Ronak D, Author At Everest Group

Insurers and AI InsurTech Partnerships | Sherpas in Blue Shirts

July 19, 2018

Insurers are increasingly investing in AI to enhance the customer experience with automated personalized services, faster claims handling, and individual risk-based underwriting processes by empowering agents, brokers, and employees. Our recently released Insurance IT Services Annual Report 2018 found that more than half of insurers are opting to build in-house AI capabilities through hiring, internal training, hackathons, acquisitions, and partnerships with InsurTech companies, while the rest are turning to IT service providers.

Increased InsurTech Investments

The appetite for change within the insurance industry is certainly there. To make that change happen quickly, insurers have been investing in InsurTechs, firms offering technology innovations designed to squeeze out savings and efficiency from the current insurance industry model, to align data and integrate backend systems. Total InsurTech funding reached US$2.3 billion in 2017, a 36 percent increase from the US$1.7 billion recorded in 2016. In 2016, AI and IoT accounted for almost half of the total investment in InsurTech startups globally.

AI InsurTech investment has increased multi-fold since 2016. Seeking access to talent pools, innovative ideas, high speed, and lower cost of innovation, leading insurers have invested in startups including Betterview, Captricity, CognitiveScale, Lemonade, Mnubo, and Uniphore.

And 2018 appears to be spurring even more investments. Indeed, some of the top insurers have created dedicated venture capital arms – e.g., Allianz Corporate Ventures, MetLife Digital Venture, and XL Innovate – to invest in technologies such as voice biometrics, cognitive virtual assistants, speech analytics, telematics, drone imagery, and machine learning.

Strategic Decisions

Research we conducted on 24 leading insurance firms’ investment model suggested that more than 70 percent of their investments in AI InsurTechs are not just from a funding perspective. Rather, they are entering into partnerships with the InsurTechs as a more strategic decision to fulfill their long-term vision of digitalization.

Significant Impact across Insurers’ Value Chain

Process optimization: The majority of the AI InsurTech investments are for automating underwriting policy administration and policy administration, resulting in increased process efficiency. For instance, AXA partnered with TensorFlow to use machine learning to optimize pricing
Product innovation: In addition to fixing processes, insurance companies are partnering with InsurTechs to develop new customized policies and pricing, per user demand through usage-based information. For example, in 2018, Munich Re’s HSB Ventures led a US$16.5 million venture financing for Mnubo, an IoT, data analytics, and AI startup, to build tailored financial solutions to improve the company’s business and facilitate new business models
Customer experience: AI is making traditional claims processing a thing of the past. Companies are pioneering new cognitive solutions that are making the claims process faster, smarter, and more efficient. For instance, in 2018, GENERALI implemented Expert System’s Cogito® technology to focus on registration and claims processing, and to automate the customer email classification, resulting in a swift and smooth claims process and better customer service.

We believe these partnerships create a win-win situation. They give insurers access to the necessary talent pool, latest technology, innovation, and speed they need to thrive, not just survive. And they provide vital to insurers’ ability to compete, and provide InsurTechs with the guidance, infrastructure, funding, and customer base they need to grow.

If you’d like insights on leading InsurTechs and how they’re changing the insurance industry, please feel free to reach out to [email protected] and [email protected].

How Insurers Can Close Their Digital Skills Gap | Sherpas in Blue Shirts

July 2, 2018

Earlier this year, we conducted a research study on how insurance companies are faring in their digital transformation journey. Using our Digital Pinnacle Model^TM analysis framework – which assesses digital maturity – we evaluated 23 insurers that operate globally across 18 dimensions including strategy, innovation, process transformation, organization and talent, and technology adoption.

Our key findings included that:

approximately 70 percent of those we evaluated will increase their investments in digital technologies by more than 6 percent in 2018
although the digital budget is managed by the CIO and CTO organization, 45 percent of it is primarily influenced and led by the CMO, CDO, and business unit leaders
there will likely be a significant increase in demand for some the next-generation technology themes, including artificial intelligence (AI), cloud-based IT infrastructure, Internet of Things (IoT), big data analytics, and robotic process automation (RPA), across the insurance value chain.

While these findings all point to positives in the move to digital, insurers, just like companies in all other industries, are facing significant challenges in finding the right talent and skills to accelerate their pace of digital adoption.

In fact, more than 60 percent of the insurers we studied are facing this major roadblock. We mapped their digital adoption investments against the skills gaps and discovered that they’re in the red zone in cognitive and AI, IoT, RPA, and cybersecurity technology skills.

