natural-language interface (Mila) and RPA. Aspect is aligning its R&D to what it feels are the expectations of next-generation agents (such as “know me” and “fit into my life”).
  • Workforce management: Aspect’s WFM and performance management offerings within its overall WEM suite continue to be market-leading products.
  • Cloud focus: Aspect continues to grow its cloud revenue business, which now accounts for approximately two-thirds of its WEM revenue.
  • WEM functionality: Aspect has some limitations in its engagement capabilities, such as functional limitations in the ability to push work tasks to remote agents on a mobile device, and limitations in interaction assistance and personalization capabilities.
  • Solution maturity: Aspect is currently still migrating some role-based functionality across to its newer user experience platform. This migration is complete for agents and supervisors, but power users/administrative roles still require access to the (somewhat dated) previous UI.
  • Go-to-market: Although Aspect regularly sells its WFM solution to non-Aspect CCI environments, WFO/WEM suite deals are primarily sold as extensions to new or existing Aspect CCI customers. In addition, the sales organization’s emphasis continues to be on selling WFO as opposed to the benefits of WEM.


Calabrio is a privately held U.S. company owned by private equity firm KKR. We estimate that Calabrio’s WEM revenue for 2017 was approximately $115 million, up 15% over 2016, and we expect this momentum to continue in 2018. Calabrio is a growing force in the WEM market. It has a strong vision for WEM and is rapidly evolving its existing leading WFO solution to better accommodate agent engagement. Calabrio focuses on providing a unified suite of functionality delivered through a single UI. Its commitment to the experience it provides customers has helped differentiate it from some of its larger competitors. Its solution provides solid capabilities across the main building blocks of WFO, but does have some omissions in terms of the broader WEM market. However, the vendor’s vision aligns well with WEM, and its R&D program is moving it toward a future leadership position, in Gartner’s view. Calabrio is positioned as a Visionary.

  • Integrated WEM suite: Calabrio offers a unified WEM solution accessed through an easy-to-use, role-based UI. All core WFO functions are supported, but Calabrio has enhanced each one with a view to elevate employee engagement and not just drive operational performance. These include the introduction of dynamic scheduling to the WFM function, allowing agents to see what skills are needed when and to sign up for associated shifts.
  • Deployment flexibility: The WEM suite is available either on-premises or via the company’s multitenant cloud platform, which is built on the Amazon Web Services (AWS) architecture. Calabrio has also partnered with multiple CCaaS vendors, including Amazon Connect, Five9, BroadSoft and Serenova.
  • Customer-focused: Being customer-focused is one of Calabrio’s four foundational business mandates. Reference customers scored it the highest of any vendor in this Magic Quadrant in terms of its ability to understand customers’ needs and the overall experience provided, from implementation to ongoing support.
  • Global execution: Although Calabrio is gradually expanding internationally, approximately three-quarters of its installed base are in North America and less than 10% of its customers are in Europe. This is reflected in the limited number of languages it supports and the limited awareness of Calabrio outside of North America.
  • WEM functionality: Calabrio currently lacks some best-of-breed employee engagement capabilities that are not needed for WFO — but are key parts of a WEM suite. Examples include agent guidance and automation tools, cross-function agent mobility, and VoE.
  • Sales execution: Calabrio’s sales model is still primarily indirect (25% came from direct sales in 2017) and, although its platform is technically ACD-agnostic, the company relies mainly on partners that focus on Cisco and Avaya environments. Of Calabrio’s approximately 160 reseller partners, over 140 of them focus on the Cisco environment.


Genesys is a privately held CCI software vendor based in the U.S., with offices and partners across the world. Gartner estimates that the company generated more than $1.3 billion in 2017, up from more than $900 million in 2016 (although 2017 revenue reflects the acquisition of Interactive Intelligence on 1 December 2016 for its SMB-oriented CCaaS and WFO solution). Gartner estimates that $150 million of the 2017 revenue came from its various WEM product lines. Genesys provides a comprehensive WFO solution. Its WEM vision is centered on providing agents with a flexible and unified working environment that is driven by embedded analytics, to ensure the right skills, motivation and knowledge are available for each interaction. AI-powered predictive WFM and further-integrated agent workspace features planned for 2018 demonstrate a continued focus on improving its WEM viability. Genesys is positioned as a Niche Player.

  • Unified desktop and mobile: The Genesys Workspace portal provides a single UI for employees for all day-to-day activities, allowing them to engage with customers, be assigned tasks, receive relevant knowledge and view WEM information. Genesys has released an updated interface providing full WFM capabilities from mobile devices.
  • Skills management: Genesys’ solution provides agents with insight into their knowledge profile and helps them identify outstanding training/learning. Skills can be assessed and the scheduling of relevant training can be automated. Employee assistance is also available in the form of “knowledge nudges” and e-learning to keep them up to date on new/special offers, unplanned events or current trends.
  • WFO underpinning: Genesys’ WEM vision is built on an established multichannel WFO platform with strong core features across its WFM and analytics-driven Quality Management (QM) modules. The solution has gained momentum in the market, both on-premises and in the cloud.
  • Engagement features: Much of Genesys’ suite has yet to be optimized from an employee engagement perspective. WEM doesn’t seem to be a driver in any customer reference beyond WFM shift visibility. The WFM, QM and coaching tools need to be more flexible and self-service-oriented, and the mobile application lacks functionality. Various partners are needed to provide features such as gamification and real-time communication for mobile schedule interaction. More out-of-the box employee personalization functionality is needed.
  • Go-to-market: The Genesys WEM suite is intended to run only with the associated Genesys CCI platform both on-premises and in the cloud, limiting its addressable market. It is increasingly difficult for customers to benefit from interoperability with third-party systems due to the associated cost and integration complexity. Procurement is complicated by Genesys having three CCaaS platforms for different profiles of organization, each with associated WEM capabilities. R&D is committed to improving and sharing functionality across these offerings, but maintaining all three is not optimal and their individual long-term future is questionable.
  • Market execution: Most customers are running only QM or WFM. Genesys reference customers scored value for money the lowest of any qualifying vendor and also cited the longest average deployment time — over six months. They perceived the solution to be complex to install and run, and having a high TCO. The sales organization is not yet positioning WEM over WFO, so customers are not yet buying it.


NICE is a large global company that we estimate generated revenue of approximately $1.3 billion in 2017, up over 20% on 2016, of which more than half came from WEM. NICE has a sophisticated WEM portfolio from which an increasing percentage of customers are purchasing more than one domain — WFM, recording/QM or performance management. NICE has cemented its move to the cloud with the launch of an integrated cloud platform that supports both its CCaaS (acquired from inContact) and newly developed WEM offerings. Some strengthening of the cloud-based WEM offering is required, but the gulf between the existing on-premises/hosted version and the more modern SaaS-based iteration will diminish through 2018. NICE is positioned as a Leader.

  • Personalized approach: NICE differentiates by wrapping traditional WFO functions around individual employee personas — a powerful approach to driving employee engagement (although adoption has yet to accelerate). Scheduling, evaluations, training, performance goals and incentives are all driven by three key facets that make up each persona: metrics (e.g., adherence, fist-call resolution), attributes (e.g., knowledge, personality) and preferences (e.g., career aspirations, desire to work at home, mornings or afternoons).
  • Advanced analytics: NICE’s strong analytic portfolio helps drive its WEM vision by providing key insights from a range of sources. In addition to operational goals, it also drives employee engagement. For example, speech analytics uncovers employees’ moods and perspectives, and desktop analytics gives a perspective on their tasks and day-to-day experience — both can then be used to assist with interactions, and automation tools can remove repetitive tasks.
  • Broad suite: NICE’s suite has leading capabilities across all main traditional WFO functions as well as complementary engagement-focused features, such as VoE, gamification, interaction assistance and robotic process automation. The recent acquisition of WorkFlex Solutions adds an intraday management capability with strong agent communication functionality, helping agents keep in the loop with ad hoc things such as urgent overtime requests.
  • Solution adoption and value: Customers predominantly view NICE as a leading WFO solution provider, and struggle to articulate how it drives engagement beyond its basic aspects (e.g., providing centralized performance data, flexible scheduling options). Customers are struggling to capitalize on the product’s depth and breadth of functionality, for which they have paid a premium, and consequently question the solution’s value for money.
  • Customer support: Although NICE continues to evolve its support organization, Tier 1 support needs further improvement, as cited by its reference customers. Customers have also cited challenges with the current setup and claimed that NICE representatives lack knowledge and do little more than triage their issues. Tier 2 support is required more often than it should, which adds time and frustration.
  • WEM technology consolidation: NICE has several platforms that each provide some form of WFO/WEM capability: a SaaS platform for CCaaS and WEM, an on-premises/hosted WFO solution, and various acquired solutions. The SaaS platform’s multitenant WEM functionality lacks sophistication versus the on-premises version — customers with complex needs that want to align their CCaaS and WEM portfolio would need to integrate a hosted version of the older platform for the time being.


