Life Reimagined with Seamless Travel Experience

1

Reimagining life in every aspect and bouncing ideas that create better experiences is the motto of this blog page. As per the AARP research in 2018, 57% of leisure travelers like to spend time with family and friends, 49% want to relax and rejuvenate, and 47% try to get away from routine stressed life. But the real-life experience of travelers is just the opposite of these expectations. Solutions that offer seamless travel experiences is the need of the day for better leisure outcomes. The ideal travel experience of current generation passengers would include:

  • Real-time journey information delivered to their personal devices
  • Biometric identification to facilitate their travel processes
  • Automation of more airport processes
  • Wait times of less than 10 minutes at security/immigration
  • Bags tracked throughout their journey
  • A human touch when things go wrong

What if a passenger arriving at security and immigration checkpoints has been previously vetted at check-in allowing a seamless, contactless process where the passenger simply needs to look at a smart camera to be cleared and allowed passage? Offering universal travel pass integrating cross-border security checks, hotel check-ins and entire travel life cycle tied with digital identity should be the new mantra of the travel industry.

Such universal travel passes will create a newfound demand for travel consultants to be more integrated with various service providers, making it a lucrative profession. Each traveler will be assigned a passenger record name/record locator so that all the services they opt for will be availed and kept secure, and the travel consultants will be the integral component of providing this.

Seamless universal travel experience is a great value to the travelers. And such a seamless travel experience is becoming a reality with new digital technologies. These technologies can enable travel agencies to transform into ‘digital travel agents’, enabling the booking process to become a trip planning experience, where agents will be able to provide more content, information and booking details. The congruence of technologies like IoT, Cloud, AI, Voice Enabled Devices, Blockchain, and 5G has the potential to offer better experiences to travelers. As tourism continues to grow and route availability continues to shrink, airports are turning to seamless travel initiatives to help passengers stay on the move and increase their satisfaction.

The dominant technologies enabling seamless universal travel experience include,

  • Internet of Things: IoT can create a seamless trip where travelers are connected to their travel agents at every stage. IoT has the ability to connect customers with travel consultation throughout the entire lifecycle of the travel experience. For agents, a global or universal passenger record can allow travel consulting to change according to any requests from the customer. As for travelers, agents can provide a universal ‘travel pass’ that can be used for a trip, without separate boarding passes, hotel check-in, bus passes, and even theme park tickets. This universal travel pass would also handle multiple currencies, where travelers won’t need to worry about exchanging currencies when traveling between different countries.
  • Cloud – Improves the collaboration with travelers for a more personal experience transforming the offline model of the travel agent to have access to all cloud-based bookings regardless of location
  • AI and voice-enabled devices – AI has the potential to transform the inevitable hassles and inconvenience of airport travel into delightful passenger experiences. AI could enable travelers can leave their home with one single biometric identifier – and board a plane or cruise, check into their hotel, and hire a car with that unique identifier. Acuity Market Intelligence forecasts that the total number of airport biometric touchpoints – increasingly AI enhanced facial recognition – at check-in, bag drop, security, and boarding gates will increase at a 27% CAGR from 2019 – 2022. Voice will be the future of booking travel. Travel agents are then able to take advantage of this and sell high value and high engagement products via voice
  • Blockchain – Blockchain technology could develop a ticket-booking solution that integrates multiple agencies – long-distance, regional,  and local agents, including Uber/Lyft car- or any other car sharing firms. With a blockchain based solution, travelers can book their travel with agents participating in the network with just a few clicks on a single website, without the need to switch across multiple sites and providers. The blockchain ledger can then record single customer purchase and even accurately can split the payment among the providers.
  • 5G network high speeds – 5G will give agents a better way to connect with travelers during their trips. If the traveler has a 5G connection, that allows the agent to be able to have a better video call with the traveler, without physically being there with them, assisting them along the way. 5G combining with VR/AR technologies offers a more engaging and immersive booking experience

Travel & Tourism sector should embrace the change creating a mass personalization contextualized to the travelers and leveraging ecosystem working with all stakeholders involved to maximize value leveraging biometrics and universal digital identity for truly seamless passenger experience.