Now, consider the impact of these skills deficiencies. Cognitive and AI are the future of data and analytics, they will enhance the way insurers operate as well as reach out to consumers. RPA is creating impact by reducing the overall cost of operations, it will help drive significant bottom-line results for insurers. Lack of skills in these areas shall hinder the digital transformation journey for insurers since they are intertwined with each other. For instance, automation is expected to the bedrock for the increased adoption of cognitive technologies in insurance. The lack of cybersecurity skills will hamper insurers’ digital adoption efforts, as security is one of the key demand themes that will provide increased robustness and resilience to their technology architecture.

We recommend a four-fold approach for insurers to succeed in bridging these significant skills gaps.

Adapt

Insurers must adapt to the digital-first talent mandate by prioritizing digital literacy through investments in training, re-skilling, and up-skilling efforts. Insurers must harness the power of technology to bring about change in their business processes. Also, as the playing field in the insurance industry is rapidly evolving, business responsiveness and agility has become a focus area for insurers. Digital Pinnacle Enterprises™ in insurance have prioritized digital learning, and infused areas like intelligence, data, design, and agile with highly skilled resources. They are in a far better position to leverage the investments and manage the trade-offs required in the digital age.

Invest

Insurers must invest in building a talent pool ecosystem through acquisitions or partnerships with niche technology firms (InsurTechs), set up innovation labs, and solve problems using the wisdom of crowd through hackathons and crowdsourcing platforms. One good example of open innovation for lacking digital skills is Allianz offering parts of its Allianz Business System (ABS) through APIs to other insurance companies. Another is Lemonade’s launch of its public API, which allows seamless sales of insurance products on digital media. Still another is AXAs’ use of KASKO’s platform (KASKO is an InsurTech offering digital middleware services) for its travel insurance products, all of which have been branded under the AXA Travel umbrella.

Partner

Insurers need to partner with IT and consulting services providers, and staffing firms, to gain access to a pool of specific next-generation technology talent that will accelerate their time-to-market and time-to-digital-success. Many providers are investing in building solutions/accelerators and assembling digital adoption best practices to partner with insurers on their digital transformation journey. Because of their domain knowledge, the providers can also deliver significant support in identifying redundant processes that could help optimize insurers’ overall IT portfolio.

Cultivate

As talent with digital skills is in competitively short supply, tapping new university and college graduates with digital training is an important way for insurers to fill in gaps. In fact, insurers can partner with universities to drive research and innovation. For example, in 2017, Allstate Insurance Company partnered with the Intelligent Systems Laboratory at Stanford University to better understand the implications of connected cars and autonomous vehicles. Collaborations like these can help foster talent at a very early stage and deliver benefits later.

Digital talent is one of the critical prongs of a viable, sustainable, competitive digital strategy. It will drive the difference between the leaders and laggards, and the survivors and non-survivors, in the rapidly transforming insurance industry.

If you’d like insights on how mature your firm is on its digital journey, please feel free to reach out to [email protected] and [email protected].

Digital Identity Trends in Banking and Financial Services | Sherpas in Blue Shirts

June 7, 2018

The meteoric growth in smartphone adoption, increasing preference for digital-first transactions, and mounting concerns over data privacy and the misuse of customer data are pushing firms in consumer-facing industries – particularly in Banking and Financial Services (BFS) – to make significant investments in modernizing their IT infrastructure.

DI solutions

One of the key focus areas is in digital identity (DI) solutions. And it’s a big focal point: the research we conducted to produce our recently released report, “Securing Digital Experiences in Banking and Financial Services – State of Digital Identity Services Market,” shows that the BFS industry’s investment in identity and access management services will grow at a CAGR of over 13 percent to reach US$5.8 billion in 2022.

But BFS firms aren’t focusing on DI solutions solely for data security-type reasons. In fact, they’ve found that having a robust DI strategy can also help them drive their digital transformation agendas. For example:

Big data & analytics: DI solutions can help avoid unauthorized access to data and insights
Automation: Automating business processes that access data from multiple systems require a DI solution
Customer experience: Identity management tools can help drive a consistent omnichannel user experience
Cloud: DI solutions help manage operational risk of unauthorized access to data on the cloud and digital identity over cloud platforms
Internet of Things (IoT): Devices that interact with the digital ecosystem need to be uniquely identified and authorized for digital transactions.

