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The cutting edge platforms for today will be the commoditized platforms of tomorrow. As the technology matures and evolves, the previous generation of technology becomes easier to build and deploy enabling a rush of vendors to capitalize on it by making it accessible to the largest possible customer base. This puts enterprises in the nontechnology sectors in an awkward position. Often not ready to consume the latest and greatest technology due to parts of their stack unable to leverage new technology and requiring upgrade to and deployment of the stepping stone technology, these enterprises have to choose between vendor lock-in in a multi-year software and service contract or risk building and implementing a version of the older technology in-house. Business Drivers of Infrastructure-as-a-Service The biggest risk in building technology platforms in-house is the risk of commoditization. The argument played out with the debate over internal vs. public clouds. Initially, enterprises were hesitant to leverage public clouds with several of them opting to build internal, private clouds. Building a cloud is hard. Operating and maintaining a cloud is even harder. Ensuring that the cloud is running on and leveraging the best in class technology requires dedication to the cause. This is often missing in non-technology enterprises by design given they are driven by different and separate business drivers and considerations. A cloud service provider is motivated to ensure the best in class service and technology because that drives revenue for them. An enterprise whose main business is not offering cloud or software services will not be motivated by the same drivers and thus there will be an inherent difference in their approach and success with building and delivering an internal cloud. Business Drivers for Platform-as-a-Service The same argument (public vs private clouds) applies to platforms. Building the best in class platforms that offer the ability to develop cuttin

One of the top reasons for digital innovation and transformation failures can be summarized as the enterprise trying to reinvent the wheel. This is the tendency of the enterprise to attempt to create technology, platforms, and applications that have already been implemented, scaled, optimized and almost perfected. This tendency almost always ends up a failed one as it does not create any net new value for the enterprise but comes with a massive opportunity cost as the enterprise spends crucial resources on reinventing the wheel than innovating for the customer. How The Wheel Is Reinvented Nontechnology enterprises can get trapped in a reinvent state where they conclude that homegrown technology is the only path towards customer and business value. This in itself is not entirely false however the type of enterprise and their decision-making process along with the capabilities they have in house have a very large impact on the success of the strategy.eRaaadada Reinventing the wheel happens when a non-tech enterprise discovers a technology trend towards much later in the hype cycle almost towards the end when the technology is hitting the mass market and decides to recreate or reinvent its own version of the technology. This is often done with the assumption that with some investment, the enterprise can have a home grown version of technology or platform that is designed specifically for its needs and is thus a better fit. However, enterprises assume that the state of the technology will remain constant and while they are attempting to home grow a version that can match the current state of the art. In reality, the state of the art shifts and the enterprise is not able to bridge the gap. Who Reinvents The Wheel Typically, technology teams often decide to go down the path of reinvention when they are allowed to make technology upgrade or technology creation decisions without business KPIs and cost constraints i.e. clear success criteria with fixed cost and clear ti

A pitfall in the path to innovation and disruption is the lop sided focus on "creation" and not enough focus on "consumption". Creation is the process of creating platforms, products, and solutions where as consumption focusses on ensuring that the created artifacts deliver the intended value. Too often enterprises get caught up in "creation" or enabling "creation" and lose sight of the fact that without consumption, anything they create is bound to be a failure. Creation & Consumption can not be Sequenced A misconception that often exists is that "if we build it, they will come" i.e creating the product and solution is enough and its existence will automatically lead to consumption and value generation for the customer. However, creation and consumption cannot be sequenced i.e. made a focus sequentially. Creation and consumption only succeed when they go hand in hand where tight, iterative loops ensure that the creation is informed by consumption trends and feedback and that consumption is also leveraging the latest creations. What Does A Lop-Sided Focus Look Like The top 3 signs of this lop-sided focus are as follows Focus on Building Platforms When the focus of the enterprise is building platforms and when customer value is only created when a developer leverages the platform to build a customer facing application, it often means that the effort invested in the platform has no ROI. When the focus is on platforms, application investment suffers and the platform builders get sidetracked with platform KPIs as opposed to business value KPIs. The platform builders might only focus on "Developer" satisfaction when ultimately, customer satisfaction matters for the business. Focus on Tools, Not on Solutions Another sign of lop-sided investment is a focus on tooling at the expense of solutions. Enterprise teams can often go overboard with building large libraries of tools and using the adoption of the tool as a metric of success. However, simil