Future of Financial Services Workforce

UntitledFinTech disruptors have been finding a way in by focusing on a particular innovative technology or process in everything from mobile payments to insurance. A forte of technologies “AI-ML-DL-NLP-CV” is fueling the FinTech innovations. The large financial services companies can’t be complacent as FinTechs have been attacking some of the most profitable elements of the value chain and as well as areas which were historically subsidized.

Let us refresh our memory on these AI technologies and their relevance to the financial services industry.

  • AI makes machines to learn from experience and perform human-like tasks – AI offers robotic & intelligent process automation (RPA/IPA) of financial processes
  • ML is a specific subset of AI that trains a machine on how to learn – ML is enabling algorithmic trading lead to better predictability and decisions around credit and consumer lending, thereby lowering risk to the bank or financial institution
  • DL is s a type of ML that trains a computer to perform human-like tasks, such as identifying images – leverage big data (customer demographics, consumption records, etc.) to parameterize a DL model that can simulate the likely response to new product/service configurations (e.g. new credit card with cash rewards, moderate interest, zero interest on balance transfers, etc.)
  • NLP is a branch of AI that helps computers understand, interpret and manipulate human language – NLP is shaping the future of banking with voice assistants and ubiquitous computing.
  • CV s a field of AI that trains computers to interpret and better understand the visual world –  CV is transforming financial services by using appealing visuals and new solutions for a new world where seeing is believing

These new-age FinTech developments are leading to a continuous transformation of the financial services workforce. The changing landscape and evolving financial services resource pyramid is presented in the diagram above. I would like to highlight a few trends reshaping the talent of financial services on this blog post.

  • AI automating business-as-usual activities of financial services: Robots and AI already started addressing key pressure points, reduce costs and mitigate risks. Building capabilities to target a specific combination of capabilities such as social and emotional intelligence, natural language processing, logical reasoning, identification of patterns and self-supervised learning, physical sensors, mobility, navigation and more are in swing. The goal is to look far beyond replacing the bank teller. There are whole categories of work that had not been seen as cost effective to automate. However, with lightweight software ‘bots’, workers are freed up to focus on higher value activities.
  • Changing patterns with Human vs Machines foray: Are financial services firms moving to re-shoring of work with talented machines? The answer seems to be, Yes. In the last two decades, many financial firms have ‘offshored’ repetitive tasks to lower-cost locations such as India, China, and Poland. However, relative costs for labor in those regions have started to rise. Combine this with improvements in robotics and AI capabilities and machines are becoming credible substitutes for many human workers. As the capabilities continue to improve and technology continues to drive down the cost of machines, these forces will combine to spur re-shoring, as more tasks can now be performed at a competitive cost on-shore. Even functions that seem dependent on human input, such as product design, fraud prevention, and underwriting, will be affected. At the same time, the need for software engineering talent will continue to expand
  • It is not just automation, Technology is picking high-end work: ML is enabling next-generation algorithmic trading systems are moving from descriptive and predictive to prescriptive analysis, improving their ability to anticipate and respond to emerging trends. And while algorithm trading programs were once limited to hedge funds and institutional investors, private investors can now get access to them too. AI soon automate a considerable amount of underwriting, especially in mature markets where data is readily available. Even in situations where AI does not completely replace an underwriter, greater automation would allow humans to concentrate on assessing and pricing risks in the less data-rich emerging markets. It would also free up underwriters to provide more risk management, product development advice and other higher value support for clients.
  • While building machines, the real focus is on accessing the necessary talent and skills to execute strategies and win markets: Financial services firms lack the internal knowledge and expertise need to implement a customer-centric approach. For example, a mainframe programmer who maintains a core banking platform may not have the skills or interests to learn to code AI applications. Many senior IT executives, non-IT staff-members, and even technical personnel do not have the skills needed to build and operate an effective digital channel offering. Financial institutions are starting to realize they will need talent with very different skills. This might mean finding more industrial engineers for robotics work, or retraining underwriters to do higher value work once AI is used to automate certain existing functions. But the issue runs deeper than developing a different competency model. First, firms to understand what is already working and what needs to be done differently. This might involve changes across the human capital strategy through revitalized recruitment, learning and development, partnering and cultural initiatives.
  • The contingent workforce is creating the talent-exchange mindset: financial firms need to address is the growing preference for flexibility and entrepreneurship among many in the labor force. In the United States, the US Chamber of Commerce has found that 27% of the labor force is currently self-employed, and some believe that this ‘contingent workforce’ could rise to 40% or more within several years. Practically, for this reason alone, financial institutions will need to adopt a ‘talent exchange’ mindset, leveraging part-time and/or self-employed individuals in a creative manner. This may range from bidding out specific tasks or work to expanding the use of seasonal or temporary workers. Of course, this will introduce challenges around culture and quality, and this will introduce new opportunities as well. For example, we might see employers using online platforms to manage confidentiality and legal risks in creative ways.

