Category: IT Services

Unveiling Hidden Dangers: Proactive Measures to Address Cloud Migration Risks | Blog

September 14, 2023

Moving an IT ecosystem to the cloud can be a complex undertaking that involves a multitude of risks – from technology and regulatory challenges to internal hurdles, as well as other unexpected problems that can arise without proper planning. Understanding these potential pitfalls and developing a comprehensive plan to mitigate them will ensure enterprises reap the many benefits cloud offers. Uncover the risks and learn recommendations to address them in this blog.  

In the last decade, cloud has risen to immense importance across all geographies and verticals, offering enterprises numerous benefits such as scalability, agility, and cost efficiency. As a result, it has become the bedrock of any digital business, leading more enterprises to increasingly migrate to the cloud. Additionally, enterprises are now also undergoing inter-cloud migration as they strengthen their cloud strategy and prioritize IT asset optimization.

Despite its apparent simplicity and prevalence in most digital transformation initiatives, enterprises must understand the associated cloud migration risks and proactively plan for contingencies. More than 55% of enterprises believe the COVID-19 pandemic rushed cloud adoptions and limited returns from cloud investments. This reinforces the importance of understanding cloud migration risks to fully realize the benefits that cloud promises.

Let’s look at the most commonly understood and observed risks that generally fall under the following categories:

  • Technology – This encompasses risk arising from challenges in integrating legacy and modern systems, possible misconfigurations during migration, and the ever-increasing technology skill gap
  • Regulatory – This pertains to risk related to data security and privacy, vertical and geography-specific compliance and regulations, and data governance and sovereignty
  • Client’s internal environment – This involves risks such as untrained internal resources, broken security controls, reliance on third-party vendors for different services, and possible operations disruptions

While service providers generally tackle these threats from the get-go, a few other potential impediments often get overlooked during the migration phase, creating larger issues later on if not proactively addressed.

Some of these additional risks can include:

  • Underwhelming perceived value: Enterprises often do not have clear post-migration expectations, resulting in most enterprises being dissatisfied within a year or two of starting the cloud migration process. An alarming 67% of enterprises have expressed their inability to realize the expected level of value from cloud. This extends beyond monetary value and also encompasses aspects such as innovation, compliance, resilience, and agility, which are expected as by-products of successful cloud migration
  • Negative stakeholder experience: Cloud migration can impact internal and external stakeholder experience. Any security breach or service disruption can expose corporate data and applications to cyberattacks and even damage the enterprise’s reputation and erode customer trust. Additionally, any unnecessary delay in migration timelines due to factors such as network issues, application incompatibility, or inefficient processes can lead to downtime and productivity loss
  • Exceeding budget expectations: Unplanned migration costs and the complexities surrounding the entire multi-cloud system end up giving most customers price shock. Around 60-70% of global enterprises believe cloud adoption costs were higher than their initial expectations of cost reduction. This occurs due to factors such as complex multi- and hybrid cloud environments, inefficient cloud resource management, lack of governance guardrails, and gaps in consumption visibility and management
  • Conflicting objectives: Senior stakeholders from various departments often view cloud migration from different lenses and have disparate objectives. Even if service providers meet the defined Key Performance Indicators (KPIs) and Service Level Agreements (SLAs), stakeholders still can be highly dissatisfied. This commonly arises due to misalignment between cloud, product, technical, and finance teams and the lack of defined accountability and ownership that results
  • Unplanned transitions: During the enterprise transition from one provider to another or from on-premise to an outsourced service provider, a proper transition methodology is crucial. Many enterprises struggle in this phase because transition teams do not contextualize their approach to the enterprise. This often results in a disconnect between expectations and outcomes in areas such as migration velocity, proposed SLAs, and risk management

Recommendations for mitigating cloud migration risks

To lessen these risks, enterprises should take the following actions:

  1. Define the value expected from cloud expectations
  • Define what value means to your enterprise. Different stakeholders often have varying ideas of value. Conduct a comprehensive assessment to come to a shared definition of value
  • Measure alignment to the defined value metrics at all stages of executing the migration plan
  • Recognize that value realization is continuous and emphasize the importance of making it a cyclic process rather than a one-time event
  1. Plan and assemble the right delivery team
  • Include an integrated cyber-cloud team to mitigate cloud security risks associated with migration efforts
  • Conduct a comprehensive RFP procedure to ensure the onboarding of certified and skilled talent with prior similar on-ground experience. Develop a detailed talent management plan across different execution phases
  • Ensure the availability of well-structured transition teams that offer industry- and enterprise-specific contextualization, particularly when transitioning from another vendor or a captive center
  1. Leverage Intellectual Properties (IPs) and frameworks
  • Implement a value-based migration framework internally or with a service provider partner to define and measure future value
  • Adopt an open communication framework that allows regular, timely, and contextualized communication with internal and external stakeholders to ensure consistent experience. This should be in addition to technology measures such as disaster recovery plans, incident response plans, and security measures
  • Prioritize the implementation of FinOps tools and solutions to enable cost optimization and visibility at all times
  1. Evolve contracting methodologies
  • Define Objectives and Key Results (OKRs), and don’t just contract for KPIs and SLAs
  • Push for some “skin in the game” from partners by encouraging transparent and flexible pricing models
  • Include knowledge transfer in the project scope to upskill internal teams to handle post-migration changes in the enterprise IT landscape

For more strategies to tackle cloud migration risks or to share your views on this topic, feel free to reach out to [email protected] or [email protected].

Unlocking the Power of OKRs to Achieve Ambitious Goals and Drive Business Strategy | Blog

September 14, 2023

Embraced by top tech companies, Objectives and Key Results (OKRs) help establish high-level measurable goals based on ambitious trackable targets. Paired with Key Performance Indicators (KPIs), these powerful tools can fuel organizational success. Discover how OKRs can benefit your business, the best practices for implementation, and how these goal-setting frameworks can work together to drive exceptional results.

Contact us to learn more.

In today’s rapidly evolving and competitive business landscape, setting and achieving the right strategic goals is essential for organizational growth and success. Businesses traditionally rely on Key Performance Indicators (KPIs) as the primary methodology for tracking these goals. However, are they effective in driving your business strategy? Or can another methodology better suit your business needs?

