Category: IT Services

SVB Aftermath: How Will the Bank Failures Impact the Technology Services Industry? | Blog

With the recent banking implosion, the global financial services industry, technology companies, and service providers will be hit in different ways. Let’s explore the reverberations of these concerning banking trends.

The failure of Silicon Valley Bank (SVB) along with Silvergate and Signature Bank raises the question: Are these isolated incidents or signs of greater trouble in the financial services industry signaling a recession in the US? We believe this will start a domino effect impacting banking regulations, profitability, and technology spend.

The recent collapse of the banks will have repercussions across the financial services system and may trigger the following aftermaths:

  • Opportunities for large banks to capture business from banks with similar concentration sector risks of sectors that are seeing slowdowns (e.g., the start-up and tech concentration for SVB)
  • Rising mergers and acquisitions (M&As) to counter concentration risks and take advantage of current banking valuations, especially in the mid-market and regional banking segments
  • Reversing rate hikes by the Federal Reserve could bring about a multi-fold impact, as most organizations have planned their business strategy with the assumption of additional hikes for rates in 2023
  • Tightening of spend across organizations to manage near-term profitability. This could also cause spending slowdowns this quarter for IT outsourcing suppliers. Discretionary spending also will dry up, and decisions on new large modernization deals will be delayed
  • Declining revenues and loss of business in the current and following quarters for IT outsourcing suppliers catering to these banks

After the dust settles, these bank collapses can bring about the following two key learnings in the long term:

  1. Data and analytics and Artificial Intelligence (AI) technologies could play a key role in better risk management (e.g., for the SVB asset-liability mismatch issue) to predict similar risk scenarios and prevent future failures
  2. Additional stress test scenarios can help avoid future bank runs on non-SIFI institutions

Banking trends and impact

As the events played out, Moody’s downgraded its view on the US banking system from stable to negative, citing a rapidly deteriorating operating environment. Banks with sector-specific concentration risks, specializing in two or three sectors, have grown deposits in the last couple of years and also have a higher percentage of customers with average deposits exceeding the FDIC-insured limit, putting them at higher risk.

These banks will need to assess their portfolios and provide assurance to their customers. Even with these guarantees, customers still may decide to change their banking partners and seek traditional large banks that have more liquidity, impacting regional and smaller banks’ growth.

Declining customers and subsequent deposits will also affect other banking portfolios, and digital and technology transformation spend may take a hit. Banks’ risk management functions also will be scrutinized again. For example, only one of the seven members of SVB’s Risk Committee had risk management experience.

Implications for the financial services industry

The global financial services industry also could be impacted. Other geographies like Japan and the UK are showing signs of distress with banks of similar portfolios and exposures.

The bank failures could have a lasting impact on the sector as the financial services industry restructures and implements new processes to avoid similar scenarios, including:

  • Stricter stress testing rules to prevent further risk to the nation’s financial stability
  • Increased frequency and number of stress testing within banks as they reassess their portfolios and plan for any asset-liability mismatches
  • Greater focus on banking governance in the US triggered by the questions raised over systemic risk exemptions for SVB and Signature
  • Layoffs and hiring freezes as the industry becomes more prudent and conservative
  • Larger banks taking business from banks that have similar risk issues and might struggle
  • Rising M&As, especially in the mid-market and regional banking segments

Opportunities for providers

Here are our recommendations on how technology and service providers can capitalize on these new banking trends:

  • Adopt a multi-stakeholder approach with large banks: More than half of the business and financial services (BFS) technology spend comes from Tier 1 banks, and we expect investments by these market giants to remain strong and even expand to address the ripple effects. Providers should adopt a multi-stakeholder approach to target risk and compliance, marketing, operations, technology, and business unit leaders who all might course correct their strategies (in response to potential Federal Reserve reverse rate hikes, products being stress tested, new ones being launched, increased regulatory reporting activity, etc.)
  • Prioritize accounts for small and mid-size banks and credit unions: Service providers need to re-prioritize their account strategy for these banks as they renew priorities and focus areas. We expect overall spending by small- and mid-size banks to decline, making it critical for providers to identify and pursue the right accounts with the most relevant messages (based on the level of financial health)
  • Reenergize pre-COVID cost-takeout playbooks with next-gen elements: As banks come under immense margin pressure, some asset takeovers and carve-out opportunities may arise. A solutions mindset will resonate more soundly with clients than a pure talent-led play. Providers should plug gaps by working with technology partners and/or bring in-house technology assets.

We expect an increase in offshoring intensity and a push for captive setup conversations through a build-operate-transfer (BOT) model approach. Service providers should watch the direction of US dollar prices as commercials will need to be revised for the foreign exchange (FX) impact (the double impact of potential rate reversal and wage inflation)

  • Support clients on product/portfolio diversification strategies (long-term): BFS firms entering and/or expanding their asset and wealth management business as part of their revenue diversification plan will spike. We hold onto our growth forecast in this segment with renewed affirmation from the market
  • Pivot to growth pockets that will be less impacted: Not all lines of businesses will be equally affected. There’s a glimmer of hope for a revival in investment banking, private equity, treasury, and brokerage spending on technology outsourcing. However, cards and payments will stay flat, and lending might struggle

Looking ahead, BFS firms will cautiously approach technology and outsourcing spending, resulting in another quarter of soft demand. We also expect increased medium-term regulatory actions leading to spending increases across risk and compliance functions for non-SIFIs.

Rippling effects across geographies

The recent bank failures have an underlying mix of bank-specific (micro) and macro-economic factors in play. The macro factors have the potential to increase fear in the markets (and depositors) as government bond yields have shown signs of reversing their course, and the added factors of slower economic recovery, inflation, high-interest rates, and the resulting layoffs in specific sectors add further pressure.

Credit Suisse saw a 20% fall in share price on fears of a liquidity crunch on March 15. This also impacted shares of other European banks, such as BNP Paribas, Societe Generale, Commerzbank, and Deutsche Bank falling between 8% and 10%.

We are closely observing the market and regulatory actions and are available for any questions you or your teams might have about the impact of these latest banking trends. Please reach out to Ronak Doshi, [email protected], Kriti Gupta, [email protected], or Pranati Dave, [email protected].

Learn about key trends and the outlook for the global services market in 2023 in our webinar, Global Services: Lessons from 2022 and Key Trends Shaping 2023.

Uncovering a Massive Insurance Industry Cloud Opportunity | Blog

Cloud computing presents a huge opportunity for insurers to drive growth, improve efficiency, and deliver innovation, among other benefits. Read on to learn about the coming phase of industry cloud and the key role system integrators (SIs) can play in advancing cloud adoption in insurance.

As insurance enterprises navigate the volatile and risky macroeconomic environment combined with recessionary market sentiment, increasing operational resiliency and agility and delivering superior speed becomes essential.

Insurers have to work effectively, efficiently, and, most importantly, smartly. The urgent demand to innovate and move beyond risk remediation to risk mitigation is making insurers realize the importance of leveraging cloud as a key enabler of growth and efficiency mandates. Let’s explore this opportunity further.