Artificial Intelligence capabilities impacting the financial industry and thereby attitudes toward work continue to change, some of the attributes that have benefitted institutions in the past such as big firm and stable employment are slowly losing their appeal. Refreshing financial firm’s approach to recruiting, learning and development, and culture may offer an effective way to address issues that FinTech has brought into the open market.

Welcome your ideas in further spotting future trends in financial services workforce.

 

AI in Healthcare

AI
Healthcare fueled by AI/ML/DL:
AI Use Cases in Healthcare:
Roadmap to Implement AI in HC
Commoditizing AI/ML in Healthcare:
AI/ML Impacts on HC. AI and machine learning are already delivering value in HC. The following are high impact areas.

The Changing Role of Retail Workforce

I was visiting Lush – a fresh handmade cosmetics store along with Lush_app.jpgmy daughter and felt that the shopping experience compared with the past is changing in a noticeable way, in particular when it comes to interactions with the store workforce. I came to know that Lush employees typically go through extensive training to ensure they have the tools and knowledge to deliver this kind of service. At Lush the digital technology offers a replacement to the information usually found on packaging – the Lush Lens app uses machine learning to recognize products, meaning customers can simply scan ‘naked’ products to discover key information about them. Hence the retail workforce is upskilling to add value beyond the digital offerings.

This blog post is a result of the experience above. Global Retail and e-commerce leaders reimagining their business models in digital evolution and which is further changing workplace practices. I can say from my vantage point that digital, social and environmental developments are shifting the needs of the retail workforce. It is evident that device and sensor proliferation is aiding retailers to experiment intelligent and connected methods to innovate new business models to try new markets, offer new services and create rich & compelling customer experiences. The new-age developments listed below reflects the continuous transformation of the retail workforce

  1. Knowledgeable workforce offering personalized shopping experience: In a world where just about any product or service is instantly available online, shoppers visit a physical location is driven by specific needs. It means recognizing that shoppers would make the trip because they need something more than what they find in the digital world: face-to-face contact, empathy, and deep expertise. Whether they want to figure out how to hook up a smart home, what dress to wear to a formal dinner, or what to pack for that dream wilderness vacation, they want to talk to someone who can offer them more knowledge and personal understanding that they can find with a quick online search.
  2. Fitment of the retail workforce in experience economy: Stores just can’t be product-fulfillment centers. In both the physical and virtual worlds, product fulfillment is fast becoming the domain of AI and robotics, with retailers, consumer products companies and e-commerce platforms racing to develop the best systems to anticipate consumer needs and deliver products to meet them. What technology cannot fulfill, however, are human needs that remain unmet today and will continue to evolve in the future. One thing I’ve learned through my work is that as technological connections grow, so does the human need for meaningful connections. This need is what’s driving the experience economy. Whether in restaurants, travel groups, shared workspaces, yoga studios or spin classes, people are actively seeking intimate connection with other people and finding it in spaces and communities like these.
  3. Uplifting workforce skills is the need of the day: Process improvement, speed, and efficiency are at the core of successful online businesses. With online infiltrating over to brick-and-mortar sales it’s a mismatch in areas such as supply chain, inventory management, trend identification, competitive pricing analysis, etc.; for example, the ability to automate 99% of pricing decisions, not only offers a real-time advantage, but it also eliminates hours and hours of manual work per week. Hence the use and mastery of algorithms is a key tool of the buyer in successful online companies, a skill that is not as prevalent in brick and mortar;