Objectives and Key Results (OKRs) have gained widespread adoption in recent years as a popular methodology pioneered by Intel’s former CEO Andy Grove. Its appeal grew when John Doerr introduced them to Google. OKRs have since evolved and spread to various industries and organizations worldwide, driven by the need for better alignment, increased transparency, and more effective goal-setting practices.

So, what exactly are OKRs?

A powerful goal-setting framework popularized by major technology companies, OKR, at its core, is designed to align teams and individuals with the organization’s overall strategic objectives. OKRs consist of these two main components:

  • Objectives: Clear and qualitative goals that outline what an organization wants to achieve. They provide direction and purpose, inspiring teams to aim high
  • Key Results: Specific, measurable, and time-bound milestones that indicate progress toward the objectives. Key results serve as tangible metrics for success

Is it another fancy approach? Are OKRs of any use?

OKRs offer several benefits that make them an attractive choice for ambitious organizations, including:

  • Alignment: OKRs ensure that everyone is working toward the same overarching objectives, fostering a unified sense of purpose and direction
  • Transparency and Accountability: By sharing OKRs openly, teams build a culture of transparency and accountability, encouraging individuals to take ownership of their contributions
  • Agility: OKRs allow organizations to adapt quickly to changing market conditions and adjust their strategies as needed
  • Motivation: Ambitious OKRs can inspire and motivate teams to go above and beyond to achieve extraordinary results

What companies have leveraged OKRs to fuel growth?

Companies like Google, LinkedIn, and Netflix have achieved remarkable success with OKRs in these ways:

  • Google utilized OKRs to launch innovative products and achieve significant business growth
  • LinkedIn used OKRs to expand its user base and improve customer satisfaction
  • Netflix leveraged OKRs to grow its subscriber base and produce hit original content

How can we define an OKR?

Here are some examples of OKRs to help you understand them better:

  • Objective: Increase customer satisfaction by 20%

Key Results: Increase the number of customer surveys completed by 40%. Increase the average customer satisfaction score by 10 points

  • Objective: Launch a new product by the end of the quarter

Key Results: Complete the product requirements by the end of the month. Develop the product prototype by the end of the quarter. Launch the product by the end of the quarter

What pointers should we keep in mind when defining OKRs?

To use OKRs effectively, consider the following four characteristics:

  1. Clarity: Objectives should be clear and easy to understand, providing a sense of direction for all stakeholders
  2. Specificity: Key results should be specific, measurable, and achievable, enabling progress tracking
  3. Ambition: OKRs should inspire and challenge teams to achieve exceptional results, pushing boundaries
  4. Alignment: OKRs should align with the organization’s overall mission and strategic priorities

Should we ditch KPIs now?

While both OKRs and KPIs are essential in assessing performance, they serve different purposes:

  • OKRs are aspirational and strategic, setting ambitious goals to drive overall organizational success
  • KPIs are operational and focused on specific metrics, measuring ongoing performance against predefined targets

OKRs and KPIs 09 12 2023 1

How can we use OKRs and KPIs together to achieve specific objectives?

OKRs and KPIs are not mutually exclusive. In fact, they complement each other in these ways:

  • OKRs provide the direction and inspiration to set ambitious goals
  • KPIs provide the data and measurement to track progress and fine-tune strategies
Parameter​ KPI​ OKR​
Objective​ Monitor “business-as-usual” drivers, identify problems, and areas for improvement​ Ambitious “business-goal-centric” view for measuring success​
Frequency​ Same metrics tracked for a longer period​ Metrics may change in the spirit of continuous improvement across multiple fronts and as business objectives change​
Ownership ​ Owned by departments or the organization as a whole​ Can be owned by individuals or teams​
Scope​ Focus mostly on operational metrics like velocity​ Focus on business objectives, such as growth, adoption, or customer satisfaction​
Level of challenge​ Maintaining current performance levels​ Push individuals and teams to achieve more​
Examples​ Increase velocity by 20%​ Improve brand awareness by increasing website traffic from 15% to 20% in Q2 through targeted marketing campaigns and content creation.​
Reduce customer churn rate by 5%​ Increase customer retention by 2% in May 2023 by improving customer satisfaction and loyalty through targeted marketing campaigns, personalized outreach, and enhanced customer support processes​

What best practices should my organization follow to successfully implement OKRs?

To ensure successful implementation and maximize the benefits of OKRs, consider the following best practices:

  1. Top-Down Alignment: Align OKRs with the organization’s overall mission, vision, and strategic priorities. Ensure that OKRs cascade down from top management to every individual, creating a unified sense of purpose
  2. Collaborative Goal Setting: Involve all relevant stakeholders in the OKR-setting process. Encourage open discussions and feedback to build consensus and ownership
  3. Clarity and Simplicity: Keep objectives and key results clear, concise, and easy to understand. Avoid jargon and unnecessary complexity to ensure everyone grasps their role in achieving success
  4. Measure What Matters: Focus on key metrics that directly impact the organization’s success. Avoid setting too many OKRs to prevent diluting efforts
  5. Flexibility and Adaptability: Embrace the agile nature of OKRs. Continuously review and adjust OKRs as circumstances change, allowing teams to stay responsive to market dynamics
  6. Regular Progress Tracking: Implement a robust tracking and reporting system to monitor progress regularly. Provide frequent updates and celebrate achievements to boost morale

OKRs and KPIs are powerful tools that can drive exceptional performance and success for organizations. By setting clear and aspirational objectives and measuring progress through specific key results, businesses can unlock their full potential. Strategically combining OKRs and KPIs allows organizations to achieve extraordinary results in a dynamic and competitive environment.

Start implementing OKRs in your organization today! Define ambitious objectives, set measurable key results, and foster a culture of transparency and accountability. To discuss how to embrace the power of OKRs to propel your organization toward new heights of success, contact Hemant Agrawal.

From Sci-Fi to Reality: Unraveling the Risks of Superintelligence | Blog

September 1, 2023

Superintelligence promises incredible advancements and solutions to the world’s biggest challenges, yet it also presents an ominous threat to society. As the lines between innovation and catastrophe blur, understanding the risks of AI is crucial. Read on for recommendations for moving forward in this uncharted territory.