Cloud rises to the top of the business agenda for insurers

Most insurers currently rely on cloud for non-core operations while they explore stepping up to full production. While cloud’s massive potential is well known, insurance enterprises hold back from completely leveraging it for various reasons, including security concerns, integration issues, and the existing legacy stack. The inability to realize full value from cloud investments also becomes a massive roadblock.

Fortunately, the mindset regarding cloud adoption in insurance is taking a huge turn. A cloud-first approach is becoming important to insurance enterprise business leaders who find its benefits too irresistible to pass up.

In addition to helping meet cost and efficiency mandates, deriving full potential and optimizing cloud investments, and driving business-focused growth and experience are arousing interest in cloud adoption in insurance.

A recent Everest Group study on cloud initiatives with more than 75 insurance enterprises found that 70% of insurance leaders believe that cloud insurance initiatives make up more than 20% of their IT spend, as illustrated in the exhibit below.

Driving business agility and lowering the total cost of ownership has become the most important aspect of cloud transformation for insurers. Achieving data-centricity by seamlessly integrating external data with internal datasets, facilitating real-time analysis of large data volumes, and enabling data-driven decision-making across the value chain are other desires gaining prominence among insurers.

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The near future is industry cloud

Slowly and gradually, innovation is taking a front seat in managing the IT estate for the insurance industry. As insurers embark on their next growth phase, they increasingly need to run industry-specific workloads on cloud, such as premium payment processing, policy administration, loss notification, multi-channel sales and distribution management, and claims management and fraud detection.

With insurers moving away from a one-size-fits-all approach, industry cloud is expected to drive the cloud spend going forward to future-proof the technology estate, monetize data to generate alternate revenue streams, and re-think value delivery to end customers. Insurance leaders have started realizing that industry cloud can be a catalyst for transforming and automating industry-specific business processes.

Industry cloud allows industry leaders to get all the assets organized in one place which are specific to the use cases of the industries they operate in. This platform is becoming the next big thing in cloud computing and insurance as it easily allows enterprises to customize processes based on usage, differentiate faster, and innovate in a better way.

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SIs need to support hyperscalers and carriers to shape industry cloud

As the need to develop the industry cloud story gains prominence, the concept of co-creating also is booming. Generally, hyperscalers provide the building blocks for cloud, and SI partners assist insurers in creating and customizing specific applications and business processes on top of that foundation.

Insurers increasingly expect cloud providers to create customized and insurance-specific core solutions that address their unique needs and enable modular business processes. However, industry cloud is the missing piece in full-stack capability for hyperscalers.

As a result, they need support from SIs to realize their vision of catering to the entire enterprise IT stack. SIs need to support hyperscalers in identifying high-potential insurance industry cloud use cases aligned with specific business segments, as shown below.

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Cloud computing has moved beyond being ‘just a digital infrastructure’ to replace on-premise servers. The latest cloud services are more aligned towards integrating advanced technologies such as Artificial Intelligence/Machine Learning (AI/ML), the Internet of Things (IoT), and data analytics to transform the insurance value chain.

For example, cloud computing can take claims management to the next level by managing and automating claims handling and offering a superior claims experience. By combining cloud capabilities with data and AI, insurers can fundamentally change how they manage claims. Infusing AI/ML in claims processes can help insurers tap the plethora of data they possess and unlock immense value to come out on top.

Cloud enables insurers to reduce manual handling, lower error rates, and perform more straight-through processing, eventually leading to faster claims processing and a superior claims experience.

Everest Group research shows about 35% of P&C insurers’ priorities across claims management focused on enhancing customer experience (based on an analysis of 60-plus case studies involving claims modernization/transformation).

Cloud computing also allows insurers to drive superior efficiency by enabling data and analytics-driven claims processing and focusing on effective service delivery to reduce claims expenses and improve claims handling accuracy – all while ensuring greater customer satisfaction.

The time for insurers to go big on cloud has come

Cloud computing is no longer a choice but a mandate for insurance leaders. The insurance industry is finally catching up to the momentum of integrating SaaS into IT systems. As insurers replace outdated mainframe and on-premise infrastructure that has become harder to update and inefficient to scale and maintain, they must leverage the skills and experience SIs offer. Close partnerships between insurers and SIs also can help drive innovation and is where the future is leading.

Everest Group is launching an inaugural Cloud Services in Insurance PEAK Matrix® Assessment 2023. Please reach out to [email protected] and [email protected] for more information on cloud adoption in the insurance industry and to participate in the Cloud Services in Insurance PEAK Matrix® Assessment 2023.

You can also watch our webinar to learn about software and cloud pricing and contract negotiations and to keep spend in check.

Impact of ChatGPT and Similar Generative AI Solutions on the Talent Market | Blog

ChatGPT’s arrival has brought much hype and speculation that it could replace several human workforce areas. While ChatGPT shows great early potential, how will it impact the “future of work” and the overall talent landscape? Read the latest blog in our series to learn more about the impact of ChatGPT and other generative Artificial Intelligence (AI) solutions on the workforce.

Since its advent, ChatGPT has taken the internet by storm, reaching a million users in under a week. No wonder it is the most talked about subject in technology and innovation. While ChatGPT has generated a lot of curiosity among netizens, the big techs are not far from the spotlight.

Microsoft has already invested billions in the technology and even integrated it into its search engine Bing. Google has officially announced “Bard,” its ChatGPT rival based on an in-house language model that is undergoing testing before being released to the public.

Chinese search engine Baidu has announced the testing of a similar tool, “Ernie Bot,” while Alibaba also confirmed working on an AI tool. Worldwide, we are witnessing rapid innovation and updates in this field, and by the time you read this blog, we might expect some more new developments.

What does it mean for the talent and workforce industry?

While the utility of a generative AI like ChatGPT remains an area to explore, we expect HR and business leaders to leverage ChatGPT across various dimensions of work and talent management. The workforce industry has evolved over the past few decades, and with the advent of machine learning and AI, we can expect to see some major transformations in the coming few years.

While ChatGPT has the potential to impact talent management, it is still not a replacement for human recruiters. Instead, it can assist them by streamlining the process and making it cost-effective and efficient by automating routine tasks, improving the candidate experience, and enhancing the recruitment process.

Some functions like job screening, content development, and job pricing will see a greater impact than other roles, as illustrated below:

Current mapping of ChatGPT and similar AI across the talent management value chain

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Where can ChatGPT replace human involvement in the near and long term?

ChatGPT has already proven its capability to solve math, write code and content, create poetry and literature, converse with other AI tools, and assist with business problems. Soon, generative AI tools have the potential to replace most non-automated tasks such as targeting prospects, writing sales pitches, drafting reports, writing basic code, developing financial models, analyzing data, assessing candidates, optimizing operations, etc. Although the list has no definite bounds, the possibility exists for a single generative AI replacing jobs across multiple domains such as marketing, sales, finance, operations, etc.

The potential impact of ChatGPT and similar AI across workforce areas

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Key examples of generative AI adoption

Here are some of the applications for these tools in the industry:

  • Content creators at leading cloud services company VMware use the AI-based content creation toolJasper to generate original content for marketing – from email to product campaigns on social media
  • Morgan Stanley is working with OpenAI’s ChatGPT to fine-tune its training content on wealth management. Financial advisors are using it to search for existing content within the firm and design tailored content for its clients
  • Codeword, a leading tech marketing agency, has already hired the world’s first AI interns as an experiment to assist them with content writing, design, animation, and marketing

On similar themes, we have seen companies leveraging AI, such as Tesla building driverless cars and McDonald’s experimenting with employee-less eateries. In a few years, AI bots could replace various roles, such as customer service executives, recruiters, content writers, and even coders.