With the advent of modern technologies bringing e-commerce intelligent systems that make running a retail store more efficient, my experiences with retailers progressed on leveraging in-store data. Having the right retail workforce management solution can take care of tedious administrative tasks across the board, while simultaneously collecting data to instantly improve in-store operations. With this schedule, store managers can be confident knowing that the most knowledgeable and high performing sales assistants are on the shop floor during times of high customer traffic, enhancing the shopping experience and resulting in more sales.

As retailers continue to evolve in experience economy continuum, it’s the value that a capable retail associate can add – the expertise, social sensitivity, and problem-solving skills – that will differentiate the good stores from the bad, the stores that will endure from those destined to fade from the scene.

AI in Operations (“AIOps”)

AIOps

Recently I was searching for verbatim “AIOps” on Google and got 624K results. Without many surprises noticed that there have been over 100 times rise in search trends since July 2017. That signifies the momentum for AI led Operations.

As my curiosity on AIOps increased, I looked at market opportunity for AIOps. From MARKETSandMARKETS analyst data, the global AIOps platform market size is expected to grow from USD 2.55 billion in 2018 to USD 11.02 billion by 2023, at a Compound Annual Growth Rate (CAGR) of 34.0% during the forecast period (2018–2023).

In this blog post, I am attempting to capture some highlights gathered from my learning curve over a past year or so. Refer to the schematic above that provides a high-level “AIOps Framework”. The following are key elements of the framework.

“AIOps” Verbatim Defined: Simply stating AIOps stands for Artificial Intelligence for IT Operations. Extending AIOps to business operations is inevitable in near future. Adding further, AIOps automates various aspects of IT and utilizes the power of artificial intelligence to create self-learning programs that help revolutionize IT services

AIOps Context: There is a significant opportunity to leverage AI for analyzing enormous data being created by IT and business operations tools, to increase the efficiency of operations, speed up services delivery and ultimately create superior user experiences. The resulting power of AIOps is enabling the progress from siloed to integrated operations backed by intelligent insights.

Signals: In today’s business and IT operations environment, the user is adapting multiple channels of communication for ease and enriched experience. So the backend operations teams as well should expand their ability to sense, analyze and respond to such structured, unstructured and semi-structured data signals. With this in mind, the AIOps platforms are being developed with built-in capabilities to receive and response signals that can encompass any events, alerts, service requests, IoT sensor data, Email, Video, Text, Voice support, UX, Social channels and many other forms.

Interfaces: The way enterprise operations backbone interfacing with signals and external queries also is shaping up in this transformation.

  • The first layer is Machine-First: Giving software/machine/bot the first act on sensing and responding to operations requisitions not only improves the automation of repetitive tasks but also augments cognitive intelligence in complementing human intelligence.
  • Human-Next Touchpoints: Human-next layers take up the operations requisitions that are not solvable by machines. These are the requests which involve human interventions.
  • Ensuring Reliability of Services: Alongside the above two layers, taking an engineering approach to services reliability for constant monitoring, triaging and incorporating insights from advanced analytics of enterprise data brings the culture of continuous improvements and stability to operations.

AIOps Platform: The entire AIOps ecosystem is based on the underlying Platform and Enterprise Core that ties all the components together. As Gartner defined, “Artificial Intelligence for IT operations (AIOps) platforms are software systems that combine big data and AI or machine learning  functionality to enhance and partially replace a broad range of IT operations processes and tasks, including availability and performance monitoring, event correlation and analysis, IT service management, and automation.”

