Machine Learning: Internal to Customer-facing

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Machine Learning: Companies

Consulting and advisory firms Deloitte and Gartner are leveraging transformational leadership and IT-based strategies such as digital automation and cloud sourcing from inward-facing to customer-facing machine learning technology. Russell Reynolds Associates have a product for client transition strategy that utilizes artificial intelligence and Microsoft Hybrid Cloud to provide data solutions as well as facilitate communications between clients and leaders.


  • Deloitte, founded in 1907, serves approximately 245,000 clients in 150 countries and territories through the collaboration of professionals who provide audit, tax, legal, financial advisory, risk advisory, and consulting services.
  • Deloitte is turning towards consumer-facing machine learning to help its clients with digital transformations.
  • Deloitte is transitioning from internal process to digital automated business process that is customer — facing by migrating their applications to the cloud.
  • In an attempt to turn the company into customer-facing machine learning, chief digital officers at Deloitte help their consulting clients with digital transformations by retraining employees and retooling business processes as well as adopting new technologies.
  • The company introduced tools and metrics to precisely measure customer satisfaction in near-real-time and has its HR team to adopt a performance management system to enhance accountability in customer-facing AI and its corporate section.
  • Implementing the right C-suite strategy to facilitate building resources to take risks and aggressively pursue opportunities like ridesharing, automation, and electric capabilities by optimizing machine learning capabilities of the company.
  • Suitable C-Suite leadership enables CEOs to achieve exploration and exploitation within their business units.
  • Implementation of the C-Suite leadership will assist the company to enhance cooperation, avoid unproductive conflict, and encourage constructive discussion of different viewpoints within company employees.


  • Gartner, founded in 1979, is a leading research and advisory company that has expanded its flagship technology research to provide leaders across enterprises with indispensable business insights, advice, and tools needed to achieve their mission-critical priorities in Research & Advisory and Consulting and Conferencing.
  • Gartner leaders are entrusted to provide trusted insights that are forward-thought and oriented, verified peer-driven research, and robust metrics and data to help them make the right decision.
  • Customer-facing machine learning is implemented by the Digital Customer Service team through its I&T Operating Model Patterns, The Gartner Service-Optimizing I&T Operating Model, Outward-Facing, Business-Centric Attributes, Inward-Facing, and IT-Centric Attributes.
  • Transitioning from the Process-Optimizing to the Service-Optimizing I&T Operating Model.
  • Gartner's Digital Customer Service team enhances its customer-facing machine learning by providing their clients with:
    • Personal guidance to help them focus on the sensitive issues and opportunities that matter to their enterprise.
    • Tools and programs to assist them to implement strategies and turn them into executable decisions to get measurable results.
    • The company serves 5,600 organizations in 100+ countries.
    • To transform into customer-facing machine learning, chief digital officers at the company have to transform the company’s technological future to focus on customer satisfaction by changing the supply chain and organizing back end business operations to improve customer experience, generate customer-focused and outbound data solutions whereas aligning them with evolving technologies.
    • Adopting digital technologies to meet pressure and help alleviate pressure from leadership to scale resource accountability.
  • The leaders achieve this by:
    • Gaining control over service websites to integrate, communicate, and harmonize strategies across business functions like IT, finance, HR, marketing, etc.
    • Prioritizing investments in the digital experience over other initiatives.
    • Exploring digital applications to improve operational efficiency in big data and back-office automation and ensuring that their IT team has appropriate digital capabilities to improve operational efficiency.


  • Russell Reynolds Associates is a leading global insight, leadership advisory, and research firm that develops tailored solutions to help build, guide, and grow organizations in complex business environments.
  • The company has over 450 professional consultants across its 46 offices worldwide.
  • Russell Reynolds Associate's transition from inward-facing to customer-facing machine learning was influenced by the urge to understand the future trends and challenges that their clients face by exploring the changing dynamics of the technology solutions industry in the IT hardware and electronics sector in Asia/Pacific and Europe.
  • After a research survey, the company identified limitations in the form of strategic leadership while remaining close to market developments and customer needs.
  • The company identified three elements for the transition as follows:
  • Also, the company's leaders harness artificial intelligence/machine learning to enhance customer experience whereas improving processes as well as creating business models to cope with the complex environment.
  • During the transition, leaders at Russell Reynold Associates are tasked with linking technology and supporting clients through:
  • For instance, Russell Reynolds Associates uses Microsoft hybrid cloud to better meet the needs of customers in a fast-changing digital world.
  • Using Microsoft hybrid cloud enables the company to protect its business and reduce cost, enabling it to increase innovation investments.
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Machine Learning: Trends

Machine learning has long been used to help businesses grapple with vast amounts of internal data. The technology is now being consistently applied to recommendation systems for customers, personalization, and advanced customer segmentation.