Blockchain are certain to disrupt almost all industries fundamentally. Though there are technical issues, the idea of utilizing a blockchain to prove ownership, to prevent double spending and to establish trust and transactions in an otherwise trust-deficient world, is gaining excitement and acceptance. More and more enterprises are getting curious about the blockchain and are willing to start investing in learning, prototyping, and building on top of the blockchain technology. Starting out with the blockchain requires investment in a building the domain expertise, establishing the identity, establishing the infrastructure and deciding the blockchain that the enterprise wants to work with. Among these decisions is the question: Should the enterprise choose a public blockchain or a private blockchain. Both have advantages and disadvantages and the question can often come down to what are the short term goals and potential applications that the enterprise wants to build on the blockchain. Public BlockChains The default option when considering blockchains is the public blockchain. This is the blockchain that is truly decentralized, leverageable for any type of transaction and in the case of the Ethereum blockchain, offers SmartContract authoring capability that makes the blockchain very attractive for building contracts that reflect the needs of the real world. However, for an enterprise deciding between public or private contracts, there are some considerations that require attention. Speed and Scalability Public blockchains tend to be slower as they are limited by the number of transactions that can be verified every second and confirmed every 10 minutes. There are several efforts underway to make blockchains faster and more scalable however those will take time to get implemented. Speed and scalability will continue to be an issue and contracts and applications that require instant or near real time execution will suffer from this lack of speed and scale. Se

Modern, RESTful APIs are not considered standard, table stakes and expected out of any new project, effort, application, system, service or product. It has become so normal to talk about developer interfaces, developer adoption, application development and innovation in the same breath as APIs that a distinct effort to build APIs for a new product or service seems out of place and abnormal. APIs are the defacto standard of app development. So where do we go from here? We believe that APIs are about to enter the second growth spurt. APIs will evolve from not just interfaces and integration enablers into the rockets that propel enterprises towards innovation and market dominance. Here are three key trajectories that will lead the next API evolution and revolution. Innovation - Starts, and Ends with APIs All modern technologies such as Artificial Intelligence, Machine Learning, ChatBots, Analytics, BlockChain etc. begin and end their stories with APIs. APIs are what enables the communication between front-end user interfaces and the backend technology services. All new machine learning capabilities offered out of the big four tech companies have seen the light of day through APIs. Intent & Sentiment extraction, Topics, Categories, Summarization, Image Recognition, Entity Extraction etc. are all capabilities powered by Machine Learning, Natural Language Processing that is ultimately being delivered as APIs to application developers. Similarly, ChatBots are typically designed to get the user entered text, use an intent API to determine intent and then use a service API to respond to the user conversationally or with a service. Clouds - Multi-Cloud, Hybrid Cloud As the big three cloud providers grow their market share and attempt to attract attention, increasingly, enterprises need to think about how they minimize their risk by building in the flexibility to switch their cloud provider if and when they need. In addition, hybrid architectures or a cloud migration

A lot has been said about agility and the need for enterprises looking to innovate and disrupt to build agility. Agility, at the same time, also gets confused with the process of scrum. Small and large teams get enamored with the idea of scrum and mistake the process with the state of being agile. This is often more detrimental to the enterprise and can often create more process and not enough real agility. What is Agility Agility is the efficiency with which an enterprise executes and delivers on its objectives and goals. Agility is the ability to react to changes in goals, feedback from customers and shifts in strategy. Agility, from the outside, looks like a predictable stream of value delivered by the enterprise that matches and exceeds the needs of the customer. Organizational agility requires agility at multiple levels within the enterprise to drive the insights that can channel and align the efforts of the entire organization by leveraging data and information to make quick and informed decisions. Business Agility Business and customer-facing employees need to achieve "Business Agility". This is the ability of these employees to react to business critical in real time if needed and have access to the latest information at any decision point. Business Agility enables users to reduce the latency or lag between a need in the market or of the customers and when they are able to service the need. Decision Agility Analysts and data scientists creating the insights to drive decisions require "Decision Agility" i.e the ability to easily discover, leverage and use data for analytics and insights through any and multiple tools and channels. Analysts and data scientists need to produce insights that reduce the time and effort required to convert data into information and insights that are required to drive key decisions and actions. Development Agility Application developers and data engineers need the ability to easily generate, collect, access and deli