As businesses are increasingly software-driven, operations downtime is becoming more costly and slow is the new down. This is leading businesses to proactively manage and improve experiences of services, applications, cloud, and networks. Along with this business 4.0 is digitally shifting the businesses offering the technologies that increase the volume, velocity, and variety of data. As traditional systems and manual efforts are facing challenges in correlating and analyzing the data or alerts, AIOps is stepping up to augment the enterprise intelligence in operations.

To conclude, the future is bright for IT and business operations with AIOps. The increasing shift of organizations core business toward the cloud, raising investments in the AIOps technology ecosystems, exponentially growing data volumes and increasing end-to-end business application assurance and uptime are driving the growth of AIOps market demand.

 

 

Marching Ahead to 2019

2019

Here is my take on the next 3 big trends to watch out as we march ahead into 2019.

1) Automation crossing over inflection point: Point I am making is progressing beyond task automation. For example, when we call a Bank, it really doesn’t matter whether a bot or a human reply from creating the net new value and better customer experience point of view. In fact, speaking to human can avoid following initial mundane activities alongside a BOT. Having a BOT may save cost and make operations efficient for a Bank, but what’s in it for the customer? Secondly, Automation has to elevate to be more intelligent and process-centric than taskmasters. That is what the inflection point for automation progressing to “creating value for consumers”.

2) “Shared to Distributed” economy/business models as a path forward: Over the past years Uber, Airbnb, Google and increasingly proliferated shared economy models are been successful use cases that rely on the contributions of users/external resources as a means to generate value within their own platforms. Unlike the Automation, here consumers get direct value from the shared economy models and better experience. But the shared economy model is still centralized and hence prevails risks limiting full potential. The shift is going to be towards a new model of decentralized organizations that are aggregating the resources of multiple people to provide a service to a very active group of consumers. This shift marks the advent of a new generation of “dematerialized” organizations that do not require physical offices, assets, or even employees.

3) The confluence of Digital technologies fuelling the next-level adaption/growth: We make a progress beyond adapting one or two digital forces towards the convergence of the ecosystem of digital technologies that drives the collective benefit of businesses, consumers and all stakeholders.

Enhancing Gift Cards Value Proposition (Blockchain for Gift Cards – Part II)

Last week, I published a blog post titled “Blockchain Boosting Customer Loyalty Programmes”. In continuation of views on Blockchain relevance, highlighting the following 4 aspects of gift cards industry that encompasses open & closed loop cards, new age innovative cards such as gift cards for stock, lottery retail gift card, donation gift cards etc.

1) Transaction fees

2) Seamless redemption

3) Consumer wallet spends

4) Fraudulence

1) Transaction fees: Gift cards market in the USA alone is estimated >$170 billion and growing at ~20% CAGR internationally across channels of stores, web, mobile, incentives, employee engagement etc. As per GiftCardsdotcom, processing fees on various types of gift cards range from 1.4% to 3.94% and lower the value of card higher the fees even touching double digits. This as a result of cumulative effect of various stakeholders in the value chain including the issuer, distributor, reseller, buyer, & receiver. Can we bring them on DLT to checkout fees?

2) Seamless redemption: Gift card industry is set up to hide identities of unspent balances on gift cards called “breakage”, which accounts to ~20% total spend i.e. $34 billion. Combining gifts, rewards, loyalty and coupon credits in one place/platform, making them available for immediate use can be one solution to this. Such platform as well can enable auctioning, trading, regifting and donating to charity features creating value for unwanted cards that expire. Can blockchain technology be leveraged for generating net new revenues from seamless card redemption?

3) Consumer wallet spends: Lack of single source of truth and shopping data has been limiting the scope of consumer wallet spend expansion. Overspend dynamic is really an upside, and analysis shows that when consumers shop using gift cards they spend an average of 30% to 40% more than the face value of the card credit. How about combining AI+Blockchain+Cryptocurrency (ABC) to increase the effectiveness of advertising by retailers to increase consumer wallet spend?