We might expect to see a single generative AI tool functioning across multiple domains (finance, HR, marketing, customer service, operations, etc.) within an organization, reducing the need for human intervention.

Blue-collar jobs were already at risk, and the success of ChatGPT further threatens several white-collar professions as well. In the long run, ChatGPT and similar AI tools can open doors to many new opportunities for AI integration, and any prediction we make has a higher risk of falling short of reality.

What challenges are associated with ChatGPT adoption?

We have already discussed the technical challenges of ChatGPT in our earlier blogs (see links at the end of this post.) Human interaction and empathetic judgment are the two major challenges for any AI tool to penetrate the talent management space. Also, limited capabilities in languages other than English and text-driven communication style restrict the use cases of generative AI in non-English speaking regions. Ethical and legal concerns also need to be addressed as the distinction between AI-generated and human-generated data blurs.

In addition, most short-term use cases of generative AI, such as chatbots, already have an alternative available in the market. It will take time for ChatGPT to further integrate into the talent market and move from an experimental basis to organization-wide implementation. Integrating a new system also requires additional investments and training that organizations need to explore.

Impact of ChatGPT on the future workforce

Amid all the hype and speculation, one thing is for sure: AI is here to stay. As humans, we need to embrace it and learn to co-exist with it. With the rise in AI adoption, the talent dynamics also are expected to change, and certain skills/roles associated with it will soar as we enter the age of AI.

Going ahead, we can expect to see higher demand for relevant technical skills. This also creates opportunities for several related skills, such as people with specific domain knowledge to train models and personnel, review content, ensure data reliability, and integrate systems based on industry needs.

Follow our next blog in the series to learn more about the type of skills/roles that will be affected and the new roles that will emerge in demand.

Below are some illustrations of the current capabilities and limitations of ChatGPT on talent-related queries. (The screenshots were taken on February 20, 2023, from India and the responses might be different for other users.)

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For our previous blogs on this topic, see ChatGPT – Can BFSI Benefit from an Intelligent Conversation Friend in the Long Term?, ChatGPT Trends – A Bot’s Perspective on How the Promising Technology will Impact BPS and ChatGPT – A New Dawn in the Application Development Process?

If you have questions about the latest trends in the talent landscape or would like to discuss developments in this space, reach out to [email protected] or [email protected].

You can also watch our webinar, Top Emerging Technology Trends: What Sourcing Needs to Know in 2023, to learn more about how organizations can implement new technologies into processes and operations.

Experience, Data, and Trust – The Industrialization of Data-driven Personalized Experiences | Blog

Balancing experience with data and trust is essential to delivering engaging personalized experiences for customers and driving business success. Developing a robust and scalable automated process for data-driven personalization is critical for enterprises to win in the evolving personalization and interactive experience segment. Read on to learn more.  

Customer experiences have become increasingly prevalent with the democratization of the internet, coupled with significant technological and data processing advancements over the past few years. Enterprises are now realizing the value of prioritizing the people side of business. Creating positive personalized experiences for customers can foster loyalty, increase customer satisfaction, and drive repeat business. On the other hand, negative experiences can damage a reputation and reduce customer loyalty. Let’s explore the importance of personalization.

Personalization – then, now, forever

Personalization is not a new concept. It has existed for decades. Enterprises must capture users’ attention and stand out to thrive. According to Everest Group estimates, more than 70% of consumers interact with a personalized promotional message.

Personalization, more commonly known as “persona-based personalization,” mostly involves grouping users into segments or personas based on common characteristics or behaviors. This approach can be effective in delivering relevant content or offers to a large group of users with similar interests or needs, based on demographics, purchase history, or browsing behavior.

Today, technological advancements have changed the landscape. Categorizing consumers is difficult because they don’t have just one interest area. The plethora of information available online has shifted the power to consumers who determine their preferences, disrupting brands that are no longer in charge.

As a result, brands now are also adopting “person-based personalization,” a form of personalization that considers the individual’s unique needs and habits instead of categorizing the user into specific buckets. Personality-based personalization is a 1:1 approach, where enterprises focus just on the customer as an individual. Everything revolves around the individual as a person, ranging from interactive experiences to advanced personalized marketing strategies. While persona-based personalization involves a large sample size, person-based personalization involves a sample size of just the individual.

Because person-based personalization has the potential to deliver high returns on investment (ROI) to enterprises, deploying an industrialized process for real-time person-based personalization is essential.

While most brands have invested in personalization, some remain reluctant to fully embrace real-time data-driven personalization at scale, which involves personalizing every touchpoint in the customer’s journey based on real-time context. This method requires a unique interplay of data, intelligence, and omnichannel strategies. Developing an industrialized process for delivering individual personalization beyond the required data analysis is essential for enterprises.

Data-driven personalization at scale is the need of the hour

Data is the most critical requirement for delivering effective personalization. Personalization is driven by insights into individual preferences, behaviors, and needs that only can be obtained by collecting and analyzing data. Data collection needs to be well-thought-out. Enterprises require large volumes of data collected from multiple sources, and this data needs to be of good quality, accurate, and relevant because poor-quality data can lead to incorrect insights. Collecting diverse and up-to-date information is another important aspect.

The scope of data gathering has increased too. In the past, customer data was mainly collected via offline surveys, point-of-sales, and telecommunication, just to name a few. But the increased digitization supplemented with advancements in data and analytics has greatly impacted personalization by also allowing for collecting and analyzing vast amounts of data through digital channels. This has led to more seamless personalized experiences for users and has helped companies build deeper relationships with their customers.

An Everest Group study suggests that 78% of startups in the customer experience (CX) space leverage Artificial Intelligence (AI) to develop more relevant and engaging solutions for customer conversion, engagement, and retention. With the rise of AI, personalization has become even more precise and can consider a wider range of factors such as emotions, mood, and context.

However, significant investments are required if enterprises want to set up in-house industrialized data collection and analysis. This is where data platforms come into the picture. Data platforms can be thought of as purpose-built systems or infrastructures to collect, manage, and process large data amounts. It typically includes technologies and tools for data storage, data processing, data integration, data security, and data governance.

Data Experience Platforms (DXPs) offer a  collection of tools such as Digital Asset Management (DAM)Customer Relationship Management (CRM), Customer Data Platforms (CDP), and personalization tools that can meet the needs of enterprises, as illustrated below.

Exhibit 1. Data collection tools for aiding personalization efforts

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How privacy and data guidelines affect user data collection

As discussed, data is essential to personalization. Clearly, the more data enterprises have, the better insights they can gain, and the better experiences they can provide. However, in today’s digital environment, user safety and trust are crucial. Consumer awareness is on the rise, with people growing increasingly skeptical about sharing their data. Concerns over how personal data is handled and safeguarded by enterprises are growing.