A Sampling of DI solution Use Cases

With the emergence of data privacy regulations such as the General Data Protection Regulation (GDPR) and Second Payment Services Directive (PSD2), BFS organizations are quickly building their DI capabilities to ensure better protection.

Related: See our latest banking and financial services research

Indeed, many banks are working in collaboration with government institutions to integrate banking and financial services with DI solutions, and are leveraging APIs, biometrics, blockchain, machine learning, and mobile technologies to allow DI solutions to become more secure and accessible. One example is BBVA Compass, which has been actively investing in the DI space through collaborations with fintech startups, hackathons, and establishment of dedicated firms.

Digital Identity Provider Ecosystem

From a country perspective, Estonia was one of the first to embrace DI. It implemented e-Estonia, which allows citizens to manage e-banking services that can be integrated with other e-commerce solutions, such as PayPal.

Increasing demand for DI-based offerings is also proving to be a breeding ground for new tech-startups, Indeed, the DI provider ecosystem is expanding well beyond the traditional tech vendors/service providers (HPE, IBM, etc.) and consulting and system integrators (e.g., Accenture, Deloitte, and DXC.) All these types of DI tech vendors are embedding AI and machine learning to enhance the capabilities of their DI solutions. For example, in 2018, Mitek, a DI verification company, acquired A2iA, an artificial intelligence (AI) and image analysis company that uses AI and machine learning to create algorithms that process checks, IDs, and documents.

While the current environment requires banks to evolve and actively invest in DI, it also presents them with a unique opportunity to reposition themselves as trustworthy identity aggregators/providers, as they already have secure systems in place to keep information safe. And some banks are already exploring the possibilities of generating revenue from DI solutions. For example, Capital One is one of the first banks in the United States to test if other businesses are willing to pay to check users’ identities with its DI products. And Rabobank entered into a partnership with Signicat in the Dutch market to offer such services as well.

Instead of treating DI as a problem, BFS firms need to embrace it to accelerate their digital transformation journeys, and build new business models to enable revenue opportunities. To further understand the major trends in the DI market, read our report entitled, “Securing Digital Experiences in Banking and Financial Services – State of Digital Identity Services Market.”

Anatomy of Digital Transformation in BFS | Sherpas in Blue Shirts

May 24, 2018

Everest Group recently conducted a study with 55 banking and financial services firms to evaluate their digital capabilities in areas including strategy, organization and talent, process transformation, technology adoption, and innovation. Here are the primary insights we collected from that study.

Investments in Digital Technologies are Increasing

More than 60 percent of BFS firms have invested in exploring the various use cases in cognitive- and AI-driven technologies. Typical use cases include helpdesk automation using chatbots and other cognitive capabilities for functions such as sales & marketing, data entry, credit assessment, and information gathering.

The AI Transformation Wave is Hitting the Front-Office

BFS companies are increasingly leveraging AI-enabled transformation in areas where there is significant customer interaction. So personal finance virtual agents, voice assistants for account servicing, voice-based payments and account authentication, and intelligent message-based account servicing are gaining traction. Not surprisingly, Millennials and a new breed of mass affluent (per The Financial Brand, this segment generates up to 70 percent of banks’ and credit unions’ total retail profits, even though they only make up less than 30 percent of the customer base) are extensively using these solutions for advisory and servicing assistance.

BFS Firms are Increasingly Emphasizing Their “Change” Agenda

Our study indicates that BFS firms will increase their digital investments by 9 percent in 2018. This is particularly driven by the need to change in response to the evolving regulatory regime, and customer demand for responsive and agile applications. For example, in the U.S., deregulation could pave the way to a shift in the utility space. In the U.K., the Second Payment Services Directive (PSD 2) has heralded an open banking revolution that forces banks to release their data in a secure and standardized format.

The Talent Gap is a Key Challenge for Digital Adoption

Although BFS firms are accelerating their adoption of AI-driven applications, they’re facing significant scaling challenges as digital talent is scarce and in high demand. The biggest talent shortage areas include cybersecurity experts to handle stringent regulatory pushes – such as GDPR in the EU – and those with deep knowledge of big data, without which enterprises can’t realize their full potential in enhancing the technical and functional capabilities of their internal teams on leading big data platforms.