OpenText is a large, Canadian, global provider of enterprise information management solutions. It entered the WFO/WEM market following the acquisition of various contact center technologies from HP Inc. in 2016. OpenText generated approximately $2 billion in revenue in 2017, of which Gartner estimates $40 million came from WFO/WEM functions. Brand awareness around these acquired products is still low, despite the underpinning platform once being a leading QM and recording offering. OpenText is doing much to address this, including forging new cloud partnerships such as with Amazon Connect to extend visibility. Significant development is needed to elevate its current offering to that of a leading WEM provider, but there are signs of this commitment. The main weakness for OpenText is its OEM reliance for WFM, which is a key building block of WEM. OpenText is positioned as a Niche Player.

  • Evaluation and coaching: Based on the acquired Qfiniti platform, OpenText has a proven, scalable offering to help record, evaluate and analyze agent interactions. It helps elevate existing coaching programs with intelligent scorecards, automated scoring and coaching tips. In 2018, the company will add AI capabilities, allowing for a more intelligent and personalized approach to catering for individual employee needs and preferences.
  • OpenText portfolio: OpenText has a broad portfolio of solutions spanning various information management domains. Several of these, such as process guidance and desktop unification, will be applicable to WEM. Alignment of these solutions with its WEM offering would help accelerate the evolution and viability of the current solution.
  • Customer relationships: Reference customers and client calls throughout the year all cited having a good working relationship, with strong communication from OpenText. Support is often called out as an area that customers are particularly pleased with.
  • Solution maturity: Given OpenText is catching up with more-mature peers, it understandably still positions the solution primarily as a WFO platform. Refinement of existing WFO capabilities and overlay of various engagement-oriented functionality have yet to occur. A lack of investment in the core offering over the past few years requires OpenText to balance its R&D across existing core WFO functions while innovating around WEM.
  • Brand awareness: The core platform has struggled to blossom ever since the original owner was acquired by Autonomy a decade ago. OpenText’s commitment to the WFO/WEM product line is encouraging, but brand awareness is still very low.
  • WFM OEM reliance: Given WFM is a core part of WEM, OpenText’s reliance on an OEM (WFMSG or Teleopti) for core WFM functionality compromises solution development, cross-domain workflow and the user experience. These OEMs have similar relationships with other vendors, diluting commitment and raising potential acquisition concerns.


Verint is a large, established, U.S.-based global provider of customer engagement (which includes CEC and WEM) and security software. We estimate that it generated approximately $1 billion in revenue in 2017, the same as in 2016. Approximately two-thirds of the revenue came from customer engagement functionality. Verint offers a unified WFO solution deployed by thousands of organizations around the world. The company has market-leading capabilities across most domains, including interaction analytics, but its main advantage is seamless integration of, and seamless workflow across, the various functions. This provides an ideal platform to build on and embrace WEM — which is now, importantly, also available as a multitenant SaaS model through Verint’s own data centers and its partner network. Verint’s vision is aligned well with WEM, and the company already has a range of complementary technologies that can help drive employee engagement, including some CEC capabilities not available from other WEM vendors. Additional development is needed to fully embrace employee engagement as an “overlay” to WFO. Verint is positioned as a Leader.

  • Unified WFO suite: Verint provides a unified, workflow-driven suite spanning all core traditional functions, and with best-of-breed capabilities across many domains. The company has a large number of strong partnerships, including several CCaaS vendors, which all leverage Verint’s suite of solutions.
  • Engagement capabilities: Verint provides various features beyond that of a traditional WFO suite, which help cement its position as a leading WEM vendor. A few key examples include gamification, mobile support, process automation and guidance, workflow, and VoE. Verint also has a frontline agent customer steering council to provide direct input into future WEM-related product design.
  • CRM alignment: Verint is unique in that it can leverage functions from its complementary CRM portfolio, such as knowledge management and community, to further drive employee engagement — although we have yet to see much adoption of these. Acquired from Kana, the knowledge management capability allows the WEM solution to create “knowledge assets” based on speech analytics, QM and other relevant insights. These assets can be delivered to employees as needed in interactions — either manually or as determined by desktop analytics and/or real-time speech analytics. Acquired from Telligent, the community solution helps facilitate real-time peer-to-peer requests for shared insights, support and ongoing mentoring roles.
  • Engagement capabilities: Verint has been refining its existing WFO capabilities to make them more engagement-oriented, such as adding flexibility to the WFM tool. However, further modifications are needed to help personalize aspects of employees’ work life based on their individual preferences and personality traits.
  • Organizational needs: Customers sometimes claim to be overwhelmed by options, given the product is so broad and sophisticated. Verint needs to assign more resources upfront to better scope projects. Multiple reference customers cited their desire for more time during implementation to focus on the associated change management and training needs required to fully leverage the offering. Verint is addressing this with a new business advisory services offering.
  • Portfolio complexity and execution: Verint continues to acquire vendors to strengthen its go-to-market offerings (most recently OpinionLab, eg solutions and Next IT), but this adds complexity to the portfolio and in some cases increases the company’s overall debt. Further, despite this broadening portfolio and associated increase in revenue from its customer engagement business, revenue for Verint overall remains flat.


ZOOM is a small U.S. contact center WFO software vendor selling exclusively through its global network of partners. Gartner estimates that it generated approximately $40 million in 2017, up 10% over 2016. ZOOM is an established provider of interaction recording and agent evaluation and coaching software. This is its core competency and it has hundreds of customer globally using it in this capacity. ZOOM is passionate about customer satisfaction and views this as its key differentiator in the market. The vendor is proven in the QM space but currently lacks credibility as a WFO vendor. It has yet to fully transition its roadmap and market positioning around WEM. ZOOM is positioned as a Niche Player.

  • Evaluation and coaching: Complemented by its interaction analytics capabilities, ZOOM’s core software is a viable solution to help organizations understand agent performance traits, preferences and personas. It provides personalized guidance to help drive engagement.
  • Cisco relationship: ZOOM has a long-standing relationship with Cisco: ZOOM is a Cisco solution partner, is available on the Cisco Marketplace and is compatible with Cisco’s new collaboration platform, Spark.
  • Customer satisfaction: Despite currently lacking a formal reference program, ZOOM appears to have a high level of customer satisfaction across its customer base. It claims an overall customer NPS score of 86 for the first half of 2017. The customers Gartner have spoken too throughout the year and for this Magic Quadrant have all been complimentary, with ZOOM scoring highly in this area of our reference survey.
  • Solution maturity: ZOOM is still evolving from being a QM vendor to a WFO vendor. Although this provides a good foundation for WEM, the solution currently lacks numerous WEM capabilities. In addition, the underlying architecture has yet to evolve to be fully multitenant. The company’s small stature and limited R&D budget will likely stifle rapid progress.
  • Enterprise viability: ZOOM’s focus is primarily in the midmarket (50 to 500 agents). Although it claims that it can scale higher, this midmarket focus will impact the product and company direction, increasingly reducing its viability for large, complex organizations.
  • Teleopti reliance: Given WFM is a core part of WEM, ZOOM’s current reliance on Teleopti for core WFM functionality compromises solution development, cross-domain workflow and the user experience. ZOOM plans to own its own WFM offering in 2018, but time will be needed for that product to mature.