According to the United Nations Conference on Trade and Development (UNCTAD), 71% of countries today have some legislation around data protection and privacy, while 9% have draft legislation. Stringent data regulations such as the General Data Protection Regulation (GDPR) in the European Union, Nigeria’s Data Protection Regulation (NDPR), The California Consumer Privacy Act (CCPA), etc., have provisions to heavily penalize enterprises misusing consumer data.

Adding to this is the increasing push to eliminate third-party cookies. While browsers such as Apple Safari and Mozilla Firefox have already taken the step, market leader Google Chrome also has announced its intention to phase out third-party cookies by 2024, extending its earlier deadline. This has brought into focus the collection of voluntary data from users (Zero-party data) and first-party sources (1P data).

Zero-party data is a valuable information source for enterprises as it provides the best clarity to individual preferences. Developing a trust-based relationship with users and having total transparency about the use cases of zero-party data is essential for enterprises. Establishing a trust-based relationship might lead users to voluntarily provide more insights.

First-party data collection also needs to be transparent and strong security measures should be implemented to protect personal data. Sensitive data must be encrypted, security regularly audited, and effective access control measures adopted. Brands need to consider the needs of empowered users by honoring their “right to forget” and “untraceable” requirements.

As enterprises possess an enormous amount of users’ personal data, they also need to take the moral responsibility to protect that data. Customers who provide their data to enterprises understandably want their data to be protected and not misused without their knowledge. According to Everest Group estimates, more than 50% of customers are willing to share their personal data with companies but only with a clear understanding of how it will be used.

Combining automation with data and trust

Winning user trust and gaining access to more voluntarily provided data is no doubt essential to achieving better person-based personalization. But this data needs to be utilized in the best manner by making use of tools (such as personalization engines and marketing automation tools) to set up an industrialized workflow for large-scale 1:1 person-based personalization. Without a robust and scalable automated process for large-scale person-based personalization, enterprises tend to lose.

Exhibit 2. The industrialized workflow for achieving data-driven 1:1 personalization

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Greater trust = Greater data = Greater personalized experiences

Personalization starts from a persona-based mechanism and, with an ever-increasing user base, shifts to person-based personalization. User data is the only way to go forward. User data and trust need to go hand in hand. To win customer attention, trust, and loyalty, enterprises need to know how to use the right data at the right time and how to go ahead with individual personalization without breaching the intrusion barrier.

Exhibit 3. Relationship between Trust and Personalization

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The outlook

Overall, the personalization and interactive experience landscape has become more complex and diverse, requiring brands to constantly adapt and stay up to date on the latest trends and technologies to reach and engage customers. However, even with increasing investments, the ROI might decline due to the heightened competition making it more challenging to stand out and generate returns, technical limitations, and privacy concerns, just to name a few.

Enterprises need to break down their user base into smaller, more targeted segments to achieve 1:1 person-based personalization and tailor products, services, and experiences to each individual user’s specific needs and preferences. The smaller the segments, the better enterprises can tailor their personalization efforts and achieve a more effective 1:1 experience.

In addition to the investment level, the strategy and implementation of personalization and experience efforts also needs to be considered. A well-designed and executed strategy can generate returns even with increasing investments. By balancing experience with data and trust, companies can deliver engaging personalized experiences that build strong relationships with users and drive business success.

If you have questions about selecting the right data platform or want to know more about personalization, interactive experiences, or discuss developments in this space, reach out to our analysts at the Adobe Summit, or get in touch with the Everest Group team at [email protected], or [email protected].

To learn about the comprehensive roadmap for enterprises to achieve business outcomes and mitigate challenges in their journey to accomplish truly industrialized 1:1 person-based personalization, see our report Emergence of CDPs: Charting the Path to Data-driven Personalization.

Check out our webinar, Strategies for Customer Experience (CX) Success in an Uncertain World, to learn key trends and hear recommendations on what to prioritize to deliver exceptional CX.

Private 5G and Wi-Fi 6: Competition or Cooperation? | Blog

While Wi-Fi 6/6E and private 5G technologies each offer advantages in different applications, these next-generation wireless networking technologies can work better together than against one another. Read on to learn how these solutions can complement each other and support enterprises’ technology transformation journeys.

Driven by massively increased device penetration and interconnectedness in recent years, combined with rising investments and research from technology and solutions providers, Wi-Fi 6/6E and private 5G technologies both offer substantial opportunities for enterprise development.

Still in its nascent phase, private 5G is beginning to take off with advancements in this technology particularly prominent across America, Europe, and Asia Pacific, especially in the US, UK, China, and South Korea.

While from a top level, both Wi-Fi 6 and private 5G offer improved network connectivity opportunities and other benefits, the technology types differ in accessibility, licensing, authentication, and use cases. Let’s compare them.

Core differences and suitability

  • Wi-Fi 6/6E – Generally, it is more suited for indoor, smaller-scale wireless networks. Its lower spectrum complexity and relative implementation ease make it a more accessible solution compared to private 5G. Wi-Fi 6/6E’s increased support for internet of things (IoT)-connected devices and high-density wireless traffic make it ideal for venues such as schools, stadiums, and shopping malls. Wi-Fi 6/6E also can be more easily integrated with enterprise management tools in areas such as security, visibility, and analytics
  • Private 5G – It is more suited to outdoor use cases on a larger and more complex scale. Autonomous vehicles, smart cities and factories, and remote healthcare are some of the leading use cases and conversation starters for private 5G at present

In the graphic below, we compare the performance and efficiency of each use case. The blue highlighted sections show the areas where the technology is better suited:

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Advantages each offer

In terms of accessibility and attractiveness, Wi-Fi 6/6E technologies have some clear benefits over private 5G. The spectrum for wireless local-area network (WLAN) technology is less complex than cellular, which may be more attractive to enterprises looking to incorporate one of the technologies to improve their wireless setup.

Wi-Fi 6/6E as a product also is at a later development stage than private 5G. This means highly developed and specialized equipment already is in mass production and readily available, whereas use case specific private 5G options may not be as well-defined. These factors can make it more cost-effective for enterprises using a Wi-Fi 6/6E solution and have an improved return on investment, especially in the short term.

Private 5G’s higher complexity does bring benefits, though. For instance, it can meet the needs of more complex and intensive wireless setups than WLAN technologies and address enterprises’ data privacy concerns around internal data and security better than a Wi-Fi 6/6E network.

How can these technologies synergize?

Both Wi-Fi 6/6E and 5G can act as catalysts for enterprises’ wireless journeys moving forward, and each offer clear benefits and use cases in which they are preferable. But this doesn’t mean they are necessarily rivals. Rather, treating them as complementary solutions can bring more benefits.

Cooperation between Wi-Fi 6/6E and 5G networks can enable innovation and success with IoT growth and edge computing capabilities. Together, the networks will be able to support remote workforces more efficiently and reliably and bolster overall connectivity with speed and flexibility. Businesses engaging in multiple verticals, for example, may find it better to incorporate both options to deal with their network demands at a range of scales.

Recommendations for the short- and long-term

With that said, enterprises may find it beneficial to focus on solutions from Wi-Fi 6/6E offerings in the short term because this more developed technology can provide greater automation benefits, and is more accommodating for stricter budgets – a substantial plus in a recessionary environment.