Technology Congestion is a not a recent phenomenon but the urgency around Digital Innovation and Digital Transformation has brought it front and center. Technology Congestion is a point in the Digital Journey where multiple technology initiatives, executed in parallel become entangled with each in a state where none of the initiatives, hampered by inter dependencies, prioritization, and cost, is able to complete, make progress and deliver business value. Modern Experiences Require Multiple Technologies Building a consumer driven, customer centric experience that truly delights and moves business KPIs requires several technologies to come together in almost a magical experience. This means that not on boarding and deploying multiple technologies is not an option or possibility. Enterprises have to build competencies in multiple technologies (and they have multiple strategic options to do so) and this can be a daunting task. Managing Technology Dependencies Often, an app-centric methodology requires a complete focus on the user and customer's experience. Delivering that experience can requires technologies that leverage each other or are inter-dependent on each other. Inter-dependencies can be sequential i.e. Technology A is required to be installed and operational before Technology B can be initialized. Inter-dependencies can also be matrixed i.e. a service X might require service Y to be complete and Service Y requires Technology B. Inter-dependencies can also be circular where System M feeds information into System N and System N, in turn, provides feedback to enable System M to iterate and improve. Innovation To A Screeching Halt Technology congestion can stall innovation. Sorting out dependencies can delay innovation and new product development and cause the enterprise to become anti-app-centric. The net impact is lost time and energy in technology installation and deployment with less than ideal focus and attention on customer value and user experience.

Enterprises have to constantly decide, at every step in their digital journey, should they build or buy. This question often is posed as a critical, do or die decision and the answer varies on a case by case basis. Building can be expensive, take longer but offers future proofing and more dependability whereas buying offers a faster time to market, less risk and accountability forced through contractual terms. However, a key point often overlooked is the cost of integration. Integration can be required at multiple levels. Vendor Applications Vendor applications typically require a two-way connection between the enterprise systems and the vendor application. The application requires incoming data and information from somewhere in the enterprise technology stack and an output stream of information back into the enterprise at one or more points in the stack or workflow. Vendor Platforms Vendor provided platforms typically have similar integration requirements as Vendor applications requiring an incoming data & information connection and an outgoing information connection into the enterprise process, workflow, platform or product. Application-To-Application Application to Application integrations where an application needs to be connected to another application to either provide data or signals to enable the downstream application to create value can be seemingly deceptive. Application-To-Application integration costs can grow at O(n^2) as potentially, worst case, each application could be connected with every other application. Enterprise Stack Fragmentation The problem of integration is exacerbated by the fragmentation of the enterprise at the organization level. This problem is also known as "Shadow IT" is driven by superficially differing needs of multiple lines of businesses in an enterprise. Shadow IT typically leads to multiple instances of similar technology stacks that cause data, compute and information to be silo'd. Stack fragmentation and its

Ron Pereira over at the LSSAcademy.com offered a really cool video that pits regular mass production vs. one piece flow, and his simulation produced a time savings with the one piece flow. In his video, what I found to be as interesting as his presented material were the comments at the bottom by professionals in manufacturing. They all seemed to think that one piece flow definitely has its place, and that it CAN be more efficient in certain contexts, but most of them also pointed out that, from a batch processing point of view, one piece flow doesn't save any time when it comes to actually delivering the product to customers if the customers are in the same place. For example, if you are folding, stuffing, and stamping envelopes, but they all have to go to the same post office to be mailed, there isn't really enough of a time saving compared to the possible amount of trips to the post office under a per piece system. Someone else also mentioned the idea of spreading each step in the one-piece flow out to several people vs. to one person, and the savings in time would not be outweighed necessarily by the fact that, now, several people are needing to be paid, instead of the one person. Either way, I think, under certain circumstances (like building full sized dump trucks with different customers), one piece flow is definitely a time saver and waste reducer than building a ton of dump trucks and running the risk of some of them not being sold. Plus, envelopes are way easier to simulate than building a bunch of dump trucks.

