Digital transformation strategy was a trending topic well before the pandemic, but COVID-19 turned it into an imperative overnight.
Organizations such as Zoom and Amazon naturally reaped the benefits of the transition to life under quarantine, but the less obvious winners were almost exclusively the companies with a broad digital footprint ÔÇö think Etsy, Grubhub, Starbucks, and Pinterest. For these businesses, cloud capabilities made the difference between surviving and thriving when the pandemic struck, and early digital investments put them in a position to capitalize on key technology investments.
There are many technologies that effectively complement digital transformation efforts, but according to research from KPMG, artificial intelligence stands out to both 88% of small business leaders and 80% of those at the helm of larger organizations. And though AI is often thought of as an innovation of the future, itÔÇÖs far from science fiction. In fact, the benefits of AI for business are well established, and the technology is already firmly entrenched in our daily lives, powering our cars, feeding us entertainment recommendations, making product suggestions, and curating our social media news feeds. In the right setting, AI initiatives are a cost-effective means to propel digital transformation, helping companies collect data, clean it, and mine it for game-changing insights.
Clearing the AIr
AI is often used interchangeably with ÔÇ£machine learningÔÇØ and ÔÇ£automation,ÔÇØ but there are distinct differences between the three terms. To make sure weÔÇÖre all on the same page, letÔÇÖs quickly break down what we mean when we refer to each:
AI, machine learning, and automation might be three distinct terms, but thatÔÇÖs not to say there canÔÇÖt be overlap between them. In addition, each of these tools can add value to a digital transformation initiative if implemented in the right place.
AI in Action
AI has exciting potential. And although itÔÇÖs being touted as a possible solution for all kinds of problems, itÔÇÖs often easiest to see the benefits of artificial intelligence in existing use cases. In this section, weÔÇÖll examine three uses cases in which AI is empowering the switch to digital and generating incredible value for the companies relying on it.
Use Case 1: Supply Chain Verification´╗┐
Trust Your Supplier is a blockchain network Chainyard built on the IBM Blockchain Platform to help manufacturers combat counterfeit products and build networks of trustworthy suppliers. At its core, TYS offers three valuable capabilities, each powered by a type of artificial intelligence:
Use Case 2: Qualifying Loan Applicants´╗┐
A mortgage is often the most significant investment a person makes in his or her lifetime, which is why Home Lending Pal: Intelligent Mortgage Advisor is designed to help buyers find the right mortgage product for them. By analyzing thousands of data points using machine learning ÔÇö including existing debt, credit scores, income, and expenses ÔÇö Home Lending Pal points buyers toward properties they can actually afford and suggests lenders that will be willing to loan them the money they need. Home Lending Pal is also improving loan access for customers with no credit history who wouldnÔÇÖt otherwise qualify for a loan.
Although AI is certainly helping connect buyers with mortgages, itÔÇÖs also being used to help banks predict how likely customers are to repay their personal loans. Upstart is one such tool, and the lending platform works with banks to augment limited credit scores (or replace them if credit scores arenÔÇÖt available) using factors such as education and employment status. With AI predicting repayment, banks are less likely to lend to customers that will default on their payments.
What does adoption look like across the industry, though? A 2018 survey by Fannie Mae found that only one-third of mortgage lenders were utilizing AI, and about half of them were merely experimenting with the technology. That number is on the rise, however, and the same survey found that just 2% of lenders wouldnÔÇÖt be willing to use the technology at all.
Lastly, the mortgage and lending process is just one potential application of artificial intelligence, and McKinseyÔÇÖs Global AI Survey found that almost 60% of respondents in the financial services sector have adopted at least one AI capability. Robotic process automation is the most common, followed by chatbots or virtual assistants for customer service teams and machine learning tools to spot fraud and augment human underwriting teams. Although many financial-services organizations are still adopting AI in response to a specific problem, a growing number are seeking to implement it more broadly throughout their organizations.
Use Case 3: Digital Workers
A digital worker is a kind of software solution powered by various applications of artificial intelligence, ranging from natural language processing to machine learning to computer vision. Instead of supplanting human workers, digital workers perform tasks alongside them with speed, efficiency, and even advanced decision-making capabilities.
Digital workers have the capacity to transform the workforce in two key ways:
Digital workers are already having an impact in a number of industries, and their influence will only grow. According to research from IDC, digital workers will contribute 50% more to the global workforce from 2019 to the end of this year, with a 28% increase in instances of technology evaluating information and an 18% growth in reasoning and decision-making implementations.
Building AI and Machine Learning Into Your Digital Transformation´╗┐
Artificial intelligence as an idea has existed for decades, but the amount of high-quality data available and steady advancements in processing power have made AI a burgeoning field full of exciting possibilities.