Private 5G setups then can be incorporated in the longer term when it is better-developed, more affordable, and able to be utilized in a higher range of verticals and use cases. Private 5G-friendly use cases also will mature in the future in segments including mining, manufacturing, and Industry 4.0.

While Wi-Fi 6/6E technologies are increasingly explored in existing applications, private 5G will become prominent for conceptual and transformative use cases. As a result, enterprises, telecommunications providers, and systems integrators may seek to incorporate private 5G technologies as part of their long-term network setups.

Key Factors to Consider

Ecosystem participants have the following critical factors to consider while making decisions about private 5G and Wi-Fi 6/6E:

  • Business and network enterprise heads can look to proactively improve their wireless setups with a view to the longer term and the transformative technologies they plan to invest in. This can be achieved by consulting with service providers to see which technologies will better fit their industry-specific demands and use cases
  • Heads of systems integrators and telecommunications providers can consider the network with cloud and IT as pivotal business initiatives. More specifically, they can investigate treating Wi-Fi6/6E and private 5G options as potentially pivotal in their network decisions. This can allow them to better exploit and benefit from developing network technologies
  • Partnership heads of technology providers can look to extend their offerings of products and services within Wi-Fi 6/6E and private 5G and showcase their ability to meet the industry-specific use case demands of customers across different segments when partnering

While wireless network decisions often can be an afterthought, having a well-planned strategy can benefit an enterprise’s IT setup and overall business. To achieve short-term results and long-term business transformation, the C-Suite should adopt a dynamic network strategy, including next-generation technologies like Wi-Fi 6/6E and private 5G.

To discuss further, please reach out to [email protected], [email protected] and [email protected].

Check out our webinar, Top Emerging Technology Trends: Six Things Sourcing Needs to Know in 2023, for insights on how to stay ahead of emerging technology.

3Cs of Emerging Risks – How Insurers Can Capitalize on the Opportunity | Blog

Insurance carriers need to transform their risk function, become more agile, and proactively create new offerings that protect against the threats of 3Cs: climate risk, cyber risk, and crypto risk. Read on to learn how this environment can create opportunities for insurers.

In today’s evolving risk landscape, insurers need to seek new technologies to improve efficiency, streamline workflow, and fill coverage gaps. Insurers must carefully navigate the detrimental effects of these volatile threats and evolve from being risk insurers to risk guardians. But are insurers putting enough emphasis on exploring the lurking threat areas that can pose imminent risks? Let’s take a look at how this will reshape the insurance industry moving forward.

Hardly anyone could predict a global crisis such as COVID-19 leading to insured losses amounting to nearly US$44 billion, making it the third most costly catastrophe to the industry. After any such black swan event, insurers need better preparedness and foresight to manage their response. The impact of unforeseen risks is becoming increasingly evident. Insurers need to foresee, pre-empt, and prepare for future risks to reduce uncertainty, and underwrite risks in a better way.

Due to spiking losses caused by emerging risks in insurance, traditional rating models are losing relevance to advanced solutions developed by InsurTechs and niche solution providers that enable data-driven decision-making powered by next-generation technologies such as Artificial Intelligence (AI)/Machine Learning (ML) and internet of things (IoT).

With insurance products being largely commoditized, carriers need to differentiate their offerings by rapidly creating newer products for emerging risk segments. We have explored three key emerging risk segments that are complex to evaluate and increasingly gaining prominence, as illustrated below:

Picture1 3
Exhibit 1

Market landscape and challenges faced by Insurers

  • The pandemic forced insurers to adopt newer technologies, scale up digital-first operations, and expand data estate leading to added risk and exposure. The average data breach costs jumped about 13% from 2020 to 2022, according to the IBM Cost of a Data Breach Report 2022
  • The increasing frequency and costs of extreme weather events is putting a greater burden on insurers. Traditional insurer risk models are not sufficient to face the challenge of accurately capturing and testing climate-related risks
  • Cryptocurrency presents a diverse risk landscape. Risky investments in digital assets and unexpected losses tied to cryptocurrency curtails their viability, triggering surety claims. Product development and coverage pricing become challenging because of the dynamic nature of these assets

In response to the challenges illustrated in Exhibit 2 below, insurers need to assess the risks and create personalized products and zero-touch claims processes.

Picture2
Exhibit 2

Next steps in the right direction

With rising losses, insurers can no longer shut their eyes to the devastating impact of these emerging risks on pricing, underwriting, and investment decisions. Insurers need to strategically rethink their risk function.

Carriers must prioritize investment bets across the insurance value chain and evaluate InsurTechs and specialists that bring in niche talent, industry expertise, speed, and experience to help them meet their key business priorities.

According to Everest Group research, specialist providers (illustrated in exhibit 3) can act as catalysts for value realization by quantifying the financial impact of climate change, providing comprehensive cyber risk visibility, and offering innovative digital asset protection solutions.

Contextualized solutions from InsurTechs are gaining prominence to fill capability gaps, enhance value propositions, and streamline workflows across the insurance value chain.

Picture3
Exhibit 3

Let’s explore some of the solutions providers offer for addressing the 3Cs of emerging risks in insurance.

Climate risk:

  • The quantitative consequences of risks must be appropriately assessed and addressed to minimize the impact. Real-time analytics providers use resiliency insights, risk engineering, probabilistic hazard maps, and historical catalogs to recognize the likely risk from natural disasters across the globe
  • Insights on possible hazards can be conveyed via geospatial web-based applications, reports, or application programming interfaces (APIs). Using asset and portfolio-level climate risk analytics, insurers can tap into these insights that affect crucial aspects of the value chain, starting from product development and portfolio planning to underwriting and pricing

Cyber risk:

  • Cyber risk analytics platform providers use telemetry and threat intelligence from across customer workloads, endpoints, identities, IT assets and configurations, DevOps, AI, and blockchain. Using this intelligence, they identify and map shifts in adversary tactics and create actionable data to automatically prevent real-time threats
  • As insurers navigate through uncertainty, they need to tap into the plethora of data they possess along with third-party data to unlock immense value. They must infuse data analytics at every step, starting with identifying, protecting, and detecting cyber-attack risk to proactively computing the cyber control performance. This will enable early identification of weaknesses and detect advanced attacks

Crypto risk:

  • Storing crypto assets is creating new risks. To quantify loss exposure, actuarial teams can draw on forecasting analysis of cryptocurrency crimes to build actuarial models around cold wallets (coverage against damages or theft of the physical storage device) and hot wallets (coverage against abuse of the private key that enables access to digital assets)
  • Insurers need to develop the tools to implement dynamic policy limits/pricing that increase or decrease based on the price changes of these assets, enabling insurers to respond and act upon real-time market changes and ensuring the policyholder is always protected even with innumerable value fluctuations during the policy period

Insurers have a critical role in leading society to navigate these looming threats. Carriers need to change their approach, become more agile, and proactively build products while safeguarding these risks.

It has never been more important to assess and address the 3Cs of insurance risks. To learn more about them in detail, check out our Insurance Solutions Specialist Trailblazers – 2023.

To discuss emerging risks in insurance, please reach out to [email protected], [email protected], [email protected], and [email protected].