Generative Artificial Intelligence’s emergence has led enterprises, tech vendors, and entrepreneurs to explore many different use cases for this disruptive technology while regulators seek to comprehend its wide-ranging implications and ensure its responsible use. Learn how enterprises can leverage GAI in our webinar, Welcoming the AI Summer: How Generative AI is Transforming Experiences.

Concerns persist as tech visionaries warn that AI might surpass human intelligence by the end of the decade. Humans are still far from fully grasping its potential ramifications and understanding how to collaborate with the technology and effectively mitigate its risks.

In a groundbreaking announcement in July, OpenAI unveiled that it has tasked a dedicated team with creating technologies and frameworks to control AI that surpasses human intelligence. It also committed to dedicating 20% of its computing resources to address this critical issue.

While initially exciting, the prospect of superintelligence also brings numerous challenges and risks. As we venture into this uncharted territory, understanding AI’s evolution and its potential implications on society becomes essential. Let’s explore this further.

Types of AI

AI can be broadly categorized into the following three types:

  • Narrow AI

Narrow AI systems are designed to excel at specific tasks, such as language translation, playing chess, or driving autonomous vehicles. Operating within well-defined boundaries, they cannot transfer knowledge or skills to other domains. Common examples include virtual assistants like Siri and Alexa, recommendation algorithms on streaming platforms, and image recognition software.

  • General AI

General AI possesses human-like cognitive abilities and can perform various intellectual tasks across various domains. Unlike narrow AI, general AI has the potential to learn from experiences and apply knowledge to different scenarios.

  • Super AI (Superintelligence):

Super AI represents a hypothetical AI that surpasses human cognitive abilities in all domains. It holds the promise to solve complex global challenges, such as climate change and disease eradication.

Tech thinkers across the globe have raised an alarm

Amidst growing concerns about the risks of superintelligence, the departure of Geoffrey Hinton, known as “the Godfather of AI,” from Google was one of the most significant developments in the AI realm. Hinton is not alone in his concern about AI risks. More than 1,000 tech leaders and researchers have signed an open letter urging a pause in AI development to give the world a chance to adapt and understand the current developments.

These leaders emphasized that development should not be done until we are certain that the outcomes will be beneficial and when the AI risks are fully known and can be managed.

In the letter, they highlighted the following five key AI risks:

  1. Machines surpassing human intelligence: The prospect of machines becoming more intelligent than humans raises ethical questions and fears of losing control over these systems. Ensuring that superintelligence remains beneficial and aligned with human values becomes crucial
  2. Risks of “bad actors” exploiting AI chatbots: As AI technologies evolve, malicious actors can potentially exploit AI chatbots to disseminate misinformation, conduct social engineering attacks, or perpetrate scams
  3. Few-shot learning capabilities: Superintelligent AI might possess the ability to learn and adapt rapidly, presenting challenges for security and containment. Ensuring safe and controlled learning environments becomes essential
  4. Existential risk posed by AI systems: A significant concern is that superintelligent AI could have unintended consequences or make decisions that could jeopardize humanity’s existence
  5. Impact on job markets: AI’s rapid advancement, especially superintelligence, might disrupt job markets and lead to widespread unemployment in certain sectors, necessitating measures to address this societal shift

As we already have seen some risks associated with this technology materialize, cautiously approaching the advancement of its progress is necessary.

Recommendation for moving forward

To mitigate AI risks and the risk of superintelligence while promoting its development for positive societal outcomes, we recommend enterprises take the following actions:

  • Create dedicated teams to monitor the development – The government needs to appoint relevant stakeholders in regulatory positions to monitor and control these developments, particularly to protect the large population that does not understand the technology from its potential consequences
  • Limit the current development – As the letter suggested, the government should implement an immediate moratorium on developing and using certain types of AI. This pause would give everyone enough time to understand the technology and associated risks better. While Italy has used its legal architecture to temporarily ban ChatGPT, efforts like this will not have a significant impact if carried out individually
  • Define policies – Regulatory agencies should start working on developing policies that direct researchers on how to develop the technology and define key levels for alerting regulatory agencies and others
  • Promote public awareness and engagement – Promoting awareness about AI and superintelligence is crucial to facilitate informed debates and ensure the technology aligns with societal values
  • Form international collaborations – Isolated initiatives won’t help the world. Larger collaboration among governments to define regulations and share knowledge is needed

While new technologies have always brought changes to the existing norms, disrupted established industries, and transformed societal dynamics, ensuring these advancements are beneficial to a larger audience is essential.

To discuss the risks of Generative AI, its use cases, and its implications across different industries, contact Niraj Agarwal, Priya Bhalla, and Vishal Gupta.

BigTechs’ Play in Generative AI in Healthcare | Blog

September 1, 2023

The healthcare sector is increasingly interested in harnessing generative AI capabilities to drive operational and cost efficiencies. Leading technology players are heavily investing in this space and partnering with healthcare enterprises to take advantage of its potential. Discover the latest developments, challenges, and outlook for generative AI in healthcare in this blog.  

The adoption of generative artificial Intelligence (GAI) by the healthcare industry has gained momentum in recent months with technological advances such as ChatGPT and Dall-E 2.

To tap into this growing demand for generative AI in healthcare, BigTechs (Amazon, Google, Microsoft, and Oracle) are leaving no stone unturned as they pivot toward developing capabilities at the intersection of healthcare and GAI. Let’s explore this further.

Recent healthcare-specific GAI announcements by BigTechs

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The frequency of recent investments by these tech giants signals that more funding will follow in the GAI-healthcare space.

BigTechs’ partner ecosystem – a key differentiator in developing industry-specific generative AI capabilities

As BigTechs make huge strides in ramping up their healthcare-specific generative AI capabilities, accessing large volumes of healthcare data is a major obstacle. To address this challenge, BigTechs are forging strategic partnerships with niche health tech firms or third-party data providers to obtain healthcare data for training Large Language Models (LLMs).

BigTechs also are leveraging partnerships to foster co-innovation and adopt a joint go-to-market strategy for healthcare-specific GAI solutions. For example, Oracle partnered with AI specialist firm Cohere to develop GAI solutions. Through the partnership, Cohere will train, build, and deploy its generative AI models on Oracle’s cloud infrastructure. Oracle plans to deploy new models for healthcare and embed GAI throughout its industry-specific applications.