Vendors Added and Dropped

We review and adjust our inclusion criteria for Magic Quadrants as markets change. As a result of these adjustments, the mix of vendors in any Magic Quadrant may change over time. A vendor’s appearance in a Magic Quadrant one year and not the next does not necessarily indicate that we have changed our opinion of that vendor. It may be a reflection of a change in the market and, therefore, changed evaluation criteria, or of a change of focus by that vendor.


  • OpenText
  • ZOOM


  • Teleopti (did not meet the functional criteria for inclusion)
  • Noble Systems (did not provide sufficient evidence to substantiate its inclusion)

Inclusion and Exclusion Criteria

To be included in this Magic Quadrant, vendors are required to have:

  • A solution that ideally provides both workforce management (WFM) and employee evaluation software as part of an integrated offering. However, if only one of these is provided directly then the other one must be provided via an OEM agreement, not a simple partnership/reseller agreement, and they would need to be able to prove:
    • Seamless integration between the two domains (including, but not limited to, single sign-on)
    • A unified user experience
    • Extensive in-house resources to sell, deploy, configure and support the entire suite
  • A solution that provides two or more of the following functions:
    • Recruitment and onboarding
    • Coaching and e-learning
    • Interaction assistance and task assignment
    • Performance management and gamification
    • Interaction analytics
    • Voice of the employee
  • A degree of integration among these core functional elements, such as a single administration environment and prebuilt workflows.
  • At least $20 million in WEM revenue during the 12 months prior to the start of the process of producing this Magic Quadrant.
  • A strategy and development roadmap for moving beyond the requirements of an operationally focused WFO platform to embrace employee engagement,* with supporting evidence of some existing engagement-focused capabilities.
  • Five new reference customers that have deployed WFM and employee evaluation functionality in an integrated environment during the 12 months prior to the start of the process of producing this Magic Quadrant. All five references need also to be able to demonstrate credentials that helped elevate employee engagement above and beyond that provided by the core WFM and evaluation features.
  • Financial viability — that is, sufficient cash to continue operating at the current burn rate for 12 months.

* Gartner defines an engaged employee as someone who feels that their work matters and is willing to invest discretionary effort.

As previously cited, the requirement to have a robust underpinning WFO platform that can drive operational performance does not go away. Gartner has therefore assessed each solution’s ability to optimally forecast, schedule, evaluate and train agents within an omnichannel customer engagement center. Each vendor’s ability to deal with non-phone-related activities, such as email, chat and social media, was scrutinized, as was its ability to deal with blended environments. In addition, an emphasis on solution integration/unification and supporting embedded analytics has grown in importance, as has the ability to support both on-premises and SaaS-based deployments.

However, with the shift in emphasis from WFO to WEM, we have also explored each vendor’s vision with regard to placing an increased emphasis on the employee. We looked at the associated functionality — both that available now and via the vendor’s roadmap — that will help elevate employee engagement. Specific areas explored include mobility, gamification, interaction assistance tools, user experience, VoE and the ability to personalize all core WFO functions to the needs of an individual employee. As an example of this shift of focus, we looked at WFM not just through the lens of “an operational tool used to drive cost reduction through head count reduction,” but also from the point of view of “a flexible platform designed to allow employees to self-manage their work-life preferences.”

Honorable Mentions

Several other vendors are on the verge of inclusion in this Magic Quadrant, all of which provide WEM suite capabilities either directly or via OEM agreements. Their omission is a result of factors ranging from their revenue to the breadth of their functionality, to simply Gartner not being able to gather sufficient information to position them appropriately. Examples include:

  • Collab
  • dvsAnalytics
  • Globitel
  • OnviSource
  • Monet Software
  • Netcall
  • Pipkins

Evaluation Criteria

Ability to Execute

The WEM software market is only just beginning to merge after a decade of operationally focused WFO platforms. Some vendors have developed in-house solutions built on an established core competence, while others have acquired — or use an OEM to access — the necessary complementary technologies. This creates significant variation in product capabilities, which is reflected in the high weighting for the Product or Service criterion.

  • Product or Service: This criterion assesses the depth and breadth of a vendor’s WEM-related functions, as listed in the Market Definition/Description section. The core (underpinning) operational-focused WFO elements are assessed in addition to the overarching employee engagement features. Additional emphasis is placed on the degree of integration and workflow across these domains, beyond their siloed provision. The architectural underpinning and provision of aspects such as role-based UIs are also evaluated. Credit is given for OEM solutions, but not for reseller partnerships. Support for SaaS is given additional credit, but is not yet deemed essential for leadership.
  • Overall Viability: This criterion assesses a vendor’s ability to ensure the continued viability of its WEM suite by demonstrating that it has a strong product development team to support current and future releases, and a clear product roadmap. This criterion also covers a vendor’s financial health — its size, growth and profitability — with particular emphasis on the financial health of its WEM business (for those whose solutions extend beyond the WEM market). It also looks at aspects such as cash reserves and operational expenditure.
  • Sales Execution/Pricing: This criterion assesses a vendor’s ability to provide global sales and distribution coverage of its WEM suite directly and/or through partnerships. Each vendor must have experience of selling a WEM product to an appropriate buying center. Each must offer consistent and comprehensible pricing models and structures — including contingencies for, for example, failure to perform as contracted, and mergers and acquisitions. Pricing structures that support large enterprises and SMBs, as well as in-house and SaaS-based deployments, are important.
  • Market Responsiveness/Record: This criterion assesses a vendor’s desire to — and its expertise and organizational flexibility in being able to — perceive evolving customer requirements and communicate these insights back to the market, as well as to create future WEM products to meet customers’ changing needs.
  • Marketing Execution: This criterion assesses a vendor’s ability to consistently generate awareness of, and demand for, its WEM solution through marketing programs and press visibility. The clarity, quality and creativity that go into this are just as important as the revenue assigned to generate new sales leads and increase brand awareness. Because some aspects of the value proposition supporting the adoption of WEM solutions are subtle, additional effort is needed compared with more traditional software markets.
  • Customer Experience: This criterion assesses aspects related to ensuring that each customer has ongoing success with its WEM deployment. Aspects considered include a vendor’s global technical support (whether provided directly or via partners), account management, user groups and panels, and customer communities. Each vendor must provide sufficient proof of the ongoing viability and acceptance of its product in the market.
  • Operations: This criterion explores a vendor’s ability to meet its goals and commitments. Factors include the quality of the organizational structure (taking account of skills, experience, programs, systems and other assets) that enables a vendor to operate. This criterion also covers management experience and track record, and depth of staff experience, specifically in the WEM market. Every vendor needs sufficient professional services — whether delivered by in-house staff or third-party business consultants and system integrators — to meet customers’ evolving requirements.
Table 1. Ability to Execute Evaluation CriteriaEvaluation Criteria


Product or Service


Overall Viability


Sales Execution/Pricing


Market Responsiveness/Record


Marketing Execution


Customer Experience




Source: Gartner (February 2018)

Completeness of Vision

Vendors in the customer engagement center WEM software market differ significantly in background and vision. Some view WEM as part of an end-to-end contact center solution that includes other CCI components. Others view it as an enterprisewide solution for optimizing employee performance and engagement. The immaturity of the market, as well as the potential diversity of engagement-focused features that can be added to complement WFO, result in extensive roadmap plans for many vendors. Consequently, we attribute higher weightings to factors such as market understanding, product vision and strategy, as well as WEM-related innovation.