1. Educate yourself.
Before you can get an accurate picture of AIÔÇÖs potential impact on your organization, you need to understand the different types of cognitive computing, how theyÔÇÖre deployed, and
how theyÔÇÖre applicable to your business. Robotic process automation, for example, involves the automation of both digital and physical tasks; itÔÇÖs the least expensive option and can offer the quickest payback period of any artificial intelligence technology solution. On the other hand, cognitive insight, which uses machine learning to detect patterns in vast volumes of data, can offer incredibly valuable insights ÔÇö but the payoff isnÔÇÖt guaranteed.
2. Look for inspiration in your industry.
Whether itÔÇÖs through a robotic investing advisor, a drug discovery tool, or a customer service chatbot, AI implementations are often specific to industries ÔÇö and you can skip a lengthy discovery process by looking at the benefits of AI for businesses in your sector. Examine how your competitors are applying machine learning to business problems for inspiration, and look for standout examples of business process automation tools and other automated business systems.
3. Address pain points with the biggest impact.
With each passing day, it seems there are fewer limits to what AI can accomplish, but that doesnÔÇÖt mean your first implementation should address the most complex issues in your organization. Look for obvious pain points where the technology can unlock the biggest benefit; this is usually done by eliminating an existing bottleneck or automating a manual process to allow your organization to scale. For example, if your business is ready to serve new customers but canÔÇÖt seem to find sufficient suitable prospects, a tool to comb lead databases and support your sales team might be the best investment. If you already have plenty of customers but satisfaction rates are suffering, a chatbot can help address many of the most common queries and ease the burden on your service personnel.
4. Launch pilot projects.
Cognitive applications should always start with a pilot project that allows you to learn about the technology, understand how it will be integrated into your environment, and evaluate the capabilities of your staff. Develop a center of excellence around new technologies to help your organization scale a solution across multiple departments. If you notice that youÔÇÖre missing certain capabilities internally, youÔÇÖll need to bolster your team by relying on third-party vendors.
Identifying a Promising Partner
AI implementations are complex undertakings, which is why itÔÇÖs common for companies to partner with vendors who can bring advanced skillsets and a wealth of experience. Not all vendors are created equal, however, and because a capable partner can make or break an implementation, itÔÇÖs important to keep a few things in mind when choosing a third-party provider:
1. Viability.
You donÔÇÖt want a new vendor thatÔÇÖs going to use your company as a learning opportunity. Look for a partner that has been around for more than five years and has a track record of success. These companies will have the fiscal security and corporate maturity to be dependable not just now, but also for years down the road.
2. Support.
An AI implementation is a journey and not a destination, so donÔÇÖt expect a project to operate on autopilot once the implementation process is complete. Look for a vendor you can return to for help with ongoing needs, and one that can fit you in for future projects as well.
3. Flexibility.
When choosing the right AI solution, the decision should be based entirely on your needs and not on the preferences of a potential partner. If vendors only advocate for the specific flavor of AI they specialize in, itÔÇÖs safe to assume theyÔÇÖre more interested in their own success than in yours. Along those lines, look for a vendor that embraces open source over pushing the proprietary technologies it sells.
4. Adaptability.
Your organizationÔÇÖs goals should be at the forefront of any vendorÔÇÖs work. Although vendors should have their own proven processes, they should be willing to adapt their techniques and procedures to your team and your organizationÔÇÖs style, culture, and mission. If theyÔÇÖre not willing to be flexible, the partnership is unlikely to be a productive one.
Incorporating AI and machine learning in business should be a part of any digital transformation strategy. The benefits of AI for business are well documented, and unlocking these benefits in your own organization is simply a matter of understanding the technology, identifying its most promising applications, and assembling the capabilities necessary for a successful implementation.
For more information about how AI in digital transformation could impact your organization, contact Chainyard to consult on how we can work together.
After the COVID-19 pandemic, companies will rely on technology and data like never before. However, thereÔÇÖs a caveat to this: Digital transformation is certainly critical for adapting to the new normal, but it has an unfortunate side effect ÔÇö an increase in cyber risk.
Companies should be excited about digital transformation, of course, but they also need to be on guard. In a 2020 survey, 82% of respondents blamed at least one cybersecurity incident in the last year on their digital transformation efforts. In 55% of the cases, a third party was involved, which highlights another risk created by an expanding digital footprint. Similarly, ransomware attacks are expected to hit companies this year at a pace of one every 11 seconds, and by the end of 2021, ransomware will steal around $20 billion.
All in all, 2020 was the year when attitudes around new technology reached a tipping point, and companies decided to finally commit to widespread digitization. Nevertheless, the last year has also highlighted the chasms between adopting promising technologies and laying the extra groundwork necessary for security.
How Digital Transformation Creates Security Weak Spots
We can tie these mounting threats back to digital transformation. After all, more technology means more targets for hackers, but many companies are rushing to complete their digital transformation without making a proportional effort to boost their digital defenses.