BigTechs’ GAI capabilities are predominantly provider-focused  

Most investments by BigTechs in generative AI in healthcare are focused specifically on enhancing administrative processes for providers and physicians. Some of the prominent use cases are centered around streamlining clinical documentation and drafting automatic message responses to patients, as illustrated below:

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Seeing how the technology giants develop capabilities in care coordination and delivery will be interesting. Providing health and lifestyle recommendations, reminders for medications and appointments, and other proactive communications could significantly transform the way patient care is delivered.

When developing care coordination and delivery capabilities, BigTechs and other technology players must ensure the GAI models are built on huge volumes of patient data. This will significantly reduce the margin for error and help improve patient care outcomes.

Adoption of generative AI in healthcare is currently limited but will surge before long

While investments by suppliers are rising, GAI adoption in healthcare is still in its nascent stages. However, we have observed a few mid-to-large-sized hospitals and providers taking the leap of faith and becoming early adopters. For example, UC San Diego Health and UW Health in Madison, Wisconsin, are adopting GAI solutions developed by Microsoft and Epic to automatically draft message responses to patient queries.

To increase GAI adoption in healthcare, technology players and enterprises will have to jointly address these key considerations:

  • People – determining and acquiring the right skills
  • Process – change management and identifying the business functions
  • Technology – ensuring security and maintaining infrastructure

Most importantly, successfully navigating security challenges will be key to increasing adoption, as enterprises are skeptical about sharing sensitive patient data to train GAI models. Technology players will have to proactively alleviate this concern by ensuring patient data is protected and that the development of GAI models adheres to data privacy and state and federal government security mandates.

Moving forward, what will BigTechs focus on?

While most current use cases revolve around administrative and operational provider functions such as clinical documentation and medical coding, BigTechs are expected to invest in other provider-related functions shortly. Some provider-specific functions that are ripe for GAI investments are:

  • Billing and payments – Analyzing patient billing data, payment history, and due dates to generate personalized payment reminders for patients
  • Post-discharge follow-ups – Generating personalized care instructions and sending tailored health reminders to individuals, including medication adherence and lifestyle recommendations

Pre-care and post-care services, such as providing appointment reminders and billing options, could be near-term investment areas for BigTechs. By working together, BigTechs and enterprises can potentially leverage GAI to analyze patient data and proactively recommend care interventions – an exciting concept to keep an eye on.

Surprisingly, we have not seen much traction or activity in the payer segment on the supply or demand side. Considering payers are generally more inclined to embrace technology than providers, we anticipate demand and supply to grow in the short term.

It will be intriguing to watch the types of applications BigTechs create for payers when they dive deeply into this segment. Streamlining contact centers and automating benefit verification are low-hanging fruits BigTechs may target.

We will continue to closely follow how BigTechs’ GAI play evolves in the payer market. To discuss generative AI in healthcare, contact [email protected] and [email protected].

Learn more about technology in healthcare in our LinkedIn Live session, How Technology is Reshaping the Delivery of Care in the Healthcare Industry.

Unlocking Success: The Rising Importance of Service Providers in the SAP Mid-Market Growth Strategy | Blog

August 31, 2023

Service providers are expected to play a vital role in meeting the unique needs of customers in the strategic SAP mid-market. To help the software company achieve its growth targets, partnerships will be crucial. Discover the five customer priority areas where service providers can make a difference in this blog.       

SAP expects the mid-market to be a large contributor to meet its revised growth forecast of 8.3% over the next three years. To effectively attract clients in this segment, the company recognizes it will need to invest in extensive industry application development and form substantial agile partnerships with service providers.

To better evaluate this market, Everest Group’s Enterprise Platform Services (EPS) practice is launching a new PEAK Matrix® assessment. Learn more to participate

SAP mid-market customers have distinct priorities compared to large clients. Service providers who can tailor solutions to meet the following five key priorities will be valuable partners:

  1. Flexibility: SAP mid-market customers need providers that offer flexible services to adapt to their changing business requirements
  2. Responsiveness: Since SAP is typically a new platform for mid-market customers, providers need to proactively educate them on its capabilities and have responsive services teams available to address queries and concerns
  3. Regional support: Mid-market enterprises demand a higher regional presence for services because they want to establish robust communication and agile collaboration
  4. Cost attractiveness: Mid-market customers seek service providers that offer the most value for their SAP and services investments, aligning with their budget needs
  5. Customized services: These enterprises want service providers that invest in understanding their business processes and deliver SAP services tailored to specific requirements

While providers of SAP services focused on this segment may lack the scale or global footprint, they are laser-focused on addressing these key priorities of mid-market SAP customers. Beyond implementation, data migration, and customization, they also offer the benefits of training and support services.

SAP’s mid-market services have already made a significant impact, contributing an impressive US$ 13 billion with a staggering year-over-year growth rate of approximately 20%. With the introduction of the RISE with SAP and GROW with SAP programs, momentum is growing for small and medium-sized businesses to adopt the SAP suite for modernization and consolidation initiatives.

SAP services market divided by buyer segmentsSource: Everest Group (2023)
SAP services market divided by buyer segments | Source: Everest Group (2023)

Based on our analysis of the service provider landscape, the below exhibit shows the prominent providers in the mid-market segment across key regions:

Prominent mid-market-focused service providers strategically located across key regions | Source: Everest Group (2023)
Prominent mid-market-focused service providers strategically located across key regions | Source: Everest Group (2023)

To better evaluate this market and assist enterprises in key sourcing decisions, Everest Group’s Enterprise Platform Services (EPS) practice is launching a new PEAK Matrix® assessment, SAP Business Applications Services PEAK Matrix® Assessment 2023 for Mid-market Enterprises.   

Providers that derive at least 40% of SAP services revenue from mid-market clients with annual revenue below US$5 billion can participate in this assessment. To participate, reach out to EPS ([email protected]) or complete the form: SAP Business Applications Services PEAK Matrix® Assessment 2023 for Mid-market Enterprises.

For information on the SAP mid-market and service providers in SAP, contact [email protected], [email protected], and [email protected].