  • Market Understanding: This criterion assesses the degree to which a vendor understands the needs and wants of customer engagement centers and embeds them into its WEM product and service vision. We look for alignment between strategic customer engagement center goals (such as efficiency and revenue growth) and the specific functions and cross-functional capabilities within a vendor’s WEM solution. We still commonly hear of ongoing organizational concerns among clients, such as with ease of use, clarity of pricing, vendor footprint and proof of ROI. We also hear of clients’ desire to develop a relationship with their vendor, rather than just being its customer.
  • Marketing Strategy: This criterion assesses the consistency and clarity of a vendor’s marketing strategy, the degree of differentiation associated with its positioning of WEM products (both internally and externally), and the relationship of these to its overall vision and brand values.
  • Sales Strategy: This criterion assesses a vendor’s approach to selling WFO products directly and through global partnership networks. A diverse range of capabilities, from strategic account management to industry expertise and targeting, are assessed. In an emerging market such as that of WEM software, an awareness of the need for some education of customers about the role and impact of WEM products is crucial.
  • Offering (Product) Strategy: This criterion assesses the strategic direction of a vendor’s WEM product and its R&D roadmap, as well as the impact these will have on customers. We assess factors such as commitment to a single codebase, product usability, support for SaaS, OEM partnerships versus internal development for missing functionality, industry specifications and prebuilt workflows.
  • Business Model: This criterion assesses a vendor’s overall business proposition and its commitment to WEM.
  • Vertical/Industry Strategy: This criterion assesses a vendor’s ability to provide both standard and tailored solutions for specific industries.
  • Innovation: Some technologies, such as WFM technologies in the WEM software market, are mature, so the potential for significant innovation is limited. However, innovation can still be achieved. This criterion assesses, for example, the alignment of these agent-centric technologies so that they act as one solution through unification and embedded workflows. Beyond this, it assesses the significant innovation potential that can be realized by extending support for communications beyond audio calls to, for example, emails, chat sessions and social media dialogues, and by introducing advanced analytics and embracing mobile interfaces tailored to each role.
  • Geographic Strategy: This criterion assesses whether a vendor understands the needs of the three largest markets — Europe, North America and Asia/Pacific — and knows how to build a strategy to focus on aspects of the overall market, whether directly or through partners. It also assesses whether a vendor delivers products and services that are in line with the needs and capabilities of buying centers.
Table 2. Completeness of Vision Evaluation CriteriaEvaluation Criteria


Market Understanding


Marketing Strategy


Sales Strategy


Offering (Product) Strategy


Business Model


Vertical/Industry Strategy




Geographic Strategy


Source: Gartner (February 2018)

Quadrant Descriptions


Leaders provide functionally broad and deep WEM solutions that can be deployed and supported globally. Their software is suitable for enterprises of all sizes and complexity, and they have broad industry coverage. Their revenue is strong and new references are readily available.


Challengers tend to be viable, with good global execution, but they often lack an in-depth understanding of the true business value of WEM beyond a check-box-type provision for each functional domain and a likely historical focus on the operational objectives of a WFO solution. Challengers may lack control over each functional domain and may therefore find fully integrated workflow-driven capabilities more difficult to deliver.


Visionaries deliver innovative and potentially market-changing solutions, but they struggle to meet the needs of all organizations due to geographic limitations, company size constraints and/or specific product omissions.

Niche Players

Niche Players offer solutions that provide functionality associated with WEM, but perhaps as part of a different overall value proposition. They may also lack specific functional domain coverage. Niche Players may offer complete portfolios, but focus on only one size of organization or one region; they may have a limited ability or even desire to extend globally.


Gartner recommends that WEM solutions be considered strategically within customer engagement centers, as they not only help to improve operational performance but also elevate employee engagement. Key market and societal shifts require a repositioning of how organizations manage employee engagement within their contact centers. Organizations need to assess the potential needs, expectations and aspirations of the next generation of employees within their centers. The impact a motivated and engaged employee can have — not just on operational performance, but also on the customer experience — should not be underestimated and should help justify future investment.

It may take several years for an organization to adopt a unified WEM solution, depending on the organization’s current approach to workforce optimization and existing investments, protracted procurement cycles, and vendor maturity. Nonetheless, all customer engagement centers with more than 100 agents should be working toward this ideal.

As the market evolves, it is highly likely that the main providers of WEM software will be CCI vendors, with several appearing in this Magic Quadrant (and many more expected to qualify for inclusion in the coming years). Vendors with market-leading offerings, such as NICE and Verint, will likely remain, albeit with visions that extend beyond WEM in order to ensure their long-term survival.

Market Overview

WEM is a concept that most WFO vendors are only just coming to terms with. The majority of end-user organizations still view investment in these platforms as a means to drive operational performance. As previously stated, this objective will not diminish during future procurement cycles, but it will become a “given.” The benefits of deploying an integrated suite with strong core functionality and cross-functional workflows will not need to be explained, nor will it continue to be a means of differentiation in the long term. Instead, the need to drive employee engagement will become an increasingly important factor and a key means of innovation and differentiation for the vendors in this market during the next few years. Analytics will be at the heart of much of this new functionality.

All vendors have extensive roadmaps to change the nature of their rather cumbersome WFO solutions to become more agile and employee-focused WEM solutions. Some vendors have a head start in this change, but more investment is needed by everyone.

A key aspect overlooked with WFO is the notion of thinking about the employee outside of the office environment. When looking at the world from the point of view of an employee, a myriad of functional opportunities reveal themselves. For example, no vendor has yet considered the ability to support “commute-based coaching” — where an employee can undertake training from their phone or tablet while on the way to work, thereby freeing up their learning break that day for personal time.

A few interesting facts about this market:

  • Adoption of WFO software has increased steadily during the past three years, with more than 2,000 purchases of integrated solutions.
  • Interaction recording will ultimately become a commodity, associated with the CCI and CCaaS markets. What will be differentiated is the way software vendors can leverage these third-party recordings to evaluate employee performance and engagement.
  • Adoption of WEM as a service is not yet mainstream, but is accelerating rapidly. The move of CCI to the cloud is resulting in a WEM technology refresh cycle and the common scenario of attaching WEM functionality to the CCaaS platform investment.
  • Mobile support for agents is increasing, but adoption is low. Most solutions currently lack capabilities beyond the obvious WFM-focused ones, such as the ability to view schedules and make shift change requests.
  • Agent recruitment and onboarding processes have largely been overlooked by WEM vendors, because they are perceived as requiring stand-alone technologies that are linked more closely to the HR domain. However, as WFO has evolved to WEM, there are numerous synergies and best practices that WEM vendors can provide, so this area is likely to see developments and acquisitions.
  • Technologies that help drive engagement through interaction assistance (such as next-best action, process guidance and process automation) are not new, but have previously been niche markets with no obvious overarching “home” because they fall outside the scope of CRM, CCI and WFO. As an important dimension of WEM, we expect various OEM and acquisition announcements from WEM vendors to be made during the coming years.
  • The VoE is seldom acted upon and usually relies on crude and infrequent mechanisms of capture. WEM requires that more-advanced features are available to capture both planned and ad hoc feedback from employees, which, of course, then needs to be listened to and acted upon.

Acronym Key and Glossary Terms

ACD automatic call distribution CCaaS contact center as a service CCI contact center infrastructure QM quality management SMB small or midsize businessTCO total cost of ownership VoE voice of the employee WEM workforce engagement management WFM workforce management WFO workforce optimization


In researching this Magic Quadrant we drew on:

  • Discussions with users of Gartner’s client inquiry service (more than 200 each year on this topic)
  • Face-to-face meetings with Gartner clients
  • Vendors’ responses to detailed questionnaires specific to this Magic Quadrant
  • Interviews with vendors’ reference customers
  • Vendor briefings over a 12-month period
  • Generally available information, news reports, and data from financial and industry publications
  • Knowledge acquired from vendors’ analyst conferences and industry tradeshows
  • Discussions with other Gartner analysts
  • Critiques by Gartner managers and during Gartner peer reviews
  • Vendors’ reviews for factual accuracy

Evaluation Criteria Definitions

Ability to Execute

Product/Service: Core goods and services offered by the vendor for the defined market. This includes current product/service capabilities, quality, feature sets, skills and so on, whether offered natively or through OEM agreements/partnerships as defined in the market definition and detailed in the subcriteria.