4) Fraudulence: “Return fraud – thieves simply walk into Walmart, Target, Home Depot, Lowe’s or another big-name retailer, steal an item, return it at a different store without a receipt and receive a gift card in return, which they can then turn around and sell to a pawn shop or secondary store for a lower price” (dangerous than cyber fund) is a new form of fraud in Gift Cards environment. Retail return losses total of $9 to $15 billion per year, 2017 survey by the National Retail Federation. >50% of companies reported fraudulent gift cards or store credit in one or more locations. How about applying blockchain technology enabling people who don’t trust one another share valuable gift card data in a secure, tamperproof way making it extremely difficult for attackers to manipulate?

Blockchain technology precisely addresses these factors and fuels the growth of gift cards industry leapfrogging customer loyalty experience and enhancing gift cards value proposition.

Refer to Part I @

Boosting Customer Loyalty Programmes (Blockchain for Gift Cards – Part I)

 

Living in an Artificially Intelligent World

imagesI was reading an article on new research led by the University of Adelaide on the subject of an AI’s ability to predict a patient’s lifespan simply by looking at images of their organs. After taking a deep breath picked up my coffee and started walking thinking about the deeper engagement of AI in human life. While paying for coffee a few minutes ago, I realized that my credit card got misplaced and called the Bank customer service to inform. A bot attended my call and navigated through the issue and without getting a human agent involved, bot blocked my lost card and placed a new one. I am sure it would have simultaneously updated records in the backend with lost and new card information in multiple systems beyond handling customer communications. This is a classic example of automating a standard business process and corresponding workflows. Then I realized ANI (Artificial Narrow Intelligence) has already made inroads into human daily life.

While contemplating further on AI reach on our lives, reached my home. My ten-year-old daughter approached me handing over the home phone and said, I am holding a call for you and it seems that “bot thingy” is on the line. She was right, it’s an automated calling service from credit fraud services. The bot enquired about the recent loss of my card, security, and privacy related queries. Then transferred the call to a human agent, who confirmed card replacement and started offering adjacent services like fraud protection, started analyzing the credit situation identifying potential needs offering a new credit card that in a way precisely address my requirements. My surprise went to the next level, as AI started traversing deeper in my life routines. Of course, post my last call to the bank, cognitive AI might have picked up from ANI and started advanced analytics on data deriving next level insights and triggering a bot to make a follow-up call. As bot done its preliminary job handing over to the human agent, this cognitive AI started helping him in offering adjacent products the make perfect sense in my scenario. The bot may sooner completely replace human interface. Isn’t it nothing but AGI (Artificial General Intelligence)? A machine that could successfully perform any intellectual task that a human being can or aid human being in doing so.

Perfect! I walked into the kitchen and got into a dialogue with my wife. We decide to go shopping. She was on her iPhone as we walk through the aisles, and I noticed that an NLP chatbot advising her on retail product recommendations with a greater personalization with rich images and connecting to VR interface enabling product tryout. What an intrusion of AI in every walk of life. This I call it ASI (Artificial Super Intelligence).

Albeit, in a day of life, I traversed with all three phases of AI with increasing degrees of influences on daily routines, needs, and decisions. Going back to the article I read in the morning, I felt humans natural dependency on AI is on a rising path. 

Blockchain is bringing Intelligent Technologies to Micro, Small & Medium Enterprises

Chatbots

As Blockchain technology is getting into the mainstream of large enterprises, I have been contemplating on how micro, small and medium enterprises (MSME aka SMBs) can benefit from Blockchain. Let me explain what I mean by this.

I looked into the data on Micro, Small and Medium Enterprises in the United States at International Finance Corporation (World Bank Group) website (http://www.ifc.org ). As per IFC consideration, Microenterprise has <10 employees, the small enterprise has 10 to 100 employees and medium enterprise has 100 to 500 employees. The latest data from IFC totals to more than 6 million MSMEs in the United States. Based on the scale and size, the technology adoption in MSMEs is driven by three factors – lower costs, ease of usability of technology and more importantly demand and advantage from new-age technology to their consumers/users. I would like to describe few scenarios before landing on to Blockchain advantage for MSMEs.