Change Involved in Moving to the Platform Operations Model | Blog

August 28, 2023

Many companies are now 5-10 years into their digital transformation journey. I have blogged for two years (here for instance) about how the journey drives companies to forge a more intimate relationship between their technology and their business operations, where they operate as one integrated team. At Everest Group, we refer to this convergence as “platform operations.” Companies over time find that the platform operations model accelerates their progress toward achieving their business objectives and key results (OKRs) while often decreasing their cost to serve.

Read more in my blog on Forbes

Navigating the Generative AI Conundrum in Life Sciences: Insights into Challenges, Implications, and an Adoption Roadmap for Commercial Technology Functions  

August 7, 2023

The life sciences industry can reap the many benefits of Generative Artificial Intelligence (GAI) by effectively overcoming challenges in this highly regulated industry to responsibly implement the technology. Discover key implications for technology players and a roadmap for enterprises to successfully adopt GAI for commercial functions.  

Help us learn more about the potential of gen AI in the life sciences commercial function by participating in this short survey and receive a complimentary summary of the survey findings.

In the first blog in this series, we explored Gen AI life sciences commercial use cases, shared industry leaders’ skeptical to optimistic perspectives on its potential, and uncovered new technology offerings. Read on for more insights into key risks, repercussions, and recommendations to adopt generative AI in life sciences.

“With great power comes great responsibility.” – Uncle Ben, Spiderman

Undoubtedly, Gen AI has massive potential to disrupt most processes and create new opportunities across industries, including the life sciences commercial function. But the highly regulated nature of this industry brings significant risks and challenges that will need to be overcome to adopt GAI at scale. Let’s explore this further in the illustration below:

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Risks and challenges associated with generative AI in life sciences

Key implications for the life sciences commercial technology ecosystem

“A journey of a thousand miles begins with a single step.” – Lao Tzu

While the Gen AI journey can appear long and daunting, commercial technology players may have a head start over their peers across the life sciences value chain. While certain use cases, such as personalized campaign generation and brand reputation monitoring, will require complex integrations and domain-specific development, other applications like content generation/analytics, market research, and autonomous customer support can be quickly implemented and brought to market.

Next, let’s take a look at six recommendations for life sciences technology providers to seize opportunities that GAI presents.

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Key Implications for life sciences commercial technology players
  1. Take a safety-first approach: First and foremost, commercial technology players need to address the safety aspects of Gen AI adoption and applications – from healthcare personnel/patient data safety and security to compliance with regulations and tackling ethical and legal risks. Providers that successfully address safety questions will instill trust and reliability with customers and gain a foot in the door to discuss and foster responsible Gen AI application across the commercial function
  1. Seize the opportunity to achieve domain specificity at scale: By combining the domain-data trained language models and large language models (LLMs), Gen AI provides a great opportunity for commercial technology players to offer domain specificity at scale across a wider range of solutions and areas. This integration enables the generation of more accurate, relevant, and specific outputs in the life sciences commercial function context, ensuring quicker model training, fine-tuning of responses, and domain-specific prompting
  1. Recognize that speed-to-market is essential: Technology providers must quickly identify, prioritize, and bring viable go-to-market opportunities and use cases to capture market attention, and, ultimately, the enterprise mindshare. While enterprises are still determining next steps with Gen AI, they are eager to learn more, explore potential use cases, and become better educated. Therefore, the velocity of go-to-market initiatives is immensely valuable
  1. Balance incremental and disruptive innovations: To succeed in the market, players will need to balance their bets between simpler quick-to-market propositions that augment existing capabilities and more strategic long-term opportunities that explore new segments, functionality, etc. With the abundance of possibilities, providers should carefully weigh options
  1. Partner with service providers: Service providers can be important allies in ensuring enterprise-wide acceptance and adoption of AI-enabled services. Technology players should look to forge strategic ties with service providers who need to be the flag bearers for technology modernization, data architecture, and process and change management initiatives
  1. Prepare to win the talent war: As demand for new skills (such as generative modeling, data engineering, and ethical AI) rises, the talent war is expected to get more vigorous. Players must proactively plan for strategic hiring and upskilling/cross-skilling initiatives

­

Enterprises are still evaluating the Gen AI conundrum across the entire life sciences commercial function, including the risks, challenges, costs, return on investment (RoI), talent, and processes. Our five-step GAI tools adoption guide can help enterprises accelerate this process, as illustrated below:

Picture3

While Gen AI holds immense promise for transforming the life sciences commercial landscape, it comes with its fair share of challenges, including ethical considerations, data quality, interpretability, and integration hurdles that need to be addressed to ensure responsible and successful adoption.

Technology providers can proactively develop strategies and solutions to overcome these obstacles. By crafting a thoughtful roadmap, committing to ethical practices, and focusing on continuous learning and improvement, the life sciences commercial solutions supply ecosystem can harness the power of Gen AI to unlock new opportunities, enhance customer experiences, and drive sustainable industry growth. While the journey to adopt Gen AI may be complex, the rewards for successful navigation are boundless.

Help us as we research the possibilities of Gen AI in the life sciences commercial sector by taking part in this brief survey. As a token of appreciation, you will receive a complimentary summary of the survey results.

To discuss Gen AI in life sciences and its impact on the commercial technology landscape, contact Rohit K, Durga Ambati, Panini K.

Six Key Takeaways from the Unisys Analyst and Advisor Event | Blog

July 19, 2023

The 2023 Unisys Analyst and Advisor Event provided a platform to showcase the company’s commitment to innovation and forward-thinking approach, exemplified by its new branding image in the IT services sector released last year. The company’s digital workplace strategy emerged as one of the key themes attracting our attention. To learn valuable insights from our analysts who attended the leadership presentations, read on.

Contact us directly to expand further on this topic.

Digital workplace artificial intelligence (including Generative Artificial Intelligence), cybersecurity, multi-cloud, and quantum computing were among the most prominent industry trends grabbing attention at the Unisys Analyst and Advisor Event, June 13-14 in New York.

Unisys presented a comprehensive update on the performance and prospects of its four business units: Cloud, Applications & Infrastructure Solutions (CA&I), Digital Workplace Solutions (DWS), Enterprise Computing Solutions (ECS), and Business Process Solutions (BPS).