As companies become increasingly reliant on technology, ransomware has more ways to infect an organization. Even worse, when technology ÔÇ£drivesÔÇØ a company, ransomware attacks that prohibit access to apps and data have devastating consequences that companies will pay almost any sum to stop. In that way, hackers are using digital transformation against companies ÔÇö and technology becomes an immense vulnerability rather than a strength.
Although cybersecurity concerns might make digital transformation more complicated, they donÔÇÖt doom it to failure. In fact, blockchainÔÇÖs many use cases help ensure a company transforms into something more secure than it was before.
Use Cases for Blockchain That Boost Cybersecurity
BlockchainÔÇÖs use cases already factor into a significant number of digital transformation plans, but not typically for the purposes of cybersecurity. That oversight could be costly because blockchain fits naturally into enterprise cybersecurity architecture ÔÇö and it could be fundamental to digital transformation in the process.
Blockchain is a good approach to improve data security due to its decentralized nature, high level of encryption, and ability to ensure data remains private as necessary. However, itÔÇÖs also
important to note that while blockchain creates another level of security, it does not eliminate or reduce other best practices around security. In other words, itÔÇÖs an integral building block in your quest toward organizational safety.
We could spend pages highlighting all the ways in which cybersecurity and blockchain intersect. To get a broad sense of how blockchain use cases boost digital protections, however, consider these examples:
IoT
Massive numbers of connected devices will start supplying companies with data from different parts of their operations ÔÇö from the most important to the most opaque. Of course, this broadens the number of potential targets available to nefarious actors.
Among the business use cases for blockchain is using distributed ledgers to authorize and transact with IoT devices at the edge. Because this data can only be amended (and not altered or deleted), itÔÇÖs much more secure. Blockchains can also apply IoT data to smart contracts and automatically administer the contract details according to the data coming in (think the release of a payment once IoT registers the arrival of a shipment). This demonstrates how blockchainÔÇÖs use cases can serve as an alternative approach to keeping a company running ÔÇö even when other aspects of IT might falter because of an accident or attack.
Healthcare
The healthcare industry is extremely vulnerable to cyberattacks because it relies on an extensive number of siloed technologies (many with weak security) and produces highly valuable data (including both medical and financial records). This combination of factors makes it a prime target for hackers.
Blockchain shuts these hackers down by placing sensitive data into a system with asymmetrical encryption, making it nearly impossible to steal. For this reason, the presence of blockchain is enough to deter many hackers who would prefer to chase low-hanging fruit.
In the context of cybersecurity, the business use case for blockchain is highly compelling: ItÔÇÖs effective against numerous attacks and beneficial for other aspects of digital transformation, offensive and defensive factors alike. Put differently, blockchain should be considered in every digital transformation effort, including yours. Now, itÔÇÖs time to identify some use cases of your own. Visit our services page to learn more, or contact Chainyard here.
Blockchain is a tremendously promising technology. We have been applying blockchain technology to transform various business processes especially supply chain problems enabling it to become more efficient both financially and operationally. We at IT People have been involved with the blockchain journey since late 2015. Throughout 2016 until now, our team has built solutions in both Hyperledger-Fabric (an IBM Blockchain innovation from the Linux Foundation) as well as Private Ethereum. Along the way, as we architected applications, we learnt and experimented in developing smart contracts and noted that patterns can be applied to design.
Last August, I had a linkedin post on Scaling Blockchain Solutions. This post tries to explore one of the bullets in that post. We discuss some of the patterns here in this initial attempt at stirring some conversation.
Patterns for Contract Development
Patterns help break the solution into simple services and thus enable simplicity, maintainability and scalability. We have developed and tested multiple solutions in private Ethereum networks based on the Parity client, and many supply chain projects on Hyperledger-Fabric.
The following patterns described below were first discovered while we were implementing Ethereum Solutions. Subsequently, we refactored the solutions we built on Hyperledger Fabric, where most of the earlier solutions were based on a single monolithic contract with several functions processing business transactions and events. We broke up our back-end solution into smaller loosely couple contracts.┬áSome of the contracts were based on ÔÇ£asset typeÔÇØ which refers to assets as anything that has value and can be moved between counter parties. Assets include crypto-money, financial securities, documents, parts, items, votes etc. We list few of the patterns which have their roots in many of the earlier discussions in SOA, J2EE, EAI etc.
Motivation: During the building of the solution, once a smart contract is deployed, it is immutable and runs for ever. Newer versions of the contract are deployed over time, and unless the old one is destroyed, the multiple versions run in parallel. How does the application know which one of the contracts is legal or which version to invoke for a particular client.
Solution:┬áA singleton instance of a special smart contract called the ÔÇ£Registry ContractÔÇØ can be defined which acts as a registry for all deployed smart contracts. Every time a smart contract is deployed, a transaction is invoked on this contract to register the details of the newly deployed contract and any other updates to previous versions. This pattern is applicable to both Ethereum and Hyperledger-Fabric solutions. While contract account number is the key in Ethereum, the Chaincode ID can be used in Fabric.