Recommendation Systems

  • Machine learning is quickly being adapted from an internalized process toward outward-facing marketing to improve a customer's shopping experience.
  • Companies such as Amazon, Netflix and Spotify have immense stores of data on customers and are at the forefront of using recommendation engines.
  • Currently, these recommendation systems can provide suggestions on products, music, movies, and more. Future possibilities include being able to offer recommendations on what software a user needs to solve a particular problem and even providing managers with suggestions on whom best to delegate work to, along with other outward-facing needs.
  • 35% of Amazon's annual revenue is generated via their personalized recommendation engine.
  • It is estimated that by 2020, recommendation engines will be able to help businesses boost profits by 15%.
  • Similar to how current recommendation engines look at a customer's buying habits, marketing can be improved by using machine learning to discover the types of products consumers are looking for and then offering these relevant product suggestions to ultimately increase conversions.
  • Not only are past browsing habits and purchases being considered, but as a result of machine learning, recommendations can now be made based on a user's mood.
  • According to McKinsey & Company: "AI and machine learning have the potential to create an additional $2.6T in value by 2020 in Marketing and Sales, and up to $2T in manufacturing and supply chain planning."
  • The trend towards machine learning being utilized for recommendation systems has been well-documented by Emerj, QuickSprout, EConsultancy, Forbes, Digital Marketing Institute, and McKinsey & Company.

Customer Personalization

  • Venture capital is being heavily invested in personalization systems that take full advantage of machine learning to personalize a customers experience. This includes personalization of calls to action on websites and the times emails are sent out.
  • Personalization using machine learning allows for highly-customizable marketing emails to be automated.
  • 52% of customers say they are likely to switch brands if they feel that a company is not doing enough to personalize their experience.
  • Research shows that 44% of customers will return after experiencing a personalized shopping experience.
  • The company Superdry has utilized machine learning for email marketing and has seen a remarkable 2,252% increase in ROI.
  • 1-800-Flowers experienced a 6.3% revenue increase in just one business quarter after implementing machine learning to improve customer personalization and experience.
  • Netflix uses personalization machine learning and saved $1 billion in 2017.
  • Customized push notifications on mobile devices can be auto-generated via machine learning.
  • Act-On, SingleGrain, Digital Marketing Institute, and all confirm that customer personalization is current trend for utilizing machine learning for external marketing purposes.

Advanced Customer Segmentation

  • Customers need to be segmented into groups to improve the engagement and targeting. Machine learning is able to objectively build a customer persona, improve personalization, and target people accordingly.
  • By properly segmenting a customer base, a business can expect to see five to eight times return on investment of marketing spend.
  • Not only can machine learning help to target potential customers, but it can also reveal the best influencers to market products.
  • Gartner cites the importance of leveraging customer experience saying that the customer experience portion of AI and machine learning will account "for 44 percent of global AI-derived business value" by 2022.
  • Already benefiting from machine learning in marketing are Mazda, Sephora, and Ben & Jerry's who have all seen an increase in their marketing ROI.
  • The trend towards advanced customer segmentation is well-covered by authorities such as QuickSprout, Entrepreneur, Simplilearn, and Gartner.