Peter Altabef, Unisys CEO, set the stage with a fireside conversation preceding the event that focused on the ever-present concerns of cyber-attacks and vulnerabilities. Discussions over the two days covered important topics such as Unisys’ merger and acquisition (M&A) cloud solutions investment approach, its ClearPath Forward strategy for ECS, and increasing its presence in Banking, Financial Services, and Insurance.

Here are six takeaways of the main points we heard from Unisys leadership at the event:

  1. Reinforcing a commitment to innovation

Themed “Imagination to Realization,” the event provided an opportunity for the Unisys leadership team to emphasize its new brand proposition focused on creating an internal culture dedicated to providing “experience breakthroughs” for clients.

Given Unisys’ legacy-heavy business history, the rebranding aims to update the company’s image and make it more relevant to modern consumers’ requirements. The initiative emphasizes innovation and new technology solutions, increasing brand awareness and customer engagement.

  1. Focus on next-generation technologiesAligning with high-growth markets of next-generation technologies, specifically GAI, was a hot discussion topic dominating both formal and informal conversations. Unisys emphasized its goal of increasing next-generation revenue to 45 percent by 2026.

With its potential to disrupt and revolutionize the industry, the chatter surrounding GAI has even surpassed the buzz surrounding AI/Machine Learning (ML) solutions over the past few years. GAI’s immense promise vastly transcends any data privacy and governance concerns.

We envision GAI playing a larger role in such areas as summarizing incidents and findings, generating clear and concise reports and presentations, and augmenting human analyst capabilities by adapting responsibilities to the organization’s landscape and enhancing the analyst experience.

  1. Expansion in the US mid-market segment

Unisys is proactively diversifying its growth strategy by targeting mid-market US corporations, especially those between $2 billion and $5 billion, while also pursuing major deals. This segment holds promise since most mid-market clients feel overlooked or are forced to pay higher prices for less personalized services. By expanding their focus, companies can gain a first-mover advantage and capture a sizeable market share in this segment.

Large US IT service providers’ approach to the mid-market should provide simpler access to IT function heads and leadership teams, Experience Level Agreements (XLAs), and Requests for Proposals (RFPs). This presents Unisys with an opportunity to forge stronger client relationships that can be leveraged to support the enterprise’s digital transformation initiatives.

  1. Dedication to the digital workplace

We were most intrigued by the DWS update. Unisys continues to be a player with a dedicated focus and investment mindset on DWS, focusing on applying ML/AI to support capabilities across the workplace.

To address market opportunities across DWS, the company also is prototyping GAI use cases. Traditionally a strong desk-side support organization, Unisys is now pivoting its workplace portfolio around the acquisition of Unify Square and Mobienergy, providing balance and a future-ready portfolio.

With all the talk about XLA 2.0, Unisys shared that it designed an Experience Governance Board (XGB) in collaboration with a client to manage the evolution of XLAs. This demonstrates Unisys’s commitment to advancing beyond traditional XLAs. As XLAs reach their peak, the Board focuses on new XLAs and business needs to tackle more pressing concerns and find resolutions.

  1. Emphasis on organizational change management

The digital workplace landscape evolution has profoundly impacted Human Resources (HR) functions. HR now plays an expanded role in change management, with AI and automation boosting productivity by facilitating administrative and training processes. Service providers increasingly focus on organizational change management to cultivate a cohesive digital workplace environment.

Realizing that end-user acceptance of digital adoption is the most crucial step, Unisys leadership is actively working to institute change management in every transaction and not just the transition phase.

Unisys has implemented a targeted organizational change management program for customers that assesses users’ digital dexterity. This approach allows the company to determine the adoption level and utilization of digital workplace services among different user personas. By understanding workplace adoption patterns, Unisys can optimize digital workplace investments.

This exhaustive strategy guarantees successful technology implementation, positive user experiences, and measurable business outcomes.

  1. Partnering with clients

Unisys demonstrated its ability to foster client relationships by sharing compelling client success stories. The company’s prowess in fostering innovation and delivering tangible value is evident by its long-standing relationships with its top 50 clients, with an average collaboration of 20 years.

In one notable partnership with Elekta, Unisys effectively employed its digital transformation proficiency to enable the precision radiation therapy solution provider to enhance the end-user experience.

Unisys delivered its Intelligent Workplace Services, ensuring comprehensive 24/7 support of employees and partners across various communication channels, contributing to high-quality radiation treatment availability for cancer patients worldwide.

Unisys also highlighted its partnership with Dell Technologies. Working together, the companies efficiently and reliably resolve customers’ technological issues by delivering end-to-end solutions created for even the most demanding IT settings.

Both of these achievements exemplified Unisys’ ability to deliver measurable business outcomes and its commitment to innovation driven by technology solutions.

Udit Singh and Ronak Doshi represented Everest Group at the event. Reach out to this team with questions about digital workplace artificial intelligence and IT services markets.

Learn more about digital workplace technologies in the first video in our digital workplace opportunities series, Unlocking Digital Workplace Opportunities in 2023 | Episode 1: Exploring the Benefits of ChatGPT.

And discover cyber resiliency and cybersecurity trends, key enterprise investment themes, and the pricing and solution themes underlying the cybersecurity and cyber resiliency market in our webinar, Cyber Resiliency Strategy: Key Themes and Pricing Trends for 2023.

Navigating Disruptions in BFSI: The Role of Desktop Infrastructure Transformation (DIT) | Blog

July 17, 2023

The Banking, Financial Services, and Insurance (BFSI) industry faces various challenges in today’s evolving environment, from inflation and cybersecurity to increased competition from fintechs, and changing customer expectations. Desktop Infrastructure Transformation (DIT) has emerged as an attractive solution to combat these market disruptions because of its ability to optimize costs, empower users, and enhance IT efficiency. In this blog, we’ll explore how DIT can help the BFSI industry tackle pressing issues.

Contact us directly to discuss this topic further.

BFSI in the “Age of Disruption”

Benjamin Franklin’s wise words, “When you’re finished changing, you’re finished,” still hold true today, particularly in the rapidly evolving world of BFSI. Recent events such as the collapse of Silicon Valley Bank and UBS Bank’s acquisition of Credit Suisse show that those who fail to adapt will be left behind even quicker than they can Google “subprime mortgage crisis.”