  • Scenario I: Blockchain can offer a substantial value by easing and expediting SME Lending process. Blockchain (i.e. Distributed Ledger) technology based SME lending Platforms could address information asymmetries and collateral shortage in aninnovative way and is applicable to any SME digital asset transaction performed online bypassing the need of any middle-man or the risk (and cost) of enforcement.
  • Scenario II: Chatbots have made a progression to successful use cases at large enterprises. Look at examples of  Allstate Business Insurance Expert (ABIe), Capital One Financial’s Eno, Domino’s pizza chatbot, a real estate bot like Apartment Ocean and list goes on. But I never come across a chatbot in interacting with a local restaurant, a childcare center, a mom and pop shops to state few examples from MSMEs. The reason being an initial capital cost and annual maintenance costs difficult to break-even with MSME financial models. Adding new-age advancements in AI, NLP and Machine Learning further enriches the power of chatbots. There exists a real opportunity in bringing the efficiency of chatbot to MSMEs by taking over tasks for which humans are not essential
  • Scenario III: Mobile Apps and monetization opportunities. Both Google’s Android and Apple’s mobile apps got exploded in recent times (7+ Million total apps as Aug 2017). According to the Small Business Mobile Apps: 2017 Survey by Clutch, 85% of micro-enterprises with fewer than 10 employees do not have a mobile app and whereas for SMEs in the lower fifties. There exists a significant business opportunity enabling MSMEs access to mobile apps.
  • Scenarios IV, V, & VI: SMS/USSD messaging, e-commerce/direct-to-consumer websites and instant messengers are other scenarios that would enhance MSMEs capability in addressing gig economy consumers. The technology is available to MSMEs in these scenarios, but development & customization needs, and costs are slowing down the adaptability.

Blockchain backed Distributed Ledger Technology (DLT) offer real opportunities enabling multiple channels like chatbots, mobile apps, SMS/USSD messaging, e-commerce/direct-to-consumer websites, and instant messaging to MSMEs and as well enable Omni channel capabilities. Blockchain decentralized autonomous platform (BDAP) can connect MSMEs, technology providers, developers, marketers, crypto ecosystem, and marketplace offering minimal transaction fees, competitive prices in the open and transparent marketplace, ensuring secure transactions, easing the channel access and simultaneously create the Omni-channel customer experience.

  • First, Blockchain (BDAP) platform takes-out the initial capital investments to access new-age technologies enabling multi-channel capabilities, establish a distributed ledger technology offering peer-to-peer financial system, smart contract to execute secure transactions and an exchange for MSME tokens, and platform that enhances exceptional customer experience.
  • There is an opportunity for sellers (tech providers/developers/marketing firms/startups) to play Business Integrator role creating MSME tokens and made available in the marketplace for MSMEs, Developers, Marketing & Content Firms, and Technology Providers.
  • MSMEs buy tokens for fiat and cryptocurrency. Developers, Marketing & Content Firms, and Technology Platforms decide the price of channels and determine token equivalents. This gives an opportunity for sellers to form a partner syndicate for creating Omni-channel AI Agent experience as an additional value-add.
  • Once tokens are received sellers of various forms (developers, marketers, media firms, technology partners etc.), MSME channels (chatbots, mobile apps, e-commerce/direct-to-consumer websites, instant messengers etc.) gets launched per purchased token volumes.

What MSMEs get out of BDAP is an asynchronous participation of ecosystem players offering a decentralized platform to access channel capabilities otherwise tied to higher capital and ongoing costs. Another key advantage to MSMEs from Blockchain enabled decentralized ledger is while MSMEs ensures their product quality building a trust/brand evaluation system, BDAP helps MSMEs scale to reputation evaluation system leveraging the platform.

You can reach me @ kishor.akshinthala@gmail.com for a deeper mindshare on this topic.