Overall Viability: Viability includes an assessment of the overall organization’s financial health, the financial and practical success of the business unit, and the likelihood that the individual business unit will continue investing in the product, will continue offering the product and will advance the state of the art within the organization’s portfolio of products.

Sales Execution/Pricing: The vendor’s capabilities in all presales activities and the structure that supports them. This includes deal management, pricing and negotiation, presales support, and the overall effectiveness of the sales channel.

Market Responsiveness/Record: Ability to respond, change direction, be flexible and achieve competitive success as opportunities develop, competitors act, customer needs evolve and market dynamics change. This criterion also considers the vendor’s history of responsiveness.

Marketing Execution: The clarity, quality, creativity and efficacy of programs designed to deliver the organization’s message to influence the market, promote the brand and business, increase awareness of the products, and establish a positive identification with the product/brand and organization in the minds of buyers. This “mind share” can be driven by a combination of publicity, promotional initiatives, thought leadership, word of mouth and sales activities.

Customer Experience: Relationships, products and services/programs that enable clients to be successful with the products evaluated. Specifically, this includes the ways customers receive technical support or account support. This can also include ancillary tools, customer support programs (and the quality thereof), availability of user groups, service-level agreements and so on.

Operations: The ability of the organization to meet its goals and commitments. Factors include the quality of the organizational structure, including skills, experiences, programs, systems and other vehicles that enable the organization to operate effectively and efficiently on an ongoing basis.

Completeness of Vision

Market Understanding: Ability of the vendor to understand buyers’ wants and needs and to translate those into products and services. Vendors that show the highest degree of vision listen to and understand buyers’ wants and needs, and can shape or enhance those with their added vision.

Marketing Strategy: A clear, differentiated set of messages consistently communicated throughout the organization and externalized through the website, advertising, customer programs and positioning statements.

Sales Strategy: The strategy for selling products that uses the appropriate network of direct and indirect sales, marketing, service, and communication affiliates that extend the scope and depth of market reach, skills, expertise, technologies, services and the customer base.

Offering (Product) Strategy: The vendor’s approach to product development and delivery that emphasizes differentiation, functionality, methodology and feature sets as they map to current and future requirements.

Business Model: The soundness and logic of the vendor’s underlying business proposition.

Vertical/Industry Strategy: The vendor’s strategy to direct resources, skills and offerings to meet the specific needs of individual market segments, including vertical markets.

Innovation: Direct, related, complementary and synergistic layouts of resources, expertise or capital for investment, consolidation, defensive or pre-emptive purposes.

Geographic Strategy: The vendor’s strategy to direct resources, skills and offerings to meet the specific needs of geographies outside the “home” or native geography, either directly or through partners, channels and subsidiaries as appropriate for that geography and market.

Source: Quadrant for Workforce Engagement Management

6 Technology trends for 2018: Innovation focused on your digital journey

1. Re-platforming the enterprise

In 2018, we’ll see an aggressive move to common IT platforms so companies can respond to market changes faster, be more productive and make better-informed decisions. These common platforms are rich in analytics, follow the information flow of the business and are simple enough that users can constantly change the business without writing (much) code. Moreover, they bring an operational and evergreen scale to traditionally bespoke enterprise IT.

These common platforms — from Amazon, Microsoft, Google and others — provide very suitable if not substantially improved replacements for what used to be custom builds.

“This is about the technology you need, not the technology you make,” emphasizes Dan Hushon, CTO of DXC Technology.

Common platforms enable companies to shift their customization efforts from infrastructure to applications and the user experience, which is where the action is.

Another bonus: Moving to common platforms frees up talent and working capital for differentiated services — where differentiation comes from the information you provide in context to customers, partners and employees for new and better outcomes and experiences.

Platforms will provide not only a foundation to improve processes, but also telemetry and insights. For smart adopters, we may see twofold to fivefold business acceleration.

2. The war for digital talent is vigorous and creative

Re-platforming the enterprise portends a major shift in talent, from operating computers to using multiple skills for information integration, analytics and governance.

These digital skills are incredibly scarce and demand is high. Companies will be fighting for people with digital skills to make the transition to common platforms and to drive disruptive change. So how can we get increased scale from a finite talent pool? And how do we maximize the productivity of the talent we already have?

The quick answer? We’ll use common platforms and a concentrated partner strategy to source experienced talent.

In 2018, companies will leverage team-based, distributed workplace platforms that use machine learning, intelligent automation, natural language processing and other technologies to drive productivity.

In addition, expect to see a rise in creative ways to access talent, described in Unleashing Digital Talent for Fun and Profit, by DXC Technology’s Leading Edge Forum:

  • Crowdsourcing — tapping talent outside your company to engage just-in-time talent
  • Bring your own teams (BYOT) — hiring entire teams at once
  • Incubators — creating or sponsoring organizations or spaces that support startups
  • Strategic acquihires — buying entire companies for their talent

Talent will decide who wins and loses in the next decade.

3. Quantified enterprise: Stop guessing and start measuring

Last year we predicted the rise of intelligent machines. We got that right; today business decision makers say artificial intelligence (AI) is pivotal to their organization’s future success. In 2018, companies will harness the “data exhaust” from their digital systems to quantify the business and become even more productive. This quantification will emerge as a primary driver of digital transformation.

Forced to rethink big data, companies will use advanced machine learning to make better decisions with less data. Call it: “The rise of intelligent decision making.”

The best companies are over 40 percent more productive than their peers — leading to operating margins 30 to 50 percent higher. So the potential benefits are huge. When it comes to determining what affects productivity, companies will stop guessing and start measuring. They’ll start shifting from making decisions based mostly on stories and gut feelings, to making decisions based on experiments and measured results.

The first opportunities will be the often-dysfunctional business processes that bring so much friction to productivity and revenue realization.

4. Businesses get stronger through cyber resilience

In the past, companies tried to create perfect security, but today security is viewed not as binary but as a continuum. In 2018, enterprises will focus on getting their resilience as high as possible to withstand attacks and threats. That means planning and practicing for such threats, because they will happen. The common practice will be continuous evaluation and improvement of risk posture.

Added to resiliency is the notion of antifragility, which means getting strongerwhen attacks happen — not just surviving the attack. You get stronger from practicing and responding. You use what you’ve learned to make yourself stronger the next time around.

With the many destabilizers facing enterprises today — cyber attacks, natural disasters, vendor failures, human error, mergers and acquisitions — enterprises must work to become ever-more resilient by applying continuous improvement to productivity, differentiation and the resiliency of the business itself.

5. Companies grow through digital business extensions

The digital core will provide enterprises with an information-rich, scalable foundation. In 2018, companies will grow by leveraging that information and scale, extending their digital capabilities into every facet of the organization — as well as into new markets and new businesses — through digital business extensions.

Amazon’s journey – from online bookseller to online-everything marketplace, to cloud platform, to online- and offline-everything platform, including groceries – is not about a company being irrationally greedy and trying to put a finger in every pie. It is a story of smart digital extensions. In other words, Amazon can run some of those businesses better because of its digital capabilities.

GE’s big plans for the industrial internet of things and its Predix platform can also be seen as a digital business extension.

To make the right digital extensions, companies need a “strategic backflow” from digital capabilities to corporate strategy. This backflow must be embedded in strategic planning rather than based on heroic behaviors, water cooler conversations and special relationships.

That means ensuring that corporate strategy and, ideally, all functional strategies (e.g., marketing, manufacturing, logistics) have mechanisms to consider digital extensions. Ask: “What can I do now?” and “What should I do next?”

Let’s let the digital tail wag the corporate dog, at least a little, in 2018 and beyond.

6. Artificial intelligence gets smarter and more practical

For all of these technology trends, artificial intelligence (AI) will determine the long-term winners and losers. In the past, people were not building AI with the right goals in mind, but that will change in 2018 as companies become more information-driven and use neural networks for continuous learning and productivity.

A big bastion of AI deployment is IoT, because it generates so much information. Other rich areas for AI advances include employee information systems and processes, clinical health advisement systems and IT service management (managing millions of computers is untenable for humans).