Our Recommendations

To stay ahead of the competition and remain relevant in the market, BFS firms must invest in enhancing the five following capabilities in alignment with their digital journey:

Strategy – Outline a clear vision, metrics, and realistic goals for focused and scalable digital adoption
Organization and talent – Acquire digital talent through reskilling and retraining existing employees, as well as recruiting talent from outside
Technology adoption – Adopt niche digital technologies at speed and scale with higher focus on AI, analytics, security, and risk
Innovation – Continually source new ideas for innovation, and embed human-centric design in the organization’s DNA
Process reimagination – Transform and automate internal business processes to remove inefficiencies.

Related: Learn more about our digital transformation analyses

The above recommendations translate to a customer-focused triple mandate of Experience, Efficiency, and Ecosystems (E3) for banks. The evolution from a product-centric to a customer-centric mindset requires an open banking ecosystem to orchestrate the lifestyle services that individuals or enterprises demand from their financial institutions at speed and scale

This metamorphosis will be challenging not only because of the complicated regulatory regimes and resilient legacy structures, but also the rise of non-traditional competitors.

Please feel free to reach out to [email protected] and [email protected] to diagnose your firm’s digital adoption maturity.

Tomorrow’s Talent is Today’s Challenge! | Sherpas in Blue Shirts

May 17, 2018

Advances in new digital technologies, the emergence of new competitors, new sourcing models, and changing customer expectations are dramatically changing the type of IT skills enterprises across industry verticals require. And, with new service delivery paradigms such as automation, agile, and Artificial Intelligence (AI) becoming mainstream, the underlying service delivery models to support the new talent demand profile are also undergoing significant changes. We expect technology themes such as data management and analytics, omnichannel customer experience, and cloud adoption to dominate near-term demand, and cybersecurity, Service Oriented Architecture (SOA)-based application design, and agile delivery methodologies to become mainstream.

So, what does this mean from a talent perspective? Below are four takeaways from Everest Group’s recent research, much of which is detailed in a newly-released viewpoint titled Closing the Gap – The Future of IT Skills in the United States.

1. New Role Creation

To support their business initiatives in the changing technological landscape, enterprises will have to create new roles. Examples of these include:

Chief Digital Officers (CDOs) and digital strategists to drive the adoption of design methodologies
Chief Innovation Officers (CIOs) to source and evaluate disruptive ideas from innovation in technology and business models
Anthropologists and psychologists to help foster human-centered design thinking
Data architects and data scientists to build a holistic data strategy and generate insights to offer tailored experiences
Agile coaches and scrum masters to deliver using the agile methodology at scale
Enterprise security engineers to design and evaluate security measures across all phases of SDLC
Automation architects and Machine Learning (ML) experts to develop automated scripts.

2. New Architecture

The technology revolution is leading to an integrated “thin slice” architecture that is enabled to deliver end-to-end experience transformation. This full-stack structure is a sharp deviation from the legacy silo-based architecture that has fundamentally different attributes for delivery of technology services in enterprises. From a talent perspective, traditional siloed factory models are evolving into smaller teams/pods with capabilities cutting across areas such as application development, infrastructure support, and security. Demand for full-stack engineers will increase significantly as the demand for this future integrated stack becomes more prominent across enterprises. Enterprises will need to invest in upskilling and cross-skilling their existing talent at scale and speed to be able to pivot to this new model.

3. Demand Shift for Tech Skills

Emerging technology themes will increase demand for some tech skills, and reduce demand for others. For instance, we expect demand for emerging skills such as Go and R programming to increase considerably, as enterprises explore the adoption of big data and AI solutions. On the other hand, we expect demand for skills specific to middleware tools, such as TIBCO, to remain low-medium, driven by increased adoption of offshoring and automation. Enterprises must have a good understanding of hard-to-hire skills in order to effectively chart out their talent roadmap. Key decisions such as local hiring versus offshoring will also revolve around expected demand and supply for skills.

4. Non-Technology Industry Verticals Demand Increasing

Demand for tech talent from non-technology industry verticals is increasing. From banks to retail firms to healthcare providers, technology-led solutions such as robust mobile applications and chatbots are being leveraged to enhance the customer experience. With enterprises focusing on building in-house capabilities, competition for tech talent has increased significantly in the past two to three years. Everest Group’s recent analysis indicates a higher demand from non-technology industry verticals for emerging skills such as configuration management tools (e.g., Ansible, Chef), JavaScript libraries (ReactJS, AngularJS), datacenter solutions (e.g., skills in handling VMWare, AWS, Azure), and automation tools, as compared to demand for basic skills like programming languages such as C and SQL.