Diagram:
Motivation: There are situations where several contracts may belong to the same family by sharing some common attributes and behavior and based off of a common template. These contracts may be organization specific and managed using user privileges assigned by the organization. Such contracts may be created at runtime. For example, if a buyer deals with several suppliers, the contract between the buyer and each supplier may be a separate smart contract.
Solution: Maintain contract templates. Instantiate a contract from the template as per the workflow at runtime. For example if an organization deals with multiple suppliers, then each supplier may have an independent contract with the buyer. In the case of Ethereum/Solidity, any contract can instantiate another contract from within the blockchain. In the case of Hyperledger Fabric, a new instance of the contract has to be deployed by the client from the outside into the blockchain network (e.g. from the NodeSDK Client via a deploy call).
Diagram:
Motivation: If there are a number of run-time instantiated smart contracts, there should be a method to lookup the appropriate contract using key attributes and then send transactions to that specific contract. For example, if the incoming transaction refers to Supplier_01, then, there should be a method to retrieve the contract associated with that supplier identifier and then send transactions such as UpdateSupplierRating(Supplier_01, args )  to that contract.
Solution:┬áWe can solve this using the same concept as a ÔÇ£Registry ContractÔÇØ. We utilize a ÔÇ£Lookup ContractÔÇØ that maintains a map of all contracts, in our case ÔÇ£Supplier ContractsÔÇØ keyed by supplier ID.┬áWhen an incoming request is received, the contract retrieves the appropriate supplier contract based on the ÔÇ£supplier IdÔÇØ. The Lookup contract acts as a registry of all contract addresses or URIs for the suppliers as depicted in the diagram below. This pattern is implementable in both Ethereum/Solidity and Hyperledger Fabric. In Hyperledger Fabric, the contract address is the chaincode name or identifier.
Diagram:
Motivation: When a transaction comes into the blockchain, it is necessary to verify the credibility of the user initiating the transaction and whether the user has the privileges to execute the transaction on that contract.
Solution: We implement a ÔÇ£Account ManagerÔÇØ that maintains records of all legal accounts┬áand some additional information and a ÔÇ£Role ManagerÔÇØ that maintains maps of roles to functions that can be accessed. The ÔÇ£Access VerifierÔÇØ acts as an internal check and verifies every transaction before execution against the account making the request and whether the account has permissions to run the transaction. An account may belong to an application, an end user persona, a contract or a client. We applied this approach while designing a private Ethereum network until we could build on top, an identity verification service and a certificate management service. This design pattern can be implemented in Fabric as separate chaincodes and using the chaincode-to-chaincode calling API.
Diagram:
Motivation: Almost all solution logic has some work-flow consisting of input, processing and output. A workflow is a series of steps or tasks performed to achieve results. The workflow may have several branches triggered by conditions. In our case, workflows do not store any data hence they are stateless.
Solution: We implement a smart contract that executes a sequence of steps based on the incoming payload or event. Each step may execute minimal logic such as validate incoming data or invoke another smart contract. In Ethereum/Solidity, our workflow does not have any ledger state variables but can make calls to other smart contracts to read data. In Hyperledger-Fabric, we have no calls to ÔÇ£putStateÔÇØ but the logic may contain ÔÇ£getStateÔÇØ to retrieve some data from the ledger, transaction-history or world-state by calling another chain code.
Diagram:
Motivation: The ledger is immutable, and data recorded in the ledger cannot be altered and manipulated. In blockchain solutions, data is owned by the smart contract and any reads or writes to the ledger can be performed only via the APIs provided by the smart contract. Thus, the underlying ledger is not directly accessible. The issue arises when a new version of the contract must be deployed. Data from the previous version of the contract must be migrated to the new version.
Solution: Split the smart contracts such that the business logic is isolated into the ÔÇ£Business ContractÔÇØ and the recording of the data into the ledger is performed by the ÔÇ£Data ContractÔÇØ. ┬áThere is one caveat ÔÇô we assume that the data contract will not change that often, and that it accommodates for most commonly used data attributes and operations.
Diagram:
Motivation:┬áAs seen in the ÔÇ£Registry PatternÔÇØ and ÔÇ£Lookup PatternÔÇØ, contracts can be instantiated dynamically at run-time and their contracts addresses are assigned during that phase. An incoming request from a client knows the function to be executed against a contract but does not know the address of the contract. In other situations, the workflow contract must be able to route transactions to the appropriate contract based on workflow.
Solution: Use a ÔÇ£RouterÔÇØ to receive incoming requests, perform a lookup to retrieve contract or chaincode address and route the request to the appropriate contract. The ÔÇ£RouterÔÇØ can maintain internal routing table or it could work in conjunction with a ÔÇ£RegistryÔÇØ or ÔÇ£LookupÔÇØ contract.