Convolutional Neural Networks (CNNs), a class of artificial neural networks, will evolve and trigger an explosion of opportunities:

  • Very Deep CNNs will push computer vision and natural language processing (NLP) to achieve emotional intelligence with end-to-end conversation capabilities.
  • CNNs will open new opportunities in fields such as system-driven drug synthesis models, leading to cost-effective drug discovery.
  • Improvements in NLP will lead to automated content generation.

AI will continue to redefine what is sci-fi and what is reality. AI is here to help people do better. But rest assured, AI will not be self-aware anytime soon.

With the right roadmap and these guideposts, companies can succeed on their digital transformation journeys in 2018 and beyond.

Source: DXC-6 Technology trends for 2018: Innovation focused on your digital journey

An IT automation strategy wilts under cloud’s shadow

Automation of internal processes has led many IT groups to streamline process steps, decrease costs and improve overall business functions. Because of this, a comprehensive IT automation strategy is an easy decision to make for any company looking to not only keep up, but stay ahead of the curve.

Unfortunately, the drive to end-to-end IT infrastructure automation hit a speed bump called the cloud. While the cloud won’t directly replace automation, it does affect what tools and investments an organization makes in its on-site data center. No one will dispute the benefits of an IT automation strategy, but what remains to automate if you move business services to a SaaS or another cloud deployment model?

IT automation trends

It’s critical to invest in data center resources, such as IT infrastructure automation, monitoring or other items, before cloud adoption, but with a cloud strategy, some of those things simply disappear or change into something else. IT infrastructure automation started as simple scripting and gave way to more complex languages and, eventually, workflows and orchestration. The challenge isn’t that the language changed. Organizations removed and relocated apps and infrastructure resources to someone else’s environment.

No cloud environment could exist without some form of automation; self-serviceis a pillar of the cloud. The difference between cloud automation and what’s in the data center is how much of it admins manage. When admins manage IT infrastructure automation on-site, they have complete control, but cloud customers are restricted to what is presented to them. While cloud-based automation and workflows boast some convenient features, it’s doubtful the admin portal will contain everything you had in earlier iterations of the IT environment, and that will take some adjustment.

The change won’t happen overnight

While cloud adoption — in particular SaaS and platform as a service (PaaS) — changes IT operations in many ways, don’t throw out everything that your team currently uses. Configuration management tools, for example, work with on-premises servers and cloud instances, and the major cloud service providers also offer configuration management as a service.

A smart IT automation strategy is still critical to the modern business. Review the many options presented to you as a customer of cloud services. It would be unwise for any cloud vendor to offer complete control of an environment wherein admins could make changes to shared, multi-tenant infrastructure. The move from an IT automation all-star to an automation customer won’t be pretty. No one likes to give up control or flexibility, but it is necessary as part of the move to cloud services.

Cloud and on-premises app deployments coexist in enterprise IT.

IT automation skills

No one likes to give up control or flexibility, but it is necessary to move to cloud services.

The new questions are: How much skill set overlap do admins have from on-site IT infrastructure automation to cloud services? Will the organization end up with an IT infrastructure automation skill surplus as cloud providers take over many tasks? Depending on the skills in an IT organization’s staff, the company might end up paying a lot of money for expertise that the organization no longer needs. Reallocate, or even retrain, the admins that want to learn new skills, such as cloud management; some might not want to. This struggle is not unique when it comes to IT personnel and internal services being replaced by the cloud-based offerings.

Not all automation jobs will disappear. Cloud vendors need IT automation experts now more than ever. But for companies moving to the cloud, internal demand for granular automation knowledge will fade. Infrastructure automation specialists will see a substantial decrease or changeover.

Time to invest in automation resources

Set an IT automation strategy based on a realistic time frame for your organization’s move to the cloud and what kind of cloud service the majority of workloads will go to: infrastructure as a service, PaaS or SaaS. Additionally, determine if an automation setup purchased or improved today could pay for itself before the move to the cloud. If the cloud migration doesn’t go smoothly, delays could make on-premises automation more attractive. These are tough discussions that rarely yield clear answers.


Source: IT automation strategy wilts under cloud’s shadow

Survey says: ERP changes, more human-machine interactions coming by 2030

By 2030, a major portion of ERP-related work may be handled by machines. These systems will increase in capability as the amount of data grows and as AI advances. Human-machine interactions will play a major role in business, and well before then.

The importance of human-machine interactions to business was ranked very high by the respondents participating in research by Dell Technologies and the Institute for the Future. The report is based on a survey of nearly 4,000 business leaders. More than eight in 10 (82%) overwhelmingly agreed that they “expect humans and machines will work as integrated teams within their organization inside of five years.”

Further out, by 2030, smart machines will play an important role in ERP. Three of the top four functions that will be offloaded to machines, this survey found, are ERP-related: inventory management, financial administration — invoicing, purchasing orders, etc. — and, in fourth place, logistics. Troubleshooting was number three.

But overall, there is a lot of uncertainty about the technological future.

When asked if “automated systems will free up our time,” the response was split down the middle, with half agreeing and the other half disagreeing.

The answers also indicate questions about capabilities. For instance, respondents were asked whether “technology will connect the right person to the right task, at the right time.” Only 41% agreed, and the remainder disagreed. Respondents were evenly divided around this statement: “Not sure what the next 10-15 years will look like for our industry, let alone our employees.”

In an interview, Danny Cobb, Dell Technologies corporate fellow and vice president of global technology strategy, discussed human-machine interactions and other survey findings.

Cobb sees a wide range of qualitative and quantitative processes and technologies — AI, context and pattern recognition, voice and image recognition — gaining enterprise use. His responses were excerpted and edited.

In 2030, more and more tasks will be offloaded to machines. Three of the top four are ERP-related: inventory management, financial administration and logistics. What does this mean?

Danny Cobb: It’s hard to imagine that that’s the first thing someone thinks about [inventory management, financial administration] in their digital transformation agenda, but it also paints a picture: We’re not as far along or sophisticated as we may think we are if those are still some of the topics that come up.

Does this mean that things like inventory management will be more automated? That something like image recognition might be used to track product as it moves through the supply chain?

Cobb: That’s right. You see image recognition, drone technology and robotic technology assisting with that function. You see maybe more global logistics functions that might be operating in a hybrid cloud or a multi-cloud way that gives a broader insight into all the inventory and material capability of an enterprise, 24/7 and around the globe.

ERP systems will be handling a lot more data from a much wider range of sources. What do those systems begin to look like in the future?

It may not be strictly a physical presence, a personal robot sitting in that room with me, but artificial intelligence itself will complement the team’s function and will provide a useful value.

Danny CobbCorporate fellow and VP of global technology strategy, Dell Technologies

Cobb: At the edge of an enterprise — the edge being wherever the first unit of intelligence begins to exist — there might be a stream of telemetry. It might be all this inventory data. It might be all the input from these drones, or from a global logistics system, or from multiple systems because of supplier-to-supplier linkages. These systems now need to be much more intricately linked than ever before. There is an opportunity for an entirely new platform to come into existence — the intelligent edge of the enterprise that handles this telemetry, that handles any of the immediate compute or storage needs. It takes that information and shares it appropriately with a core data center that might contain additional intelligence from the rest of the enterprise. The edge technologies do the first stage of work, and then, those migrate upstream to a set of core technologies that are responsible for further analysis, long-term storage or broader distribution.

How much data will we be getting from these alternative sources, and what are the challenges to processing it?

Cobb: Artificial intelligence, machine learning sorts of capabilities are going mainstream because the amount of compute that we have has caught up or is catching up with the amount of useful data that’s there to be analyzed. Other instrumented systems [such as autonomous vehicles, building automation systems, jet engines] are throwing off a tremendous amount of data, and we can now afford to process it as it’s being generated. We can now embed processing in just about anything.

A high percentage of those surveyed for this report expect to see more human-machine interactions by 2030. What does that mean?

Cobb: It may not be strictly a physical presence — a personal robot sitting in that room with me — but artificial intelligence itself will complement the team’s function and will provide a useful value. It’s that sort of digital partnership.