To learn more about the emerging technology themes, their impact on talent requirements, the skills we expect to gain importance in the future, and their supply outlook, please read our viewpoint on skills of the future in the U.S. And feel free to share your opinions and stories on how you are managing tech-talent directly with us at [email protected] or [email protected].

AI projects in Insurance are Moving from Pilots to Business Programs | Sherpas in Blue Shirts

May 4, 2018

Insurers are rethinking their business ethos to become protectors instead of payers. The insurer of the future is aiming to develop a customer-centric value proposition. Carriers are looking at developing innovative products that are contextualized to meet evolving customer needs. And the insurance distribution strategy is shifting to adapt to new product offerings, client needs, and digital technology-led disruption in the ecosystem.

Not surprisingly, insurers are adopting AI and related technologies to drive these capabilities. According to our just released Insurance IT Services – Annual Report, the top three business objectives insurers are trying to achieve with AI projects are customer experience, process optimization, and product innovation.

AI Trends in the Insurance Industry

Our annual report studied 80 unique AI initiatives by global insurers to unearth AI trends in the insurance industry. Here are the top ones we identified.

Capabilities

Approximately 53 percent of insurers are developing in-house capabilities for their AI initiatives. But many have large skills gaps that will inhibit their ability to scale pilot projects and realize the expected value from AI initiatives.

Embedded intelligence

Insurers have accelerated their focus on embedding intelligence across the value chain, with higher adoption of AI for sales & distribution and underwriting processes.

Self-service

Insurers are adopting intelligent self-service AI tools to enhance the customer experience.

Mid- and back-office process value

The value delivered through front-office AI initiatives such as chatbots is limited. But real value can be unlocked when AI is applied to optimize mid- and back-office processes such as agent support and claims management.

Data

While structured enterprise data remains the major source of data for insurers (52 percent, per our research), the connected ecosystem – i.e., data from IoT-based devices – is gradually gaining traction, at approximately 35 percent. As insurers evolve in their AI journey, deploying AI and machine learning (ML) to leverage unstructured data from third-party sources and connected ecosystems is likely to increase. But as of today, enterprise data silos, legacy systems, and lack of interoperability standards to tap into the connected ecosystem and third-party data are slowing down insurers’ AI initiatives.

Some Standout Examples

Many insurers have made progress in deploying AI and ML to their data and are starting to see quantifiable results. For example:

Zurich Insurance deployed AI in its personal injury claims process. The company claims that AI has helped it save 40,000 work hours, and reduced claim processing time from 58 minutes to five seconds per medical report
ICICI Lombard launched a chatbot called MyRA to underwrite two-wheeler, fire, and burglary insurance for SMEs. Since its launch, MyRA has been engaged in 65,000 customer interactions, and has sold more than 750 policies without any human intervention.

AI has the potential to deliver significant value to insurers and their customers. To learn more about how it can impact your business, our recent Insurance IT Services – Annual Report is packed with data and our take-away insights from 80 unique insurance firm AI projects. In it, we outline how AI implementation is impacting the insurance industry, and present various AI use cases across the insurance value chain.

Please write to Ronak and Priyanka to discuss how you’re adopting AI in your insurance business processes.

How GICs are Unblocking Blockchain Value | Sherpas in Blue Shirts

March 21, 2018

At a NASSCOM-hosted event earlier this year, I moderated a roundtable discussion on “Blockchain: Looking beyond the hype” among executives from 20+ GICs. The discussion quickly elevated from the “what” to the “how and how not” to do blockchain initiatives.

Here are some of the key take-aways from the session, in part sparked by discussions on some of our blockchain research.

Blockchain is Inching Closer to Prime Time

Blockchain has crossed the chasm: With the definitive number of live deployments and successful PoCs, we believe that the early adopters will be able to demonstrate early results by year’s end. Because timelines for technology evolution have compressed, we also expect a wave of fast followers will invest in this space.

GICs are Taking the Lead

GICs’ innovation can transform them into Global Capability Centers (GCCs): GICs are leading blockchain initiatives, from education, evaluation, use-case design, and PoCs to live deployments. They are also externalizing the technology solutions to create newer business and revenue models, and driving blockchain adoption at speed and scale. And their R&D investments are extending beyond live blockchain deployments to patent filings to retain competitive advantage.

Building a business case: GICs are researching every possible use of blockchain in their industry. We are seeing GICs helping enterprises across a variety of use cases in insurance, capital markets, banking, supply chain, education, and technology – and one leading financial services GIC prioritized four use cases from a long list of more than 40. A framework, like the one we recently published, will help firms prioritize business use cases that are ripe for blockchain adoption.