Much has and needs to be said about an enterprise's AI strategy. Artificial Intelligence or AI is considered a fundamentally disruptive technology similar to the steam engine, electricity etc, a technology that will be pervasive and absolute in its impact on the world and its inhabitants. The ability to find hidden patterns to predict the future or detect a behavior has massive implications across the world, in every industry, sector, and domain. When faced with this realization, enterprise's can find themselves stuck, paralyzed and unsure about how to proceed. The field of AI is decades old already and the early success stories have been practicing AI for multiple years already with the tech industry leading the way. How can an enterprise that has no experience and competency in this area let alone lead the technology or even leverage it appropriately to drive business value? When developing the AI strategy, two ideas are paramount. First, this a fundamentally disruptive technology and the enterprise will need to establish it as a core competency for the foreseeable future. Not doing so will not be an option. Second, a long-term plan to success is superseded by the need to drive quick wins and small successes not only to build confidence but use real-world experience to develop and hone that skill. The Short-Term AI Strategy The short-term AI strategy should focus on driving immediate business value through enhanced customer experiences that leverage any field of AI be it machine learning, deep learning, natural language processing etc. Driving the usage and deployment of AI in front of an end user making them smarter, productive and better informed can pay rich dividends by not only helping the enterprise can real-world experience, but it can also give a perception boost to the company as being innovative and cutting edge. However, most importantly, this can highlight and promote the success and potential of AI in the enterprise and encourage a snowball eff

Pandemic & Natural Flu Prevention with Simple Daily Habits The current Coronavirus Pandemic sweeping the world is causing all of us to look at our daily habits. Most of the focus has been on hand sanitation, covering your mouth if you cough or sneeze, and keeping your distance from people who may be at risk of spreading the virus. However, a more prudent action to take would be to look at the daily habits you have in place which could protect you long term from being in the high risk group of most likely to suffer severe consequences from contracting a virus such as COVID-19. Rather than resort to waiting for an immunization to emerge, you could start now to adopt daily habits that support natural pandemic and flu prevention. This high risk group comprises people over the age of 60 who are immune compromised and/or have an underlying health condition that makes them more susceptible to disease and death from that disease. Unfortunately, the health of our population as a whole has been declining for many years now. Have a look at some of the statistics: From 1990 to 2013 there was a 141% increase in deaths from Heart Disease. From 1996 to 2009 there was a 145% increase n people suffering from Asthma From 1999 to 2015 there was a 150% increase in Inflammatory Bowel Disease From 1990 to 2015 there was a 250% increase in Epilepsy From 1999 to 2010 there was a 300% increase in Diabetes From 1996 to 2018 300% more births required fertility treatments. From 1991 to 2015 there were 783% more deaths from Alzheimer's Disease From 1990 to 2018 there was a 4,200% increase in Autism Common diseases are now increasing at epidemic rates, but none of this is hitting the headlines of our mainstream media! What could be causing this massive decline in our population's health, and therefore making us more vulnerable to pandemics like COVID-19 and seasonal flu viruses? Nutrient Deficiency Diseasesmineral-defiency-deseases-and nutrient deficiencyDr Wallach has been saying for man

This week's webinar features Guest Speaker Rich Stocks Rich Stocks Youngevity business trainingwho has been with Youngevity for 21 years. Rich helped the company to launch in Australia and New Zealand about 20 years ago. He has an impressive history in Network Marketing and as a business entrepeneur. Some of the highlights of Rich's career are: 4 Star Executive with Youngevity Author / International Speaker and Trainer Successful Entrepreneur Youngevity Circle of Excellence Inductee Member of Youngevity Circle of Honor A member of the Multi Million Dollar Earner's Club Featured in The Greatest Networkers in the World by John Milton Fog