The Role of Experience Service Providers (ESPs) in Extracting Value from Brand Communities | Blog

Through brand communities, companies can gain loyal, engaged advocates and customer insights that are key to personalization. With the help of engagement service providers, enterprises can realize tremendous business value by using this marketing channel. To learn more about the value of ESPs in unlocking the full potential of brand communities, read on. 

Why are brands suddenly talking about communities?

The hunger for social interaction and human connection that started during the pandemic has not subsided, fueling the continued growth of niche communities on social media platforms and offline self-help groups. Companies are realizing that strong brand communities can help create long-term brand advocates and have many other benefits.

Influencer marketing and social media marketing are proliferating – from thriving online blockchain NFT communities such as CryptoPunks to strong offline communities that are avenues for in-person events like fitness brand Gymshark.

How can brands leverage communities for personalization?

With Google sunsetting third-party tracking cookies, marketers will need to quickly adjust their strategies to use first-party data directly from customers to champion true personalization.

Beyond solely capturing behavioral first-party data, brands have an opportunity to incentivize customers to voluntarily share zero-party data that a customer intentionally and proactively shares with a business, which will be paramount for personalization.

This is where brand communities come to the rescue – making highly credible customer data available on both an individual and aggregated cohort level, expanding the scope for effective customer engagement.

In addition to being a source of high-quality, sustainable customer data, let’s explore how communities also can help brands in several other enticing ways.

 Six possibilities that come with brand communities:

  • Actionable insights across the customer journey – Starting from the discovery phase with display ads and FAQs to building loyalty through customer stories and peer answers, communities help brands engage with customers across all touch points and gather meaningful insights to incrementally enhance customer experience
  • Self-sufficiency mindset to minimize support cost – Most customers are self-solvers and communities give them access to the ears of other customers facing similar issues and multi-department company teams in one place. This leads to faster problem resolution for customers and reduced support costs for enterprises
  • Co-creation of products – Communities can help product teams gather continuous customer feedback for testing concepts, validating roadmaps, and prioritizing product backlogs at every stage of the product planning lifecycle
  • Acquisition through advocacy – Customers tend to trust other customers when they share testimonials. Brands can leverage communities to organically acquire new customers by identifying brand advocates and incentivizing them to share their experiences
  • Experience-based marketing for retention – Brands also can use these platforms to create engaging experiences such as competitions, events, discussion boards, and surveys, keeping customers hooked and further enhancing retention
  • Reusable user-generated content – Community-created content such as food reviews, skincare routines, fashion looks, or DIY projects can be reused in emails, ads, product pages, etc. to drive revenue and cut content creation costs

How can ESPs help brands build sustainable communities?

While communities bring a plethora of opportunities for enterprises to meet their personalization goals, brands struggle to extract tangible Return on Investment (ROI) from community engagements because they frequently lack a sustainable customer engagement strategy.

Also, when it comes to choosing the right technology platform for building communities, the extremely fragmented technology landscape makes it difficult for brands to evaluate the right fit for their custom needs.

This is where the role of ESPs becomes extremely crucial, as illustrated below.

Exhibit 1: The role of ESPs in extracting value out of brand communities 

Engagement strategy ESPs need to devise a strategic implementation roadmap in collaboration with creators and influencers to create impactful communities for brands from the ground up. They also need to provide hand-holding support to brands who have been unable to scale their community efforts due to the lack of strong engagement strategies
Technology implementation ESPs will need to either partner with existing community platform vendors such as Tribe and Vanilla Forums or create their own tech landscape for embedding data inputs from community platforms into customer data platforms (CDPs). They will need to meld insights from communities to continuously enhance the customer’s 360-degree profile for personalization
Managed services (experience operations) Since communities take a longer time to generate value and need continuous content and security support, ESPs can provide the benefit to upstart communities of already having technology expertise and also deliver support services to brands with existing communities

Investing in creating a new successful community might seem like a daunting task, but enterprises need to draw on learnings from leaders such as Starbucks, Harley-Davidson, Sony PlayStation, and SAP, which are already reaping significant benefits from their communities.

ESPs also need to spread their knowledge and educate clients about this largely untapped market and begin building their tech ecosystem for this opportunity to get ahead of their peers.

Promising outlook for ESPs

With skyrocketing customer acquisition costs, relying on growth through paid media to create truly personalized experiences becomes increasingly difficult. Adopting cost-effective alternatives for achieving sustainable customer loyalty is crucial for enterprises. Successful brand communities can become the secret sauce for gaining long-term competitive advantage in the race for hyper-personalization.

ESPs will play a crucial role in actualizing the returns from communities for enterprises. Providers need to kick-start the process by educating clients about the tremendous benefits of using this marketing channel while also building robust technology architecture to support long-term business outcomes.

To discuss further, contact [email protected] or [email protected].

Learn more about how to create hyper personalized customer experiences in our webinar, Strategies for Customer Experience (CX) Success in an Uncertain World, for recommendations on what to prioritize to deliver exceptional customer experience.

ChatGPT – A New Dawn in the Application Development Process? | Blog

ChatGPT, the advanced Artificial Intelligence (AI) chatbot that’s taken the world by storm, can potentially accelerate various stages in the Software Development Lifecycle (SDLC), from gathering requirements to design and testing, and also enhance developers’ productivity, among other benefits. But it still has limitations. Read on to learn more.   

ChatGPT made headlines when it reached 1 million users in just five days after being unveiled in November 2022. Not only was the tech community awed, but it also has interested a wider audience, from students to industry veterans, and attracted more than 100 million users by the end of January 2023.

ChatGPT and other AI chatbots, such as DALL-E, are poised to radically disrupt multiple professions, including education and healthcare. In our ongoing coverage of this trending topic, we’ll explore how these recent developments may rapidly advance the application development process.

What is ChatGPT, and why is it creating major upheaval?

ChatGPT (Chat Generative Pre-Trained Transformer) is a chatbot built by AI firm OpenAI. It is based on Generative Pre-Trained Transformer (GPT-3) architecture, a neural network Machine Learning (ML) model that generates human-like responses to natural language text inputs. Its ability to converse like a human, answer follow-up queries, and reject inappropriate queries makes it more special than its predecessors. Its capabilities include language translation, text summarization, and text generation.

We tried our hands on ChatGPT and asked it to write a blog on itself, and the results amazed us. See the exhibit below for the blog that ChatGPT generated.

Picture1 1

Next, let’s explore in more detail how ChatGPT could be embedded in the Software Development Lifecycle (SDLC) to create applications and the associated benefits.

The avant-garde movement in application development

While low-code/no-code and AI-assisted application development made leaps and bounds in this field, ChatGPT has the potential to step up the game even further. This potent AI tool can be used to accelerate different processes at various phases of the SDLC, leading to faster development cycles, enhanced productivity of developers, and quicker value delivery to enterprises.