GICs and the ecosystem: Blockchain adoption requires significant orchestration among governments, regulators, technology vendors, enterprises, startups, and customers to create a win-win environment for all. GICs are not just consortium and forum participants; they are highly active contributors to the advancement of blockchain technology maturity.

Talent is not a huge roadblock: Leading adopters have started by building a core blockchain team that invests its time in understanding the ecosystem, undergoing training, and exploring multiple use cases. Lead steers we’ve spoken with stated that re-skilling efforts to build a blockchain developer pool have not been the uphill battle that leading blockchain consulting firms hypothesized. They’ve approached re-skilling by driving blockchain awareness to a broader group in the firm, and then identifying a pool of talent with adjacent skills, e.g., Angular JS developers to be trained on solidity, for the first wave of training. More developers join these teams as they scale up. Enterprises are conducting a series of hackathons to tap into the talent pool – both in the GICs and the extended ecosystem – and provide on the job training opportunities.

On the Technology Front

Evolution of the enterprise blockchain technology stack: Enterprises are taking a fundamentally different approach than the public or cryptocurrency related initiatives in building their blockchain technology stacks. Blockchain-as-a-service vendors have helped manage the complexities of the blockchain stack for early trials and pilot stage activities. However, early stage trials that did not plan for the blockchain technology stack for the live deployment phase have found it difficult to scale up their pilots. Node-level identity and access management, interoperability, quality assurance for smart contracts, and current scalability limitations of existing blockchain consensus mechanisms and transaction validation protocols are some of the key challenges highlighted by early adopters.

Sidechains are a key feature of the enterprise blockchain tech stack, not limited to cryptocurrencies: Several enterprises are solving the data privacy issues by creating both off-chain and side-chain applications that can then write final-hash on the blockchain network. This unique approach can accelerate blockchain adoption for specific use cases. However, interoperability on different blockchain platforms is a key challenge.

With all this, there should be little doubt that GICs are quickly evolving into global capability centers that further the digital transformation agenda for the enterprise.

As we continue studying enterprises’ and GICs’ blockchain journeys, we’d love to hear about yours. Please share it with me on [email protected].

And please participate in our ongoing GIC Digital Maturity Pinnacle Model™ survey to learn more about successful GICs’ digital journeys and see how your GIC compares.

Blockchain: Making the Global Supply Chain Healthier | Sherpas in Blue Shirts

March 7, 2018

In 2015, Denver-based Chipotle Mexican Grill suffered a major crisis with an E. coli outbreak that left 55 customers ill. Sales plummeted, news stories and investigations shattered its reputation, and the restaurant chain’s share price dropped 42 percent, to a three-year low, where it has languished ever since. Why couldn’t Chipotle prevent or contain it? What triggered it?

The answer lies in an ever-present scenario companies face – dependence across multiple vendors and lack of transparency and accountability across complex supply chains. A radical solution, using blockchain technology, is rapidly emerging, and is being explored by a slew of startups and corporations.

Blockchain allows supply chain managers to attach digital tokens – a unique, negotiable form of digital asset – to intermediate goods as they progress along the production, shipping, and delivery phases among different supply chain players. This gives businesses far greater flexibility to find markets and price risks, by capturing the value invested in the process at any point along the chain.

Blockchain in Action

One example of blockchain in action is Walmart working with IBM and Beijing’s Tsinghua University to follow the movement of pork in China. Another is BHP Billiton, a mining giant, using the technology to track mineral analysis conducted by outside vendors. Everledger, a dynamic startup, has already uploaded unique data on more than a million individual diamonds to a blockchain ledger system, thus developing quality assurances and helping jewelry market associations comply with regulations barring “blood diamond” products.

“Smart contracts,” an application based on blockchain technology – buoyed by advances in chip and sensor technology – is an especially powerful option providing traceability and automation benefits. These contracts can grant different vendors special, cryptographic, and encrypted permissions, can be automatically executed by an autonomous system, and provide visibility on each other’s activity to all members of a supply chain community.

This kind of provable, transparent credentialing will be especially important for additive manufacturing, which is central to the dynamic, on-demand production model of the burning Industry 4.0 movement. For instance, operations and maintenance crew in an aircraft carrier need to have absolute confidence that the software file they downloaded to 3D print a new part is safe and not hacked. One of the most compelling arguments for blockchain is that it can help eradicate the trust problem in supply chains, without which the sophisticated, decentralized, IoT–driven economy many are projecting might be impossible.