Diagram:
Motivation: In almost all enterprise applications, we deal with business objects such as order, supplier, customer and product. Storing large data objects in any blockchain technology in the ledger has implications. The storage requirement is enormous and is replicated across all the nodes. Queries against the object or a list of objects can result in latency issues. Finally, there is a cost for storage and data transfers. Data stored on the blockchain must conform to blockchain principles and requirements for decentralization, trust, transparency yet support privacy, auditability and immutability. However, business solutions represent end-to-end applications to solve business problems.
Solution: Our approach is to store blockchain specific attributes of a business object on the chain, while storing all other attributes about the object that support the solution for transaction processing and queries in an off-chain database such as MongoDB or CouchDB. This approach has helped us to engineer solutions to meet performance requirements and isolate private information to the off-chain storage with their hashes stored on-chain. The off-chain data store is attached to the client interface and complements the on-chain datastore. The combination of the two is considered part of the blockchain aspects of the overall solution.
Diagram:
Our Vice President of Business Development, Alex Rosen, recently collaborated with IBM Blockchain Squad Manager Burton Buffaloe and Program Manager Vishnu Tadepalli to understand how blockchain could be used to streamline contractor management.
This talk was originally featured at Think 2018, IBM’s technology and business conference, although a copy of the slides can be downloaded for free by clicking the link at the end of this article.
Enterprises are exploring new ways to work with their suppliers and competitors using Blockchain-based business networks. They need to understand the new opportunities and threats that emerge because of the new models Blockchain enables.
Our architects, developers, security researchers, performance analysts, test engineers, and DevOps experts are solidifying the foundation on which enterprise Blockchain solutions are built.
Businesses need Blockchain infrastructure designed to meet their requirements for privacy, compliance, and performance. Every day, ChainyardÔÇÖs team helps advance Hyperledger, the leading open business Blockchain. Our architects, developers, security researchers, performance analysts, test engineers, and DevOps experts are solidifying the foundation on which enterprise Blockchain solutions are built.
Chainyard provides needed guidance and skills through our services, including consulting, engineering, and operations. If you have an interest in leveraging blockchain technology, speak to an expert today.
Chainyard’s CTO and VP of Business Development recently got a chance to sit down with IBM to reflect on some lessons learned after wrapping up the development of our blockchain EAM solution. The original article (which can be found at the end of this article), tracks the journey of an IBM team tasked with improving the end-to-end management of enterprise assets.
We describe our starting point, the key architecture questions we had to answer, and our ultimate blockchain-based solution for our business. We share our lessons learned and thoughts on how to scale the system for future growth. Finally, we detail the IBM offerings we used and that are available to you for building your state-of-the-art blockchain solution.
Businesses need Blockchain infrastructure designed to meet their requirements for privacy, compliance, and performance. Every day, ChainyardÔÇÖs team helps advance Hyperledger, the leading open business Blockchain. Our architects, developers, security researchers, performance analysts, test engineers, and DevOps experts are solidifying the foundation on which enterprise Blockchain solutions are built.
We provide the right experts who bring the experience needed as solutions evolve from minimal viable products to enterprise-grade solutions. We work with multiple Blockchain technologies and have a specific focus on Hyperledger Fabric and its ecosystem.
Our team of Blockchain experts bring extensive experience in architecting, designing, building, testing, securing and operating complex distributed systems to help adopters of Blockchain technology succeed.
Chainyard are experts at Blockchain, and work with small, medium, and large companies to develop innovative blockchain EAM solutions every day. If you think you have a business need for blockchain, or are interested to learn more about our blockchain EAM solution detailed in this article, reach out to us and speak to an expert today.
Chainyard’s Senior Vice President of Consulting, Isaac Kunkel, was invited to guest post over at IBM’s Blockchain Unleashed blog this week. In his post, Isaac looks back on the journey that Chainyard has taken within the realm of blockchain, and our experience with using Hyperledger Fabric.
ÔÇ£A journey of a thousand miles begins with a single step.ÔÇØ
One famous proverb states that ÔÇ£a journey of a thousand miles begins with a single step.ÔÇØ In this proverb we learn that something which takes time begins with an initial action. For most, the blockchain journey starts with the adrenaline fueled feelings associated with trading cryptocurrency. For┬áIT People Corporation, it began with an opportunity to contribute to The Linux FoundationÔÇÖs┬áHyperledger Fabric┬áopen source project starting in late 2015.
The team was assembled to help build and support the infrastructure necessary to develop the early releases of Fabric. In partnership with IBM, the framework for continuous integration and  testing, along with other development, performance test and support activities, were built.
With contributions by dozens of engineers and companies, the early releases started to come together allowing early, pre-release solutions to be initiated, first with release 0.3, then release 0.5 in March 2016 and then with the first official release of 0.6 in September 2016.
Chainyard specializes in advising and supporting small, medium and enterprise companies in Blockchain.
Enterprises are exploring new ways to work with their suppliers and competitors using Blockchain-based business networks. They need to understand the new opportunities and threats that emerge because of the new models Blockchain enables.