Here are the potential benefits of each phase:

Requirements gathering: ChatGPT can significantly simplify the requirements gathering phase by building quick prototypes of complex applications. It also can minimize the risks of miscommunication in the process since the analyst and customer can align on the prototype before proceeding to the build phase

Design: DALL-E, another deep learning model developed by OpenAI to generate digital images from natural language descriptions, can contribute to the design of applications. In addition to providing user interface (UI) templates for common use cases, it also may eventually be deployed to ensure that the design of a given application meets regulatory criteria such as accessibility

Build: ChatGPT has the capability to generate code in different languages. It could be used to supplement developers by writing small components of code, thus enhancing the productivity of developers and software quality. It even can enable citizen developers to write code without the knowledge of programming language

Test: ChatGPT has a major role in the testing phase. It can be used to generate various test cases and to test the application just by giving prompts in natural language. It can be leveraged to fix any vulnerabilities that could be identified through processes such as Dynamic Code Analysis (DCA) and perform chaos testing to simulate worst-case scenarios to test the integrity of the application in a faster and cost-effective way.

Maintenance: ChatGPT can significantly improve First Contact Resolution (FCR) by helping clients with basic queries. In the process, it ensures that issue resolution times are significantly reduced while also freeing up service personnel to focus their attention selectively on more complex cases.

While ChatGPT has an important role to play in automating more cognitive tasks in the SDLC, users must be aware that security and privacy concerns with the current version still need to be properly addressed.

Now let’s cover a few issues with the tool.

 Five possible roadblocks to ChatGPT adoption

  • Privacy and security – Privacy and security are concerns with the current tool. As it learns from each query, keying in any sensitive data would have drastic repercussions on enterprises. Amazon has reportedly warned employees to not put confidential data on ChatGPT, fearing security concerns
  • Limited knowledge – ChatGPT currently is not connected to the internet and has limited knowledge of the world and events after 2021, meaning the code it generates will not be in line with the latest security patches
  • Potential Bias – While OpenAI has added guardrails against bias in responses, users can occasionally get around this by rephrasing their questions or asking the program to ignore its guardrails
  • Inaccurate responses – ChatGPT responds to queries based on the patterns it learned from the training dataset and also can generate fictitious responses that cannot be verified for accuracy. Although the tool is still evolving, inaccuracy in responses can be a major hindrance to its adoption
  • Energy Consumption – As an advanced AI-based tool, ChatGPT takes a huge amount of computing power to process the information, leading to high energy consumption and carbon emissions. With environmental, social, and governance (ESG) becoming a key mandate across geographies, enterprises may be apprehensive about large-scale adoption

The way forward

ChatGPT is seeing rampant adoption among the developer community, and as it gains further traction, enterprises need to ensure suitable governance models are in place. Service providers need to collaborate with tech players like OpenAI and DeepMind to proactively shape the market and build capabilities for efficient application development.

As details unfold on how this technology will revolutionize the application development process, enterprises and service providers need to closely monitor this space and make proactive investments – clearly, the cost of missing out is too great.

For our other recent blogs on how ChatGPT will impact various industry sectors, see Can BFSI Benefit from an Intelligent Conversation Friend in the Long Term and ChatGPT Trends – A Bot’s Perspective on How the Promising Technology will Impact BPS.

We’ll investigate the implications of ChatGPT for the technology services industry in more detail in a follow-up blog.

To discuss how ChatGPT will impact the application development process, please reach out to [email protected], [email protected], or [email protected].

Will It Be Happily Ever after Post Veeva-Salesforce Divorce?

With the Veeva-Salesforce marriage splitting in 2025, can the two long-time partners remain business friends? Read on to learn what the end of this life-sciences CRM partnership will mean for each of the companies, enterprises, and customers.

The fairy-tale beginning!

Veeva and Salesforce are the front runners in the life sciences-focused customer relationship management (CRM) and commercial technology landscape, with their exclusive focus on Pharmaceutical and MedTech domains, respectively (with a solid non-compete agreement in place). Veeva originated as a spinoff from Salesforce with the potential to disrupt the pharmaceutical CRM space with cloud software. As such, Veeva CRM was built on the Salesforce platform, and Salesforce has been foundational to the building of Veeva ever since. Very soon after its formation, the newly forged Veeva team started developing life sciences-focused applications, spanning the life sciences value chain areas, on a new platform, Veeva Vault. This platform has an applications suite well-spread across the life sciences value chain areas. To date, most Veeva applications related to clinical operations, quality, regulatory, safety, etc., are hosted on Veeva Vault, while Veeva CRM (including solutions for customer experience management, multichannel engagements, and real-time insights) is hosted on Salesforce.

Mid-relationship crisis!

Too many risks added cracks to the Veeva and Salesforce partnership. Veeva, with its dependence on third-party IT infrastructure (Salesforce and AWS) for Veeva CRM, has always been wary of the risks associated with the partnership structure. Some of the highlighted risks include:

1 2
Exhibit 1: Key risks associated with the Veeva-Salesforce partnership
  1. Suboptimal customer experience: Salesforce (and even AWS) have faced significant service outages in the past, and Veeva knows the repercussions this can have on overall customer experience
  2. Market/geography restriction: Veeva is highly dependent on Salesforce in terms of markets where it can sell its CRM. In addition to this geo-restriction, Veeva also will be left stranded if Salesforce exited any existing markets
  3. Domain expansion restriction: Veeva is legally restricted from expanding into the MedTech CRM domain (where Salesforce is the market leader). This puts a potential roadblock in Veeva’s future expansion strategy (and a possible limiting factor to achieving its goal of US$3 billion in revenue by 2025)
  4. Competitor product possibility: While the same agreement also limits Salesforce from selling its products in the pharmaceutical domain, it does not restrict Salesforce’s customer’s ability (or the ability of Salesforce on behalf of its specific customer) to customize or configure the Salesforce Platform to suit their pharmaceutical commercial operations. As such, Veeva’s current or potential customers can prioritize building custom applications over buying Veeva’s products
  5. High exit/platform shift cost: The cost of shifting the Veeva CRM to an alternate platform is exorbitant. In extreme scenarios, if Salesforce decides to annul the agreement on short notice, it will disrupt Veeva CRM and will massively affect all Veeva customers, leading to an indelible mark on the Veeva brand

The divorce!

In its Q3 earnings call for 2022, Veeva announced that it will not renew its Salesforce partnership when it expires in September 2025. As such, it will be moving the Veeva CRM to the Veeva Vault platform. With the agreement’s five-year wind-down period, existing customers can continue with Veeva CRM on the Salesforce platform through September 2030.

Implications for Veeva

2
Exhibit 2: Implications for Veeva
  1. Superior customer experience: Veeva will be able to offer a better end-to-end experience to its customers with all the solutions and applications (ranging from the clinical and R&D areas to sales and marketing) hosted on a common Veeva Vault Platform. This also will let Veeva provide first-hand and more personalized service (hence, better SLAs) to its customers by leveraging a strong service partner ecosystem that includes partners across avenues (geographies, therapy areas, functions, etc.)
  2. Cost optimization: While Veeva stakeholders cite better customer experience as a key reason to move from the Salesforce platform to its own, a cost-related underbelly exists in this relationship – known as the “cost of subscription service.” This is the cost that Veeva has to pay to host its applications (including Veeva CRM) on third-party infrastructure (such as Salesforce and AWS). In 2022, this cost was equal to 12% of the total annual revenue. Moving Veeva CRM to Veeva Vault will let Veeva optimize this spend from its profit realization equation
  3. Growth: Veeva has outlined a very optimistic US$ 3 billion goal for 2025 (meaning a healthy growth rate of approximately 35% from 2022 to 2025). While its pharmaceutical-focused CRM business is expected to grow, with the Veeva-Salesforce relationship coming to an end, we can expect Veeva to foray into a MedTech-focused CRM as well. MedTech, although a much smaller part of the overall life sciences CRM pie, is touted to grow much faster than other domains. This can be a potential growth engine for Veeva to achieve its goals
  4. No access to Salesforce: Post 2025, Veeva will no longer be able to access Salesforce’s range of accelerators, tools, and partners. On the flip side, this is a potential opportunity for Veeva to beef up its capabilities in these areas. Additionally, with Salesforce out of the picture, Veeva will need to withstand enterprise expectations around scalability, value proposition, and change management