Obstacles to Overcome

While the need for efficiency improvement and information aggregation suggest blockchain technology could deliver vast supply chain savings for companies everywhere, there are formidable obstacles to overcome first, such as:

Development and governance of the technology is a big concern, with two imperatives – global supply chains anchoring to a public blockchain (that no entity controls) to encourage free access and open innovation, and private or closed ledgers to protect companies’ market share and profits. This conflict leads to a couple of challenges:
- Achieving global economic capacity for the most significant public blockchains, digital currency and smart contract platforms becomes constrained by divisions in open-source communities, making it difficult to agree on protocol upgrades
- There needs to be interoperability across private and public blockchains, and this will require standards and agreements
There exists a complex array of regulations, maritime law, and commercial codes that govern rights of ownership and possession along the world’s shipping routes and their multiple jurisdictions. It will be extremely difficult to marry this old-world body of law, and the human-led institutions that manage it, with the digitally defined, dematerialized, automated, and denationalized nature of blockchains and smart contracts.

Despite these challenges, positive steps are being taken. For example, Hong Kong recently formed a Belt and Road blockchain consortium that seeks to bring a structure and order along with ICANN (Internet Corporation for Assigned Names and Numbers), an international, private sector–led global administrator and adjudicator.

While it might be too early to say that blockchain entirely solves the global supply chains issues, we believe any system that promises to enhance transparency and control for businesses and their customers, while also countering inter-commercial trading frictions, is worth exploring.

An increasing number of investors, businesses, academics, and even governments are starting to view blockchain technology as a much-needed platform…are you with them?

Don’t Turn Cross-selling In Banking into A Villain | Sherpas in Blue Shirts

October 14, 2016

A critical factor behind the Wells Fargo fiasco was the incentivizing of employees based on their ability to achieve their sales targets by cross-selling products. While this is the easiest and lowest cost model for defining and measuring sales team performance, it can lead to fraud if left unchecked. In Wells Fargo’s case, over 5,300 employees were fired for fraud that occurred across multiple years and led to the exit of CEO John Stumpf.

The scandal raises serious questions. Did Wells Fargo not have the data and analytics tools needed to identify fraud that had been going on for so long? Did the bank’s processes not have a channel to capture customer feedback on transactions to raise a flag for the fraudulent activity? Can we create employee performance measures other than sales targets?

To answer these questions, I believe banks need to go back to services marketing basics 101:

Measure customer acquisition costs
Develop mechanism for measuring customer satisfaction (in almost real time, on an ongoing basis for consumers in the age of connected ecosystem)

If Wells Fargo had measured the cost of acquisition per customer and had the ability to drill down at the sales representative level, it would have realized that the 5,300 fired employees had unbelievably low cost of customer acquisition for the sales they made over the years – meaning they were doing amazing, or fraudulent, work. Whichever the case, the bank would need to explore further.

These days, measuring customer satisfaction after every transaction is the norm in many industries. After every call I make using Skype, the application asks me to rate my experience. The same is true for every Uber ride I take, and each time I book a flight online.

Can’t banks do this? I believe they can. It makes sense for multiple reasons:

In the age of agile development and DevOps, driving continuous integration and continuous deployment the customer feedback loop needs to be real time for the customer experience and service design teams to actually drive continuous improvement of their systems
This helps banks develop a rich data set that can be used to drive process and product design and improvements, and also identify fraud
The data can help improve the customer experience, and demonstrates to consumers that their feedback is valuable. Customers can be enticed to leave feedback through offers of loyalty points, which in turn can help improve customer retention
This approach drives customer centricity, and ensures designing processes that are aligned to the needs of customers
Banks can use this data to predict the need for different segments of customers, and help drive personalization of user experience

While there are many more reasons why measuring customer satisfaction is valuable for banks and customers alike, let’s dive a little deeper into the idea of using it to measure sales team performance.

Banks can use the customer satisfaction measuring mechanism to capture feedback that enables measurement of the effectiveness and value added by the sales team member across the customer lifetime journey, from being on-boarded to systems to purchasing products to retiring products.

By embracing a customer-centric design philosophy for all its internal processes (not just for its products and services), including performance appraisals of all employees, with every KPI being linked to customer satisfaction, banks will be able to create a consumer-centric enterprise.