Chainyard specializes in advising and supporting small, medium and enterprise companies in Blockchain.
Because we work closely with members of the Hyperledger foundation and are actively involved in the Blockchain community, weÔÇÖre able to provide our clients with expert insight into the Blockchain landscape to determine the most valuable Blockchain solution implementation for your business.
WeÔÇÖll work closely with you to help define a successful strategy focused on Blockchain adoption, development, and implementation.
You can continue reading the rest of the article over at IBM’s Blockchain Unleashed blog.
This article was originally published on LinkedIn
Earlier this week, I had the opportunity to participate in the annual┬áNational Retail Federation Tech 2018 conference in San Francisco, attended by over 100 C-Level Retail Execs. Earlier on Sunday, Brian Behlendorf, Executive Director of the Hyperledger Project, had briefed the CIO council about┬áHyperledger. The event kicked-off on Sunday with two fantastic key-note addresses. The first one by Amy Trask, CBS Sports Analyst and former CEO of the Oakland Raiders had one message ÔÇô ÔÇ£understand your FansÔÇØ which in retail parlance translates to understanding your customers. At one point she talked about how she would spend her time in the stands with her fans rather than the special boxes. While understanding what the quantitative data is telling is important, qualitative data is as important if not more.
The second keynote was delivered by Shabnam Mogharabi, CEO of┬áSoul Pancakes, a content creation company. Her entire message was about how to tell a good story that connects with your audience. The customer appreciated ÔÇ£positive uplifting content, filled with energy, liveliness and vibrancyÔÇØ. There are ÔÇ£22 rules to story tellingÔÇØ. She added another dimension of ÔÇ£emotional dataÔÇØ to what Amy had said earlier. In order to tell an authentic story, one has to ÔÇ£create discomfort that leads to real + vulnerable storiesÔÇØ. A┬áviral┬ástory is short lived impact but a story with a┬ávirus┬áspreads and can sustain audience attention for longer periods of time.
Monday morning kicked off with Andrea Wasserman (VP of Retail Experience at Verizon). The first speaker was Katie Finnegan who kick started WalmartÔÇÖs Store #8 initiative – an innovation center for understanding customer behavior to evolve future retail strategies. Each idea went thru a ÔÇ£Shark TankÔÇØ process where each selected candidate would present a ÔÇ£Point of View of the FutureÔÇØ as in a C-Series pitch. Once an idea is taken forward, that innovation was treated as a separate business with its own CEO and accounting head.
I heard concepts like story telling, content pitching, immersive retailing and PoC. The Store #8 incubation process follows a ÔÇ£design-> initiate-> build-> iterate-> minimum viable scale-> evaluateÔÇØ approach.
Ajit Sivadasan of Lenovo stressed that while strategy discussions are great, executing the strategy is where the rubber hits the road. It took them several years to come to where they are today. Starting with collection of data and reporting, today they are at a point where they use AI and machine learning capabilities to gain insights. They had significant challenges at the beginning, but today they utilize data sciences to innovate or get answers that were previously not intuitive.
During the breakfast, I met Raghu Sagi, the Chief Engineering Officer of┬áSephora. I have to admit I am not keeping up with the trends and had to ask him what does┬áSephora┬ádo. Their strategy was to give the ÔÇ£ladyÔÇØ a connected experience throughout from home to the store or connecting with their friends and other users. A key to their strategy is to create individual experiences for each woman and simplifying the user experience across all channels.
Maryanne Byrdak, SVP & CIO of Potbelly said that while they are still dealing with legacy systems transformation, their strategy is to protect their brand and be selective on which channel they want to leverage. For example, they would not want their sandwiches delivered with some other brand food products in certain channels. For Potbelly its important to focus on the ÔÇ£Right Price, Right Time and Right ExperienceÔÇØ.
Julie Averill , CTO of Lululemon shared an interesting story at Nordstrom about how IT was perceived as an ÔÇ£Electrical ClosetÔÇØ that only mattered when something went down. For Lululemon, business acumen, inspired partnership and strategic relationships with customers are important. She talked about ÔÇ£Speed to change and innovateÔÇØ, ÔÇ£emotional fitnessÔÇØ and ÔÇ£accountable for commitmentsÔÇØ as key to their business.
The CIO of Levi Strauss & Co, Chris Clark shared changes in the perception of IT as a partner who sits on the table with the business as opposed to being in the background as a service provider. The Strauss family is very interested in understanding technology trends and want it to be an integral factor in formulating business and financial plans.
Brandless is another startup that focuses on retail and feeding America through a community approach. According to Tina Sharkley, the founder, through supplier relationships and optimizing the supply chain and cost model, they have kept the pricing of any product at $3. They work with the community and through focus groups understand the needs and behavior of their customer.
Karen Etzkorn leads the Curate group (HSN, QVC, Zulily) and through acquisitions they have grown and also been saddled with disparate technologies. However, she points out that they are extracting the best from each of the entities and applying it across others. Agility and agile methods are very important to them and most importantly ÔÇ£making risk cheapÔÇØ.