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Digital Transformation is tough, even for seasoned technologists. This is because it is a transformation of an organization at its core. Everything from culture, technology, ideation, development, integration, delivery, and support needs to fundamentally shift to be more customer-centric, service driven, automation first and experimental in nature. No wonder that a lot of organizations take a long time and a lot of investment to see ROI from their digital transformations. Here are 5 signs that your digital transformation might be in trouble. Culture mistrusts the core digital transformation team You are spawning new initiatives before completing previous ones Decisions are top down with low accountability at the leaf nodes You tend to focus on technology stacks with little focus on customer value Inter-organization politics stifles cross-organization scenarios Culture mistrusts the core digital transformation team It is almost impossible to make an entire organization aware and participate in digital transformation at the same time. There are exceptions but in our experience, starting out with a core digital transformation team is a much better strategy than otherwise. This team should be enabled to attack a limited set of important and business relevant problems, build cutting-edge solutions and use them as examples to train and evangelize digital transformation strategies to the rest of the organization. However, the more entrenched an organization in the old way of doing things, the harder they might this central team. Resistance can be active and passive such as refusal to share data or provide the relevant context of the problem. An organization that does not set up the early crusaders for success almost always has a much harder time showing value from their digital transformation activities. You are spawning new initiatives before completing previous ones Executing on a digital transformation strategy is much harder than defining the strategy especially fo

Are you AI-First? By editor Posted October 13, 2018 In Artificial Intelligence, Digital Strategy, Technology & Design 0 An AI-First company is an enterprise that has transformed to believe and understand the incredible and disruptive potential of Artificial Intelligence. Such an enterprise not only sees the value but can see the destructive impact of being left behind. An AI-First Company understands that it might not know all the answers but realizes that it needs to seek out a path forward with AI or risk being marginalized. Key Characteristics of an AI-First Company A-First companies might not be any different from their previous form but think and act differently. Here are some key characteristics of such companies. Approach to Problems and Planning An AI-First company evolves its approach to problems. AI-First companies realize that determining the existence of a problem and selecting the most consequential problems is a function of data and analytics. An AI-First company invests in building predictive mechanisms that can signal current or upcoming problems including the severity and priority of these problems. Building these predictive mechanisms becomes the first step in determining how and when to prepare for problems or upcoming issues. In addition, these companies leverage news and information that is generated inside and outside the enterprise as it is generated and ensure that their employees and customers have access to the insights embedded in the news and information. Approach to Products and Product Development An AI-First company understands how a prediction or classification could help them deliver a better solution to a problem faced by their customers and how their existing products can be adapted or new products created that change behavior based on the predictions and classifications. Enterprises that understand the power of AI ensure that data scientists come part of the core product ideation and development team with a heavy infl

One of the most common misconceptions out there is the belief that technology equates innovation. Innovation is the creation of new value through a better solution for a problem that either does a better job in solving the problem or does so in a manner that the solution is accessible in a larger set of circumstances by a larger number of people. On the other hand, technology is simply the tooling that holds the promise of new solutions but by itself, is meaningless. Enterprises can become enamored by the promise and hype about technology and go down long, complex journeys, invest millions in upgrading technology and still come out empty on the other side because they built technology for technology's sake. Even in well intention boards and C-suite, industry peer pressure and hype around technologies can force action that ultimately leads to massive investments in people, software, technology, and vendors but does not yield the ROI promised by the technology. Leadership The problem can be accentuated when not enough due diligence is done on the applicability of the technology to the enterprise given the current state i.e. the point in time when the technology is being introduced, the customer's propensity to accept the technology-driven solution i.e. are the users ready to embrace, adopt, learn and utilize new solutions and burning problems that necessitate the adoption of new technology to better solve the problem. When the timing of new technology introduction is gotten wrong, it almost always fails to deliver on its promised ROI. Leaders need to rise above the hype and peer pressure and ensure that they understand, first and foremost, the burning problems that plague their customers or make the bedrock of their future strategy. Next, leaders need to ensure and validate that the technology in mind can actually be used to solve the problem through rapid prototyping and minimal investment. Once customer feedback on the prototype has been validated, then only