Implications for Salesforce

  1. Loss of revenue: Salesforce will lose the annual subscription service revenue stream coming from Veeva. However, since this amounts to less than 1% of total Salesforce revenue, we do not expect it to create a major dent in Salesforce’s annual revenues
  2. Opportunity to strengthen its life sciences product portfolio: Similar to Veeva’s opportunity to expand into the MedTech space (where Salesforce is the market leader), Salesforce will have the freedom to expand into the pharmaceutical CRM space (where Veeva is the market leader). This is a bigger opportunity of the two, given the larger size of the pharmaceutical CRM market

How should enterprises plan for the split?

Enterprises should start planning their next steps as the two companies go their separate ways. While customers may be concerned about the company’s move from Salesforce to Vault for the CRM offering, an extended period will be available to transition. By mapping out transition journeys today, enterprises will have a better chance for a seamless shift.

Enterprises also can now expect products from both Veeva and Salesforce in the MedTech and pharmaceutical spaces, so life sciences customers can plan out which product they want to run with. As the companies sever ties, however, enterprises will want to be more aware of rising pricing and licensing fees, making it plausible to look elsewhere if the price point and product are no longer a fit.

3
Exhibit3: What should enterprises do?

1 Pharmaceutical includes pharmaceutical and biotechnology industries for human and animal treatments.

If you have questions about current CRM trends or would like to discuss developments in this space, reach out to [email protected] or [email protected].

Discover more about the current CRM landscape and explore customer experience strategies for life sciences enterprises in our webinar, How to Deliver Hyper-personalized Customer Experiences in Life Sciences.

Everest Group’s 3-R Framework: Optimizing the SaaS Spend | Blog

With a looming recession and high inflation combined with the tech talent crisis, SaaS spend optimization has become a key priority as companies seek to spend less but maintain functions and user experience. By following the 3Rs (remove waste, reduce duplication, and right-size requirements), enterprises can capture greater value. Read on to discover how using this framework can optimize SaaS spend.

SaaS (Software as a service) is perhaps one of the most widely used and discussed topics in large tech forums as well as large and small enterprises. This is logical, given the ease of use, versatility, and cost-effectiveness of SaaS offerings.

The days when software licenses were installed from a CD are long gone. Today, anyone with a personal computer and internet connection can buy SaaS licenses/subscriptions at the click of a button with a credit card and use it almost instantly.

The SaaS industry has rapidly expanded to include a plethora of plug-and-play applications for small, medium, and large enterprises. SaaS spend for enterprises continues to increase by 15-20% each year. On average, enterprises with more than $1 billion in revenue use more than 100 different SaaS applications.

However, this significant and rapid proliferation of SaaS has also eaten up huge chunks of IT budgets. While IT teams strive to enhance user experience and shorten time to market by leveraging the endless possibilities of SaaS-based applications, procurement and finance teams are focusing on maximizing their ROI.

Chief Information Officers (CIOs) in many enterprises are leading SaaS spend optimization initiatives. With the current macroeconomic factors of a looming recession, and high inflation coupled with high-tech talent attrition, enterprises’ need to scrutinize SaaS spend more closely has intensified.

Enterprises must understand the philosophy behind SaaS spend optimization before starting any cost savings initiatives. The goal is to find ways to efficiently reduce spend on SaaS products/applications without impacting functionality, usability, and user/customer experience. Let’s explore how to accomplish this further.

Negotiating with SaaS providers to get lower rates seems like the most obvious way to achieve savings. While this is one approach, enterprises can pull other levers internally to reduce their overall SaaS spend.

Our 3-R framework can help enterprises get started on SaaS cost optimization initiatives by identifying potential areas of value leakage that can be tackled immediately to realize savings. Using this framework, a large manufacturing client recently identified potential savings of 13-18% in its SaaS spend with multiple software providers.

Below are the 3Rs to examine:

  • Remove waste: Research indicates that, on average, more than 30% of SaaS products that an enterprise purchases are unutilized. But most enterprises do not have a robust SaaS-usage monitoring and tracking practice to discover this. As a result, these unutilized products remain in the tech stack, and enterprises continue to pay for them.

Enterprises can start with a quarterly status check report on usage of all purchased SaaS licenses. If some of these licenses have not been used for more than 90 days, they likely are no longer required. After confirming this with the user department, these unused licenses/subscriptions can be terminated immediately

  • Reduce duplication: SaaS licenses/subscriptions come at a fraction of the perpetual license cost and can be purchased on the go. Most of the time, departments across enterprises purchase SaaS licenses for their incidental requirements with little or no involvement of the procurement function. Since such purchases happen in silos, the enterprise’s tech stack has many applications with significant overlapping features. For instance, two different departments in the same enterprise might buy and use different SaaS applications for project management or team collaboration.

Enterprises can identify applications that have similar functionality using the tracking mechanism that we discussed in the point above to help them find potential applications that could be discontinued.

Using the same application at an enterprise level creates homogeneity and ease of maintenance. It also will result in a single SaaS provider garnering a large part of the spending versus smaller and fragmented spend with multiple SaaS providers for the same requirement. Enterprises can leverage a larger volume of business with a single provider to get better discounts

  • Right-size requirements: Most SaaS providers have multiple editions of their products. For instance, ServiceNow has requester, approver, and fulfiller roles; Microsoft has basic, standard, and premium versions of M365. The nomenclature may vary from one SaaS provider to another, but the idea behind having multiple editions is to meet the requirements of different user groups. The basic edition typically has limited features and is the least expensive, while the highest edition has the largest number of features and is the most expensive.

Every user does not need the most feature-rich expensive edition. But enterprises often buy the same editions for all users, resulting in a lot of waste since many users might not require all of the purchased edition’s features.

Enterprises should leverage persona profiling to identify three or four user groups that will need different SaaS editions to optimize their bill of material for SaaS licenses/subscriptions and reduce total costs

As more and more SaaS-based applications get pushed into the market and used by departments across enterprises, SaaS spend will only grow. This creates an immediate need for increased transparency by the IT, procurement, and finance departments to closely examine how SaaS licenses are procured and used. By adopting our 3-R framework, enterprises can gain momentum in their SaaS spend optimization journey.

Are you focused on SaaS spend optimization and interested in exploring this framework? Reach out to Udit Maheshwari or Shikharjit Mitra to discuss the current SaaS market dynamics and how to get the maximum value from SaaS contracts/subscriptions.

Watch our webinar, Top Emerging Technology Trends: Six Things Sourcing Needs to Know in 2023, to align your sourcing teams with the latest technologies and technology optimization.

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