From Part 01
  • "Sometimes, a customer-facing chief digital officer turns into an inward-facing one. Andrew White, research vice president and distinguished analyst at Gartner, recalls a recent conversation with a chief digital officer who told him: “I spent the first couple of years engaged with customer satisfaction. "
  • "But if I can’t change the supply chain and organize the back end of our business, I can’t improve things for customers.” Increasingly, that chief digital officer found himself working internally, looking at the data solutions the company was using. “I started out customer-focused and outbound,” he told White. “Now I’m looking at our back end and suppliers, so the role seems to have evolved into something broader.”"
  • "“We can’t say, ‘We’ve transitioned all Deloitte applications to the cloud, therefore Deloitte is digital,’” he says. “We can’t say, ‘We have robotics process automation in finance, therefore Deloitte is digital.’ We have to do all these things and more to be a digital enterprise.” Becoming digital, he says, is a matter of mindset — retraining people and retooling business process — as well as adopting new technology."
  • "CEOs know firsthand that today’s business environment has dramatically evolved. Even in the relatively recent past, disruptions were radical but episodic. But in today’s fluid, digitally connected business ecosystems, disruption has become the norm rather than the exception, as wave after wave of upstarts-become-incumbents topple under yet newer competitive threats"
  • "This continuous flow of disruption has changed investor attitudes and expectations. Once focused almost exclusively on increasing profits by enhancing efficiency, financial markets and boards now expect CEOs to simultaneously optimize the current business model and inspire the company to search for the next one. In doing so, CEOs face the challenge not simply of steering companies through occasional monumental events, but of navigating constant turbulence with unerring agility—and empowering and inspiring their C-suites and organizations to do the same."
  • "Enter Mary Barra. From day one, Barra threw a wrench into the company culture, ousting seven high-level executives, claiming responsibility for the ignition problem, dismantling a system based on inward-facing metrics, and implementing a customer-focused system of accountability combined with open debate."
  • "Founded in 1979, we are the leading research and advisory company. We’ve expanded well beyond our flagship technology research to provide senior leaders across the enterprise with the indispensable business insights, advice and tools they need to achieve their mission-critical priorities and build the organizations of tomorrow. Together with our clients, we fuel the future of business so that a more successful world takes shape"
  • "Our clients turn to us for indispensable management and technology insights, advice and tools, delivered through our three lines of business"
  • "Digital Technologies and Growing Customer Expectations Mean Service Leaders Must Get the Digital Experience Right, According to Gartner Emerging digital trends are top of mind for customer service and support leaders in 2019, according to a recent survey by Gartner, Inc. Customer-facing artificial intelligence (AI), big data, customer activism and rising CRM costs are key priorities for customer service and support leaders this year.Dig"
  • "“The propagation of digital technologies and growing customer expectations in the service space are driving the need for greater digital capabilities and a more seamless digital experience,” said Lauren Villeneuve, advisor at Gartner. “With increasing internal and external expectations, service leaders are on the line for mastering digital. Only then will they be able to truly differentiate their organization and help drive growth.”"
  • "So, when people ask, “what’s different about Deloitte?” the answer resides in the many specific examples of where we have helped Deloitte member firm clients, our people, and sections of society to achieve remarkable goals, solve complex problems or make meaningful progress. Deeper still, it’s in the beliefs, behaviors and fundamental sense of purpose that underpin all that we do."
  • "With over 150 years of hard work and commitment to making a real difference, our organization has grown in scale and diversity—approximately 245,000 people in 150 countries and territories, providing audit, tax, legal, financial advisory, risk advisory, and consulting services—yet our shared culture remains the same."
  • "Deloitte” is the brand under which tens of thousands of dedicated professionals in independent firms throughout the world collaborate to provide audit, consulting, financial advisory, risk management, tax, and related services to select clients. These firms are members of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee (“DTTL”). Each DTTL member firm provides services in particular geographic areas and is subject to the laws and professional regulations of the particular country or countries in which it operates."
  • "Assessment Understand the behavioral and leadership traits responsible for enhancing or impeding your executive team’s performance. Learn More Board & CEO Advisory Partners Navigate core people issues, plan for the unexpected and proactively address board performance issues before they become a headline. Learn More "
  • "What We Do At Russell Reynolds Associates, we develop tailored solutions to help build, guide and grow your organization in an increasingly complex business landscape."
  • "As part of Russell Reynolds Associates’ commitment to understanding the future trends and challenges that our clients will face, we publish reports which examine the transformations taking place across major business sectors. In each of our studies, we look at an industry from the inside by gathering the views of experts, executives and senior commentators. In this report, we explore the changing dynamics of the technology solutions industry, drawing on interviews with executives in the IT hardware and electronics sector in Asia/Pacific and Europe."
  • "One of the critical challenges facing management teams is to strike the righ​t balance between providing strategic leadership while remaining close to market developments and customer needs. All too often the higher up the corporate ladder executives climb, the less contact they have with clients. "
  • "Our research identifies three structural elements which are changing to fit the new, post-sales environment: account management, product proposition and executive remuneration."
  • "Artificial Intelligence We find leaders to harness the power of artificial intelligence / prediction machines so our clients can enhance customer experience, improve current processes, and/or create new business models altogether."
  • "As companies outside the technology industry have begun developing in-house artificial intelligence, machine learning, and data science capabilities, a new set of technology talent challenges have arisen across the value chain."
  • "Members of our Technology Officer's practice work closely with industry sector leaders to help clients find these experts by first encouraging and facilitating conversations with their senior executives and outside experts to ensure that the right foundational questions have been asked -- even before the search process begins. We support our clients from the earliest stages of discussion to the conclusion of a successful search for a variety of AI focused positions, including:"
  • "Russell Reynolds Associates is a global leadership advisory and executive search firm that uses the Microsoft hybrid cloud to better meet the needs of customers in a fast-changing digital world. Russell Reynolds moved backup to the cloud using Microsoft System Center 2012 R2 Data Protection Manager to safeguard VMware workloads and transfer them to Microsoft Azure Backup. "
From Part 02
  • "Improving customer experiences by strengthening sales and marketing with greater insights is one of the primary catalysts driving AI and machine learning adoption today."
  • "Machine learning helps marketers discover which types of products consumers want based on their browsing histories and shopping behaviors. Relevant product suggestions increase conversions."
  • "Companies like Ben & Jerry’s, Mazda and Sephora have already recognized the positive impact that machine learning can have on their brands, including higher engagement rates and increased ROI."