It's not too late to jump on to the Blockchains trend. We often hear from customers whether it is too late to get behind blockchain. The number of startups in this space is growing rapidly and the number of large ISVs and SIs providing blockchain capability and expertise is also increasing. However, the market and the technology space for blockchains is far from saturated, settled or stable. Here are three reasons why now is a good time to get into blockchains Early Mover Advantage Blockchains are bound to disrupt fundamentally how business is done. By enabling trust in an otherwise trust-deficient environment, blockchains enable transactions between two or more enterprises who otherwise might not know about each other. Blockchains offer solutions to several common problems faced by the enterprise such as Digital Identity, Secure Data Storage, Secure Data Sharing, Distributed Ledger, Distributed Databases etc. Blockchains are based on strong cryptographic standards based in mathematics, cryptography, and encryption. Building blockchains as a core competency requires a deep understanding of the mathematics behind it and an internal process for deploying, managing and developing on top of the blockchain. Early mover advantage can be generated by taking small steps in this area and targeting simpler scenarios initially. Nascent Technology It is going to take another few iterations of the blockchain technology before it can truly be enterprise-ready. There is a lot of ongoing work to make blockchains more secure, scalable and performant. Innovations are constantly being made and added to the core blockchain technology that is constantly increasing the type and complexity of applications that it can support. As the technology matures, enterprises can be well suited and ready to leverage the advancements by building a core competency in not only the blockchain technology but by becoming a member of the blockchain community, standards and keeping up to date with th

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Lean systems are meant for producing the best products and services with little or no wastage of various kinds of resources. Lean supply chain management purports to create a well designed supply chain management system where all the resources are effectively utilized. The people, processes, technologies and suppliers will be optimized at the beginning of the implementation and it will be an ongoing process. The best of the best features will be implemented and there will be no room for waste. Lean supply chain helps companies deliver high quality products quickly and efficiently. What is expected from lean supply chain management? In fact, lean supply chain management is a new way of thinking to understand the supplier networks. It is required to have cooperation with various suppliers and should be able to balance it with the competition present in the market. There is a great deviation between lean supply chain management and traditional methods. There will be less number of structures in lean model whereas they are more in traditional systems. Most of the lean supply chain management principles are derived from the basic lean principles. How companies will be benefited by the lean implementation? By implementing lean methods in a systematic way, companies will be benefited to the greatest possible extent. The winning business strategy realizes the importance of the relation between the supply chain management and the overall financial status of the company. By streamlining the supply chain management with all the other core aspects of the company, the business will emerge into a profitable enterprise and will be able to deliver cutting edge solutions. Strategy for lean supply chain management In order to implement the lean supply chain management in an effective manner, it is required to build the core infrastructure and should be collaborated internally and should be executed externally as well. The next step would be the selection of the right kind of

Transforming into a tech company has become top of mind for executives in all major industries. It is clear that modern technology will fundamentally alter what and how business is done in every domain, sector, and industry. This has led to a call to arms in every enterprise to understand how they can transform into a tech company. The Tech Company Magic Tech companies have fine-tuned the art of bring new digital products and services to the market, quickly, efficiently and effectively and understanding customer feedback to iterate and improve. This capability makes them incredibly agile and leads to faster experimentation that is cheaper and involves less risk. In turn, this enables them to bring new capabilities to the market and even if all do not succeed or get traction, a few do and that drives innovation, customer satisfaction, and growth. From the outside, tech companies appear to be massive juggernauts that are unstoppable and able to crush everything in their path. The 'Non-Tech' Technology has been leveraged in every sector and industry, however, it has almost always been treated as a means to an end, something that is required but never the real value driver for the customer. This has led to the typical organizational structure in enterprises into "Business", "Operations" and "Information Technology". The "Business" arm generates value for customers, the "Operations" team carries out the requirements of the Business team and the "Information Technology" team provides the systems (databases, network and compute) required to "keep the lights on" for the Operations and Business Teams" This structure served enterprises well in the last decades as customers did not have an alternative to directly working with the enterprise and this fortified the value supply chain and also established a hierarchy of sorts within the enterprise where the business looked down upon operations who looked down upon technology. The purpose of