Facing various internal and external disruptions, BFSI enterprises struggle with difficult questions. However, a recent Everest Group survey of 500 senior stakeholders supports that “fortune favors the bold.” The survey found 59% of respondents identify digital transformation maturity as a critical priority to withstand disruptions.

Considering these findings, the following framework provides an overview of disruptions BFSI enterprises face and outlines the actions to offset them:

Picture1 6
Source: Everest Group 2023

BFSI enterprises need to act swiftly and effectively to mitigate the impact of these disruptions. As highlighted in the framework above, DIT and its two sub-components – as part of an overall mature digital transformation approach – can provide a strong buttress against disruptions.

These sub-components can be broadly defined as follows:

  • Virtual Desktop Infrastructure (VDI): Technology that allows a user to access a desktop operating system and its applications from a remote server and thin clients
  • Full-stack Desktop-as-a-Service (DaaS): Cloud computing environment with bundled pricing for hardware, software, and ancillary management services in a pay-per-use model

In the following section, we examine the most pressing disruptions BFSI enterprises face and explore how DIT can provide a solution to address them:

Disruption Evidence Complication Question DIT to Rescue
Compounding impact of concurrent inflation and recession Inflation is at a 40-year high in most developed countries such as the US and UK –      Reduction in banking payments and transactions

–      Dip in insurance investments and higher payout expenses

–      Deterrence of new bond issuances and Initial Public Offerings

 How can enterprises offset the impact of inflation and be prepared for a recession? Cost effective and pay-as-you consume model through DaaS or VDI
Embracing Banking 4.0 and seizing new business opportunities The customer acquisition cost for a physical branch is approximately 50 times higher than for digital banking –      BFSI companies are under pressure to digitize their platforms/services immediately

–      Automation and data-driven decision-making has become pertinent

 How can BFSI enterprises effectively leverage the Banking 4.0 approach and seamlessly launch related businesses and products? Cloud-based desktop infrastructure for agility and to ensure faster time-to-market for digitized products/services
Increasing prevalence of cybersecurity attacks More than 60% of global financial institutions with at least $5 billion in assets were hit by cyberattacks in 2022 –      Higher risks of financial losses and reputational damage

–      Increased regulations and compliances, creating operational complexities

 How can BFSI companies manage cybersecurity threats while maintaining productivity and profitability? Embedded security over bolt-on security through centralized security controls and Artificial Intelligence (AI)-based threat analytics within VDI
Encroaching fintech startups, reshaping traditional BFSI Venmo’s users increased by 11% year over year in 2022, while the traditional bank growth on average is about 2-5% –      Increased pressure for collaborations between fintech startups and traditional banks

–      M&As leading to business process changes

 How can enterprises seamlessly transition to new business models and strengthen collaborations? On-demand desktop infrastructure scalability and seamless integration across enterprises through VDI and DaaS

Source: Everest Group 2023

Empowering BFSI Organizations through DIT

To better understand the composition of VDI and full-stack DaaS in a typical enterprise environment, the below framework provides more detail of the two previously defined key DIT components and their enablers:

Picture2 5

Note: The above framework is not an exhaustive representation of all the components within DaaS and VDI.

Source: Everest Group 2023

Now, let’s take a look at the benefits of this transformation initiative by exploring some applications of DIT that ideally align with the needs of the BFSI sector:

  • Cost optimization: With agile capacity management, increased device lifespan, and a pay-as-you-consume model, BFSI organizations can achieve cost efficiency while maintaining desktop infrastructure quality
  • Single pane of observability: AI-led analytics, synthetic bots for application performance testing, and proactive alerts help IT resources within a BFSI enterprise effectively monitor and manage their desktop infrastructure, achieving operational excellence
  • User empowerment: Personified Virtual Machines (VMs), a self-help marketplace, and DevOps-based feature development enable organizations to empower their end users and improve their experience
  • IT efficiency: Scalable architecture and limited upfront investment support expansion to alternative business models, geographies, and product lines. Cloud-hosted models also allow firms to seamlessly integrate with other IT stacks during mergers and acquisitions (M&As), and divestitures
  • Security and reliability: Automated patch management, trust zones, centralized security controls, and role-based access are some DIT features that enable continuous compliance with industry regulations and help BFSI enterprises avoid security breaches

Making DIT Real for BFSI Enterprises: Balancing Stability and Change

Let’s walk through the following use cases of DIT in various BFSI segments to demonstrate its value for employees ranging from investment traders to data scientists and knowledge workers:

Use case 1: Ensure zero downtime in a trading environment Scope: DaaS
Industry: BFSI Sub-segment: Investment banking Category: Emerging Persona: Power worker (traders)
The business need:

  • Supporting resource-intensive tasks, such as pre-trade processing, trade confirmation, and trade clearance
  • Enabling work on network-heavy applications, such as Bloomberg and Reuters
  • Embedding security and compliance
  • Supporting high-resolution audio-visual tasks
 DaaS Benefits:

  • Lag-free, high-performance machines
  • Seamless access to critical trading systems through inexpensive thin clients
  • Enhanced user productivity and experience through improvement in metrics such as win rate, loss rate, and winning trades
  • Interactive, multi-screen support to bolster decision-making

 

Use case 2: Facilitate data-driven, rapid decision-making Scope: VDI, DaaS
Industry: BFSI Sub-segment: All Category: Emerging Personas: Data scientists, business analysts
The business need:

  • Identifying meaningful data patterns from large data sets for smarter decision-making
  • Leveraging data analytics for cyber risk insurance analysis, fraud management, actuarial analysis, and credit record management
  • Identifying potential opportunities and threats
 Benefits:

  • Equips data scientists/analysts with a high-performance computing environment, accelerating decision-making
  • Enables secure remote access to custom platforms and tools to run compute-heavy Artificial Intelligence (AI) and deep learning workloads
  • Proactively identifies malicious transactions and requests

 

Use case 3: Realize synergies from M&A activities sooner Scope: VDI, DaaS
Industry: BFSI Sub-segment: All Category: Prevalent Personas: Knowledge workers and power workers
The business need:

  • Accelerating consolidations divestitures, and M&As
  • Providing omni-channel access during transition to critical functions such as wealth management
  • Avoiding business disruptions, cost leakages, and productivity loss
 Benefits:

  • Seamless accrual of targeted synergies
  • Efficient onboarding of new workforce, improved productivity, and reduced employee downtime
  • Cost optimization through models such as pay-per-use in device infrastructure

These use cases demonstrate the substantial value DIT offers in addressing the vital requirements of the BFSI sector and mitigating market disruptions. Several key benefits of DIT include cost optimization, operational excellence, user empowerment, and enhanced IT efficiency.