True that Wells Fargo’s case has made the idea of cross-selling a villain. But we must realize that its debacle was also caused by other more pressing issues such as top management failure to respond to the matter in time, lack of data and analytics solutions to identify fraudulent transactions, and the organization culture that promoted unethical behavior.

FinTech players in the market are looking to disrupt traditional financial services players by leveraging technology and designing for customers. However, they face challenges in terms of gaining customer trust and loyalty while building scale. Traditional banks boast of having scale and years of customer trust. But, we are witnessing erosion of that trust. While financial services enterprises are investing heavily to embrace the wave of digital disruption from FinTechs, they need to ensure while they pursue this strategy they continue to protect their competitive advantage of years of customer trust.

Dominating themes at the #NASSCOM Design and Engineering Summit 2016 | Sherpas in Blue Shirts

October 4, 2016

Digital technologies are fundamentally changing the demand ethos of the US$75 billion Engineering and Research and Development (ER&D) global sourcing market, which is expected to grow at a CAGR of more than 18 percent over the next five years. With rapidly evolving consumer needs, an increase in global regulatory pressures, the rise of the shared economy, increasingly complex security needs, and technology’s shift from enabler to disruptor, following are the major themes I expect to dominate the NASSCOM Design and Engineering Summit 2016, which is being held in Bangalore on October 5 and 6:

The connected digital ecosystems: The proliferation of smart devices and radical improvement in connectivity infrastructure are shaping the evolving digital ecosystem of everything. Orchestrating this connected digital ecosystem and creating products that tap into it are creating a new demand portfolio of ER&D services across industries. Think rapid consumerization in the healthcare industry with increasing use of connected smart medical devices, the connected and autonomous vehicles defining the future of mobility in the shared economy, or the convergence of machine-to-machine (M2M) technologies and advanced analytics driving the industrial 4.0 revolution.
Designing for the future: Enterprises must understand the needs of tomorrow’s customers, and will need to push the boundaries of innovation and design thinking to engineer products that are at the intersection of leveraging cutting edge technologies and re-imagining processes and business models.
Smart, smarter, and smartest: The rise of cognitive computing technologies has pushed the boundaries of process and task automation to create smart products. Research advances in the field of Artificial Intelligence (AI), machine learning, and edge computing will drive development of products that dramatically improve the user experience, and provide convenience beyond expectations for consumers and employees alike. This creates demand for a talent model with hybrid skills of product engineering and design, domain knowledge, and ability to leverage cognitive technologies.
Making sense of data: Enterprises are collecting a lot of data through a multitude of external and internal data sources, and are looking at how to enhance product design and engineering processes, reduce costs, improve quality, and meet evolving user expectations. Enterprises in the retail, defense, media, and financial services industries have been at the forefront of using data and analytics to answer these questions. Demand from these industries is driven from adoption of further sophisticated analytics initiatives that helps deliver competitive advantage. Industries including manufacturing, energy, telecoms, and healthcare and life sciences are rapidly adopting big data and analytics technologies.
Real use cases beyond the cool stuff of AR/VR: Augmented reality and virtual reality technologies have great potential in areas such as remote monitoring and predictive maintenance, training, and simulated testing environments. Expect to hear more use cases for AR and VR technologies.
Software-defined everything: “Software eats everything” across all industries – software-defined infrastructure, software-defined manufacturing, software-defined networking, software-defined datacenters, and so on. The delivery of software product as-a-service, the ability to remotely support and maintain customer premise equipment, and the increasing demand for configurable over customized software products are creating a new demand paradigm for ER&D services in the software products industry.
Time-to-market: Speed is the new currency in the product engineering world. Sourcing has enabled enterprises not just to reduce costs but to drive agility and flexibility to respond to market volatility and constantly changing consumer demands. As technology becomes core to all activities, concepts such as agile and DevOps are becoming relevant across the ER&D services industry value chain.
Standards, security, and compliance: Security is among three priorities for all C-suite executives globally. In the age of connected digital ecosystems, building security into product design is becoming an absolute necessity. Compliance but is a critical component of the demand driver for the ER&D services industry.

I look forward to interesting discussions on these and other topics with the engineering services enterprises and vendors during the #NASSCOM Design and Engineering Summit. If you’re there in person, feel free to contact me or my colleagues H Karthik and Bhawesh Tiwari.

Click here to read about Everest Group’s latest research on the engineering services global talent spot, and here, here, and here to check out detailed insights from this research.

Author: Ronak D