How useful is it to think about the world 15 years or so from today?

Cobb: They [customers, users] need to start getting a blueprint that helps them address some of these opportunities or manage some of these risks. What research like this does is to give customers a vehicle for thinking about this. What are the new roles that are going to be created? What are the skill sets that need to come into existence? How might that impact job satisfaction?

Source: says: ERP changes, more human-machine interactions coming by 2030

The Power of Democratizing Automation


Over the past few years, we’ve heard from numerous pundits who have painted a very dystopian picture on the demise of white-collar jobs at the hands of automation.

It makes for attention grabbing headlines but when you examine the facts, automation is about liberation from the mundane and driving digital transformations in the enterprise. It’s true that some jobs will be eliminated by automation, however we don’t see the new digital worker as a replacement for humans, but as an enabler to become an intrinsic part of the fabric of a future workplace.

In the past couple of months, industry experts have stated that digital workforces will assume responsibility for mostly rote, repetitive, and productivity-busting tasks, not entire jobs. In fact, a recent Everest Group blog said, “the fear about the impact on jobs is way overblown.” It also stated that, “it is highly likely it will impact slices of jobs and/or departments that will allow for those employees to be transitioned to higher-value tasks.

This evolution should encourage enterprise executives to consider technologies like Robotic Processing Automation (RPA), fueled by bots to provide automation for repetitive and rules-based tasks that involve structured data. This, of course, makes sense. Who wouldn’t want more time to make a real difference for their company and their customers?

Collaboration Between Employees and Software Robots

A recently-published KPMG report, “Rise of the Humans 2,” indicates that the concept of humans and robots working together to deliver an outcome is becoming increasingly important. Indeed, when employees and smart, enterprise-grade RPA robots – meaning those that understand context, derive meaning, and anticipate change to deliver better and faster outcomes – work collaboratively, it can make for a very powerful partnership.

The removal of monotonous tasks not only makes for happier employees, but also allows them to take on higher-value roles. Shop Direct, one of U.K.’s largest pure-play digital retailers, for example has fraud advisors handling phone calls from distressed customers identifying and verifying fraudulent and genuine purchasing activity. Needless to say, it’s quite a lengthy process.

The company introduced a blended process with manual interventions, where the customer is still calling in and speaking to a person. The RPA-enabled process, robots take care of all the administrative verification box-ticking and new customer account establishment, significantly accelerating time to solution. And the time saved allows the now upskilled fraud analysts to have a more customer-centric conversation. Shop Direct has been able to return 328,000 hours annually (and rising) back to the business thanks to RPA. It is a win-win situation for both customers and employees.

Working together with IBM we are seeing firsthand the power of automation being made accessible to all. We’re helping joint customers like Walgreens deploytheir strategic digital workforces. As a global Blue Prism partner, IBM offers clients deep expertise and a full range of automation solutions—from infrastructure to applications and business processes, in both on-premise and outsourced implementations—fully supported by IBM services and Watson’s AI capabilities.

The primary goal of truly smart software robots is to deliver a wide range of benefits to the business. These fall into three categories:

1. Driving Top Line Value:

  • Reducing customer churn with faster execution of customer service requests
  • Increasing insights with reporting of process anomalies
  • Achieving faster time to market through automated launch processes.

2. Improving Bottom Line Profit:

  • Reducing “cost to serve” by automating manual processes
  • Lowering operational risk by collecting every nuance of ever process transaction
  • Defending against fraud with real time anomaly reporting, while lowering the cost of compliance.

3. Reducing Risk:

  • Saving and reporting every step that occurs in every process
  • Ensuring adherence to stringent HIPPA requirements.

What we’ve noticed is that the forward thinking, contemporary enterprises are already imagining the digital worker as an augmentation to our human workforce. A new workforce that allows every person to be far more productive, collaborative and supportive to customers by giving them access to an infinite resources of execution 24 hours a day, offering new levels of service.


Source: IBM-The Power of Democratizing Automation 


The principle that technology performs technology jobs and humans perform human jobs is a simple one. Virtual and human workers each have their own strengths that should be employed and valued. The difficulty lies in determining the best fit for each role and responsibility, especially when a lack of standardization is involved.

Robotic process automation (RPA) is large part of future-of-work technology. To use RPA optimally, standardization is required. The fewer steps an automated solution performs, the quicker it will run. Additionally, if a single set of instructions exists, a single solution can be built. If highly variable instances with many different requirements exist, multiple solutions must be designed and built.

What Is a Standardized File?

Most clients understand that having structured data (e.g., a field-based file) that uses a good data type (text and numbers) is vital for RPA. But there’s a common misconception that having the same data on a page, regardless of position or format, is equivalent to standardization. To be fully standardized, the data must appear in exactly the same cell, field or position in every instance.

The same goes for the processes. It isn’t enough that certain actions take place. Every instance of each action must be performed in exactly the same way, in the same order, using the same rules.

What Are the Benefits of Standardization?

The following are some benefits of process standardization.

  • Simple, well-defined standard operating procedures (SOPs). When you’re using highly standardized processes, you can write simple and well-defined SOPs that exclude futile work and bad practices. Employees are less likely to develop individual workarounds. Having clear SOPs is also useful for compliance.
  • Ease of training new employees. Clear and simple rules allow quick and structured training for new employees. They also mean that when associates have learned how to interact with and process one client, they can work with all clients. This benefit is especially useful when work must be transferred from one employee to another for reasons such as annual leave or attrition.
  • Ease of adding new clients. You can take on new clients with ease, as all new clients undergo the same process. In closing the sale, clients will be aware of exactly what input they must deliver and the business can be transparent with them from the start.
  • Increased scope for RPA configuration. Any simplification and process re-engineering that occurs before RPA development will make the deployment faster (meaning the benefits will accrue sooner). The RPA solution won’t need reconfiguration for new clients, and it’s more adaptable for future process developments.

How Can Standardized Processes Help Meet Individual Client Needs?

It’s important to ensure clients feel well served and unique, and some varying requirements between clients will be inevitable. Almost all processes, however, provide opportunities for standardization. For example, legislative parts of processes tend to be common across all clients. If they are standardized and then deemed suitable for RPA, associates will have more time to spend meeting the bespoke requirements of your clients.

For example, in one of Symphony’s completed future-of-work Assessments, a process involved receiving fresh information from the customer each month. The employees would create Excel templates for each customer, but only about 30 percent of the customers submitted their details using the template. Other data arrived in a modified version of the template; a customer-created Excel file; a Word, PDF or alternate application file; or a free-form email that attached a mixture of the above. Not only was the associates’ effort wasted in creating the template, but dealing with the mixed-data input was a difficult and time-consuming task. By analyzing the business case they discovered that if the clients enforced template usage and increased their standardization levels from 0.3 to 0.6 (over all processes) before implementing RPA, their three-year ROI jumped from 300 percent to over 450 percent.

In conclusion, standardized processes should be the same in every instance. The benefits of having standard processes apply to the workflow, the employees, the clients, RPA development and finances. As such, process re-engineering to increase standardization is critical for an organization’s journey into the future of work.

Source: datacenterjournal-THE BEAUTY OF STANDARDIZATION

In The Mind of Algorithms: A Conversation with UiPath’s Machine Learning Team

It’s everywhere. It’s all around you. It’s in your smartphone, in your e-mail, in your Amazon and your Netflix, in your car and in your favorite supermarket. It’s in Google’s CAPTCHA, in the stock market and probably behind the recent presidential vote. It’s in genomic sequencing, in particle physics and astronomy. What is it?

It’s Machine Learning. And it’s changing the world as we know it.

You give me data, I give you (instant) gratification

Here’s a question: why would someone ever want to keep in their house a machine that collects information about them 24/7 for purposes that are arguably beyond their knowledge and control?


It’s a trade. You entrust me with your data, and in return I give you answers to your questions, product recommendations and dating suggestions tailored to your interests, optimized driving routes, spam filters, or a new credit card.