The most illustrative painting of the future came from Peter Schwartz of Salesforce. Kicking of his presentation with a clip from Minority Report, he said that the future will be touchless and based on based on sound, personal digital assistants and intelligent devices communicating with each other, They will understand every move the consumer and personalizing everything. Peter talked about individual personalization using Netflix as an example. At Netflix, they study individual behavior and make minor changes to the UX/UI to tailor the experience based on learning. For example, Peter watches war movies where the selection is limited and hence it tries to steer Peter towards other themes.
His presentation was preceded by two startups ÔÇ£HingtoÔÇØ and ÔÇ£LisnrÔÇØ both looking at changing retail experiences. The theme of ÔÇ£HingetoÔÇØ was ÔÇ£anyone can make, anyone can design, anyone can ship, and anyone can buy anywhereÔÇØ all without locking up inventory. On the other hand, ÔÇ£LisnrÔÇØ hopes to change experience including payments using near-ultrasonic, ultra-low power data transmission technology that enables fast, reliable, and secure communication between devices via any speaker and/or microphone.
I noticed that there was limited understanding of ÔÇ£BlockchainÔÇØ among the attendees, and how it could disrupt the industry. I spoke with several folks including NRF, Sonoma-Williams, Ralph Lauren, Sephora, Zebra, Hughes, Remini, For Eyes, Richemont and Stein Mart about Enterprise Blockchain in Supply Chain. I had some detail chat with Janet Sherlock CEO of Ralph Lauren and Susan from American Eagle about supply chain settlements using blockchain to improve operational efficiencies, reduce disputes and eliminate reconciliations.
I attended the conference as the CTO of Chainyard which is the Technical Partner of Bleexy. @Argentina Moise, the CEO of Bleexy presented the vision of an integrated network of market places that leverage both public and private blockchains, enabled by smart contracts to initiate cross market place transactions and settlements. Bleexy provides a platform for retailers to collaborate in a trustless, transparent environment, yet support privacy and confidentiality. The Bleexy demo can be viewed by clicking here.
There was a presentation by Ryan Orr, co-founder of Chronicled about blockchain. He painted a weaker picture of several features such as key management and privacy still lacking in blockchains and that one in five who claim to be blockchain experts is bluffing. My strong feeling is that they work in the Ethereum space where many of these features have to be custom integrated to create private blockchains. Hyperledger-Fabric, while still advancing, provides native capability to address many of these challenges through the availability of channels, sideDB, service discovery, encryption on the chain, zero knowledge proofs, certificate authorities and member services and many more.
In summary, retail has several challenges in fast changing environment that include compliance with PCI, GDPR, protecting brand reputation, protecting, employees and understanding patterns of transactions. While many retailers are struggling with legacy systems and transformation, others see Amazon both as driving innovation at a a tremendous pace and a threat to their existence. Retail innovation is experimenting with several technologies such as chat bots, digital voice assistants, augmented reality, gamification approaches, avatars, social media, AI/ML and in store technologies such as smart devices, listeners, voice and facial recognition. Personalization is now at an individual level. Of course Price and Value are still very important. Innovations in retail have focused on several emerging technologies ÔÇô data sciences being on the top.
The NRF has done a fabulous job of hosting this event. The event was held at the beautiful Ritz-Carlton in San Francisco. The event kicked off on Sunday and gave plenty of opportunity to learn about the trends in retail. For a change, the sponsors did not have to put up booths and hang around which was a welcome relief. The breaks in between, the lunch, cocktail hour, dinner and post dinner cocktails all offered enough time to understand and chat with attendees. The food was excellent and had a variety for the foodie. Loved the interaction with the NRF Leadership. Thank you NRF for a beautiful event.
This article was originally published on LinkedIn
I have always been curious about how we manage releases of the Fabric images to the Hyperledger community for all the platforms consistently, continuously and with such efficiency since 2016. A couple of weeks ago, Chainyard sponsored and hosted the July JAM (Jenkins Triangle Area Meetup) Organized by the Cloud bees team. Our DevOps expert Ramesh Thoomu (Chainyard) and Will Refvem (Solution Architect) from CloudBees presented a session on Jenkins Job builder (JJB). Around 30 members from different organizations (CloudBees, Redhat, IBM etc.) joined the conversation.
 Jenkins Job Builder is a tool to automate the Jenkins job configuration. This gives lot flexibility and consistent way of managing the jobs. JJB gives flexible options to manage jobs as shown below:
┬áA Job configuration on Jenkins UI involves specifying Job Name, Description, Properties, Parameters, SCM, Triggers, Build Environment, Build and Post-build actions. A Hyperledger-Fabric project team is usually working on multiple branches across multiple build platforms. Take an example of a simple job, which one can trigger on ÔÇ£masterÔÇØ, ÔÇ£featureÔÇØ, ÔÇ£developmentÔÇØ branches and on ÔÇ£x86_64ÔÇØ and ÔÇ£s390xÔÇØ platforms. This can end up creating 6 Jenkins Job on Jenkins UI. This process takes a lot of mouse clicks and results in creating redundant job configuration and manual process. Managing all these jobs is a cumbersome task and can introduce errors if the process is not consistent.