Yet, it is essential to recognize and thoroughly assess the associated risks of this technology, such as user acceptance and training challenges, as well as potential dependencies on network infrastructure. By carefully evaluating these factors, enterprises can make informed decisions about investments like DIT aimed at enhancing the IT infrastructure and diminishing market disruptions.

Ultimately, however, understanding the risk of inaction is critical. As Tony Robbins, life coach and author, aptly notes, “Risk comes in many forms, but the most common one is simply not investing.”

To discuss Desktop Infrastructure Transformation, contact Prabhneet Kaur and Udit Singh.

Generative AI in Retail and CPG: Revolutionizing Operations and Customer Experience | Blog

July 13, 2023

Generative Artificial Intelligence (GAI) can transform multiple facets of retail and consumer packaged goods (CPG) industries, from product development and digital commerce to sales and marketing, supply chain, and in-store operations. Explore GAI’s exciting future in this blog.

Contact us to speak to an analyst on this topic.

Following the growing trend in other industries, retail and CPG enterprises are now investing in GAI to harness its potential to enhance operations and customer experience.

While not a completely new technology, the current enthusiasm for GAI stems from the introduction of user-friendly interfaces (ChatGPT) that enable users to effortlessly generate high-quality text, graphics, and videos in seconds, marking a significant advancement in content creation.

But the question remains: Will GAI leave a lasting impact on the retail and consumer goods value chain, or will it follow the trajectory of numerous other technologies and fade into obscurity? Let’s explore this further.

To comprehensively grasp the impact of generative AI in retail and the CPG industry, we have identified and highlighted specific use cases across the value chain. By examining its potential and ease of adoption, we can better understand how GAI can revolutionize and drive transformative change in this sector.

The matrix below explores the more promising application areas and roadblocks to adoption across five areas of the retail and CPG industry value chain: product development, digital commerce, sales and marketing, supply chain, and in-store operations.

Picture2 1

From our analysis, the following key takeaways emerge:

  1. Product Development: GAI’s integration with data, analytics, and customer preferences empowers product development in retail and CPG, propelling innovative and efficient design processes. GAI enables businesses to create products that resonate with customers by enhancing decision-making capabilities and driving success in the competitive retail and CPG market.

Use Case: Anheuser-Busch’s AB InBev developed the world’s first AI-created beer called Beck’s Autonomous by leveraging GAI to analyze customer preferences. GAI tools such as ChatGPT and Midjourney were used to create the recipe and logo, name the beer, and design the packaging

  1. Digital Commerce: By leveraging GAI, businesses can create personalized and interactive customer experiences to optimize engagement and satisfaction. From dynamically generating product recommendations to creating virtual fitting and styling experiences, GAI opens new avenues for transforming the way customers interact and engage with retail and CPG brands.

Use Case: Levi’s has introduced a tool that allows customers to virtually try on apparel by capturing their body shapes with a smartphone. Integrated with GAI technology, this feature then generates images of them wearing different attire options

  1. Sales and marketing: GAI holds the transformative potential to revolutionize sales and marketing strategies in the retail and CPG sector, particularly by customizing messaging. Businesses can use GAI to create highly tailored and personalized marketing campaigns that resonate with individual customers, increasing engagement and conversions. Additionally, GAI enables precise targeting of localized market segments, allowing brands to deliver relevant and targeted messages that effectively capture the attention of specific regions or demographics.

Use Case: Utilizing GAI, IKEA collects consumer preference data from various regions and cultures, allowing the retailer to create localized marketing campaigns that successfully resonate with local audiences. This approach includes tailored campaigns for furniture products targeting young urban professionals to suburban families

  1. Supply chain: GAI can be a game-changer in optimizing supply chain operations for the retail and CPG industry, unlocking its vast potential to drive efficiency and productivity. By combining GAI with advanced analytics, businesses can gain valuable insights into demand forecasting, inventory management, and logistics optimization, resulting in streamlined operations and reduced costs. Moreover, automating documentation processes through GAI simplifies paperwork, saves time, and improves accuracy, contributing to smoother and more efficient supply chain workflows.

Use case: Walmart is harnessing GAI to develop efficient and sustainable supply chains. The retail giant employs algorithms for accurate demand forecasting, waste reduction, improved inventory management, and optimized transportation networks, resulting in lower costs and emissions

  1. In-store operations: GAI has immense promise to revolutionize in-store retail operations, offering a powerful tool to optimize various customer experience aspects. Applying GAI’s capabilities, retailers can analyze vast amounts of data and extract actionable insights to enhance sales performance. Additionally, GAI can automate and optimize tasks like managing inventory, creating visual merchandising, and personalizing product recommendations, ultimately improving operational efficiency and increasing customer satisfaction.

Use case: Amazon Go is enhancing its contactless checkout process by leveraging GAI to track customer movement, identify selected products, and automatically charge customers’ Amazon accounts when they exit the store

Outlook for Generative AI in retail and CPG

The future potential of generative AI in retail and CPG demonstrates encouraging prospects for enhancing customer engagement and operations. However, conducting thorough research before implementing this technology is crucial.

As the retail and CPG industry is still experimenting with GAI, it is advisable for businesses to first identify specific problems and understand how GAI can effectively solve them, rather than investing in flashy use cases.

Enterprises interested in experimenting with GAI technology should begin with customer-centric use cases as pilot projects before expanding to more complex applications. By taking this approach, retailers and consumer goods companies can ensure a smoother transition and realize the many benefits this technology offers.

Everest Group will continue to follow the evolution in this space. To discuss generative AI in retail and the CPG industry, please reach out to [email protected], [email protected], and [email protected].

Learn about the vast potential of GAI in customer experience in our LinkedIn Live, Generative AI in Customer Experience: Use Cases and Responsible Adoption.

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