As our digital footprint deepens, most of the data we continuously generate is being collected, processed and transformed into useful products or services. Just as Google’s algorithms determine to a great extent what information you find, Amazon can largely influence what products you buy.


Machine Learning (ML) algorithms have an extraordinary capacity to process vast amounts of data and find patterns in it. And the more data there is, the more they learn. For many applications—from vision to speech to robotics, and in different areas of business—from retail to finance to manufacturing, Machine Learning is becoming the new driving force.


To give you a rough knowledge of this technology, a conceptual model to better navigate the expert field currently taking our own industry, automation, to new heights, today we’ll introduce you to UiPath’s team of Machine Learning developers. Stefan Adam, Virgil Tudor, and Dragos Bobolea are the geeks who are leading the research and development of Machine Learning here at UiPath.

Guys, what is Machine Learning?


Virgil: Machine Learning is a subfield of Artificial Intelligence (AI) that enables systems to learn from data. It has at its core Deep Neural Networks, as does most of the current state of the art AI.


Dragos: Deep Learning—the part of ML that we are using—focuses exclusively on multi-level Neural Networks. Basically it involves a network of information that takes pieces of knowledge, combines them in various ways, and finally builds them up towards sensible, high-level meaning.


In the past, AI was composed of lots of very specific algorithms invented for all sorts of problems, from finding contours in pictures to very specialized things like detecting faces. A big part of the job was engineering all this domain knowledge into the algorithms.


Now, thanks to recent advancements in Neural Networks research and hardware computing power, it became feasible to leave this reverse engineering task to a Neural Network and assist its learning process in various ways. The biggest advantage is that Neural Network training, like pedagogy if you will, is almost universally transferable across domains. For example, teaching maths is not that different from teaching chemistry (same teaching method, different curriculum). Similarly, here at UiPath we can use the same state-of-the-art methods that others use for OCR engines, speech recognition, self-driving cars, etc.


Gartner predicts that Machine Learning will reach mainstream adoption in two to five years from now:


“Machine Learning is one of the hottest concepts in technology at the moment, given its extensive range of effects on business. A sub-branch of Machine Learning, called Deep Learning, which involves Deep Neural Nets, is receiving additional attention because it harnesses cognitive domains that were previously the exclusive territory of humans: image recognition, text understanding and audio recognition.”

So what is currently embedded in our Platform in terms of Machine Learning?


Stefan: So actually in the product we have integrated different OCR components. We are using OpenCV to process images, and we also support text analysis based on Microsoft, Google and IBM components. Our image recognition engine uses powerful algorithms that are optimized to find images on screen in under 100 milliseconds. This makes it possible to automate even the most complex applications, available through Citrix and other virtual environments. In fact, it takes almost the same amount of time to build an integration that involves Citrix as it takes to automate a regular desktop application.

And what are we planning to develop going forward?


Stefan: There are three main directions. The first one is related to the way UiPath interacts with the target application—the application which we are trying to automate.

The current detection engine is based on different Accessible API’s. That’s why our screen scraping engine is strongly connected with the execution environment. We plan to incorporate ML especially Deep Learning in our product such that the system will be able to understand any screen, similar to the way humans can understand it. In this way our core detection engine will become invariant to the execution platform. This will also lead to the ability to continuously train our engine by assisting a human user.

The second direction is to offer more Cognitive activities related to natural language parsing and image processing.

And the third direction is to also offer businesses the possibility to build, train and customize different Machine Learning models for performing different tasks, mainly classification and detection.

So with all these enhancements, automation will gradually come closer to emulating and augmenting the power of the human brain.


Stefan: Yes. It has always been the specialty of humans to read and listen to words or capture images. But with the advent of Machine Learning, Natural Language Processing, Neural Networks, Deep Learning and so forth, being able to read text, understand voice and recognize images is also becoming the domain of machines. And the application of these technologies in business will open up possibilities that were previously unimagined.

One of the first, most effective outcomes of applying Machine Learning to RPA will be a newly gained ability of robots to handle complex processing exceptions autonomously. By learning from historical data, they could predict exceptions and prevent anomalies, eliminating the time, effort and cost needed to handle them. All of this will greatly extend the scope of automation to include many activities that involve human judgement.

Using learning algorithms, an RPA robot could make processing decisions contextually, while considering millions of data points from past experience and delivering more accurate predictions. In a claims processing scenario, for example, the robot would automatically review the claim file, eliminate duplicate entries, assess eligibility and then deliver adjudication decisions with human-level precision.

What sparked your interest for this domain?

“(…)In most of the computer science subfields, a scientist or a programmer without basic AI knowledge will be like a blind painter.”

Virgil: The raw power of Deep Neural Networks, the fact that it employs a lot of math and because it’s a mandatory skill for any future computer scientist. In most of the computer science subfields, a scientist or a programmer without basic AI knowledge will be like a blind painter.


Dragos: I guess the thing that awed me the most was this framework of representing knowledge. As a layman, seemingly trivial concepts like “what is a pen” were very fuzzy and ungraspable when I tried vizualizing them. There’s no obvious way of quantitatively representing a pen, so you could say, “look, this picture’s of a pen because this or that.”


Trying to make sense when your pen is just an array of numbers is even more mind-boggling. You start imagining various rules, that get very complicated very quickly, you get scared and think how could anybody ever do this? But that’s what people actually did for a long time (and are interesting on their own). So naturally, I got very excited at discovering methodical ways that can attack these sorts of problems. Also, it’s amazing that we live in a time when we can put them to good use!

The hottest job in Silicon Valley


According to Tim O’Reilly, data scientist is the sexiest job today. Machine Learning experts are rare, forming an elite category that is frenetically being hunted by the big players the likes of Google, Facebook or Amazon. The McKinsey Global Institute estimates that:


“There will be a shortage of talent necessary for organizations to take advantage of big data. By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.”

They say Machine Learning is the ideal occupation, because learning algorithms do all the work but let you take all the credit. What have you got to say in your defense?

“The whole concept of learning needs a function that will measure how good or bad a prediction is. If you see a cat, it’s wrong to say it’s a dog. It’s very wrong to say it’s a truck.(…)”

Dragos: A 7 year old knows how to read, right? Imagine giving him a full fridge, and a cookbook. His beef wellington will be similar to the results of an off-the-shelf Neural Network that somebody threw data at. There are at least 3 important things that a Machine Learning developer does:


First, he has to know how different algorithms work, and why they work, so that he knows what tool to choose for the job. Second, he has to figure out how to make the best use of domain knowledge, and give possible “shortcuts” to the Neural Net—this can turn potentially unworkable problems feasible, because it heavily trims down the “number” of bad tries. This is both a problem understanding challenge, and also a technical challenge—you have to write good code for it. Third, once all the pieces are in place, you have to attend to the whole training process, because there are many more ways for it to go on a wrong path than not:

  • The whole concept of learning needs a function that will measure how good or bad a prediction is. If you see a cat, it’s wrong to say it’s a dog. It’s very wrong to say it’s a truck. This function—the cost function—turns out to be very hard to design, as it depends very much on the problem at hand (eg. the data distribution).
  • You have to find good learning rates at different stages, so that it doesn’t start out too slow, and so that it can learn fine details later on.
  • Make sure the model does not overfit the learning data, so that it will perform well in real-life situations.
  • Figure out edge cases, adversarial examples, and understand why they occur and how to protect against them.

As a final note, could you share your favorite resource on ML knowledge for all aficionados out there?

Virgil: The book Deep Learning by Ian Goodfellow, white papers from https://arxiv.orgCoursera’s deep learning course, and then the rest of the internet, of course.

Dragos: This is an emerging field, with advancements being made every few weeks. is the website where most of the research is published, and that’s what you’ll usually find the team sipping their coffee over. For maths and other bottom-up knowledge I love OCW and Stanford’s online courses. And of course, like any developer, we all have that Chrome window with 20 tabs of StackOverflow and Github threads.

Source: The Mind of Algorithms: A Conversation with UiPath’s Machine Learning Team