JJB can tremendously simplify the problem. Job templates use Job definitions and modules to fulfill all the above Jenkins job requirements. Within Hyperledge-Fabric release process, the team is successfully managing 100s of Jenkins jobs easily with Jenkins job templates supporting seamless release process. The newer version of JJB supports a Jenkins pipeline plugin which makes things easier to create a touch-less seamless integration on CI/CT/CD, avoiding redundant job configuration and managing the jobs using simple yaml or json formatted configuration files.
Today we announce that Chainyard has joined Hyperledger, adding to the positive momentum Hyperledger is experiencing. Hyperledger is an open source collaborative effort created to advance cross-industry blockchain technologies. It is a global collaboration, hosted by The Linux Foundation, including leaders in finance, banking, Internet of Things, supply chains, manufacturing and Technology.
Hyperledger holds the distinction of being the fastest growing project launched by The Linux Foundation. Hyperledger now includes five different Blockchain framework projects: Hyperledger Fabric, Burrow, Iroha, Sawtooth and Indy and with the addition of over dozens of new members in the past few months, over 250 participating companies.
ChainyardÔÇÖs membership in Hyperledger gives us more direct ability to contribute to the worldwide network of professionals who are working together to research, develop and advance blockchain technologies. Our membership means that our blockchain experts will have a comprehensive view and are on the leading edge when it comes to recommending new solutions and providing blockchain services.
We are very excited to be moving from a contributor to general member with Hyperledger.  This gives us more opportunities to co-create value that will directly benefit the blockchain open source ecosystem
Isaac Kunkel, Chainyard VP of Consulting
Making the decision to join was easy since HyperledgerÔÇÖs objectives of maintaining openness, transparency and interoperability of blockchain technologies reflects our own vision. We see the potential for blockchain to significantly alter existing business models by development of decentralized networks that facilitate business through decreased complexity, increased efficiency, improved security and potential for new revenue streams to benefit all members of the network.
After working with Hyperledger for nearly three years, we have made a strategic decision to participate in a way that reinforces our vision, strategy and commitment to the Hyperledger project and further contribute to the technology stack. The team helps to build, maintain and support the infrastructure necessary to develop the early releases of Fabric. In partnership with IBM, the framework for CI/CD/CT and other development, performance test and support activities are maintained.
This global journey has enabled us to meet with many Blockchain enthusiasts from Austin to Boston, New York to San Francisco and Toronto to Singapore. We have had the privilege of speaking at IBMÔÇÖs Think Conferences, demoing at Consensus Conference and attending many other Blockchain conferences and meet-ups. Along the way, Hyperledger Fabric has matured, first with the GA release of Fabric 1.0 in July 2017, then the major upgrade release to Fabric 1.1 in March 2018 and most recently with the major upgrade release to Fabric 1.2 earlier this month, July 2018. The community releases are global in scale with efforts from hundreds of developers and dozens of companies. The collaboration of developers, scientists and businesses continue to push the platform forward to be the best choice for blockchain for business, that is, blockchain focused on permissioned, private networks built to solve business problems.
With the tremendous amount of collaboration going on in the community the technical acumen of the blockchain community has matured. This includes maturity in blockchain concepts, blockchain platform fundamentals, agile development practices, automated testing frameworks, performance testing frameworks, DevOps capabilities, cloud engineering and network security.
The growth has enabled POCs to transition to real world solutions across many disparate industries including financial, transportation, food, healthcare and mining. The platform and momentum have enabled us to work on solutions in supply chain including track-and-trace, procurement and compliance. With the combination of Hyperledger Fabric and IBM Blockchain Platform, we have built ready for prime-time business solutions.
Earlier this year we announced the launch of Chainyard, a wholly owned subsidiary of IT People Corporation. This was done to demonstrate our focus and commitment to blockchain technologies. Joining Hyperledger reinforces leadershipÔÇÖs commitment and focus on Blockchain for Business and our belief in the transformational nature of the technology. We are confident many others will be joining us in the future.
Hyperledger, an open source collaborative effort created to advance cross-industry blockchain technologies, today announced it has surpassed the 250 member mark with the addition of Chainyard.
Read more about Chainyard joining the Hyperledger here.
Chainyard has been named by LinkedIn as one of the top three companies where Blockchain developers work, along with IBM and ConsenSys.
Blockchain Developer also topped the list of emerging jobs in 2018, with an outstanding 33x growth. Runner up was Machine Learning Engineer, with 12x growth, followed by Application Sales Executive.
Click here to read the LinkedIn 2018 Emerging Jobs Report.