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Success with AI is heavily influenced by the data maturity of an organization i.e. their ability to procure, clean, curate, store and analyze data to power value generating applications. A data-mature enterprise know what data it has, knows what the data means and can ensure that the data is accessible to whoever needs it. Unfortunately, the past few years, driven by the big data hype, have encouraged enterprises to focus on updating their data infrastructure to leverage new big data technologies. With a lot more data now available, enterprises already stuck with massive data storage costs, are being forced to choose between storing data that might eventually be useful for stabilizing, if not reducing their storage costs.

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We are a different AI company. See how our LearnCloud brings together your entire enterprise to operate on the same "information plane" towards an exponential increase in efficiency. Jenny is responsible for customers at Acme Corp Jenny feels she is driving blind. She realizes the ground truth but often it is too late. The information is spread across multiple applications & systems. Even when available, it does not help her look into the future so that she can act & save the day Sarah is a Support professional at Acme Corp Sarah feels she has her hands tied behind her back. She has to manually process each & every issue. Her job is tedious and inconsistent. She is not able to leverage patterns across issues & across support professionals. John is a salesperson at Acme Corp John is frustrated with antiquated tools & late arriving insights He has to manually scour the internet for information about his prospects & their changing strategies. He has to talk to many people to understand the state of the customer. By the time he understands the current state, it is often too late to prevent abandonment or drive the expansion People like them encounter these problems all the time which causes frustration and attrition for them and their customers. How does this happen?

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

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

Digital Transformation is a huge topic now. Most software vendors have adapted their products to include the Digital Transformation message. Transforming into a digital company is no longer a choice and it is clear that the companies that transform faster can develop a competitive advantage that will serve them for years while the companies that do not will slowly fade into irrelevance. Digital Transformation is the change in an enterprise that makes it acquire and deploy the best in class technology assets and systematically removing analog or manual touch points, handoffs, processes and decision making. It is the ability of the enterprise to understand, assimilate and leverage the latest technology trends such as cloud, mobile, APIs, AI, Blockchain, ChatBots, Analytics, IoT etc.

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

Digital Transformation has become a necessity for enterprises in every vertical, sector and industry. Software is indeed eating the world and there is no industry that cannot ignore the burning necessity of transforming to a software driven organization. However, the road to digital transformation is long, unpaved and full of dangers. It is a road that most enterprises that are embarking on it have never encountered. These organizations realize that their ultimate survival depends on navigating this road but are hesitant, unsure and scared because this transformation requires competencies, culture and an approach that is alien and unknown. Though, traditional IT departments have always been part of such organizations, they have always been looked upon as plumbing that ultimately is only relevant in the background to keep the lights on. Faced with impending doom, organizations have no choice but to rethink their IT. This is not simply an initiative in the IT team. CEOs and CFOs need to rethink what and how software can and will disrupt their companies. Business and IT need to come together to have a joint software driven experience strategy and needs to be prioritized by the CEO and funded, for the long term by the CFO. Do you need to think about a Digital Transformation strategy? If you answer YES to any of the questions below, you should. Are your teams, data, and systems fragmented? Are your key processes fragmented, manual? (for example, Onboarding, Decision Making, Incident Management, Support) Is your data of low-quality data (customer profile, transactions, glossary, documents) Is your regulatory compliance inconsistent and more a matter of luck than planning? Could your customer relationship, lifecycle, performance management be better? Could the information flow in your organization be matured? Do you have a weak understanding of internal and external events and how they impact your business?

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

Enterprises across the board have a lot of untapped potential in their data. The data is not only relevant and useful within the enterprise but can be a valuable source of insights for the enterprise partners and customers. In some cases, the value of this data can be high that partners and customers are willing to pay extra to get access to this information at a certain fidelity, freshness or scope. Enterprises that do not have a clear and coherent monetization strategy are leaving money on the table. In addition, they stand to lose customers to competitors who gain the first movers advantage by addressing this market need. The Value of Data The first step in determining a monetization strategy is an audit of the enterprise data assets and a determination of the customers who are interesting and willing to pay a premium for access to this data. The Value of Data is proportional to the following: Freshness The more "fresh" a dataset is higher its value typically. This is because there is an advantage in the early visibility provided by first access to new information. 'Freshness' is defined the latency between the creation of data and the delivery of the data to the consumer. Consumers of data will pay a premium for fresh data if it fits into their decision and action strategy. Fidelity Higher the "fidelity" of data i.e. how much detail a particular data point carries also increases the value of the data in the eyes of the data consumer. Higher fidelity data offers more information and detail enabling the consumer to design highly valuable analysis that leverages the additional details offering a deeper insight into the situation at the present or historically. Raw The more "raw" a data set, higher its value as it can support a much larger set of analysis scenarios that a processed data set could support. Data sets that are aggregated, sampled, filtered or transformed can have a lower value as they can severely limit the type of analysis. Raw

One of the biggest hurdles to Digital Transformation and Digital Innovation is the organization's inertia and tendency to optimize for self-preservation. Self-preservation can exist in the enterprise at the individual, team, divisional or the organizational level and can have a devastating impact on the organization's ability to innovate and grow. Self-preservation is not a new phenomenon however, it is more deadly for an enterprise now than ever. This is because the speed of technology change has increased geometrically. In the past, self-preservation would automatically get corrected as the technology was generally learned and adopted slowly with enough time for the enterprise to become aware of the change and implement it. However, the rate of technology change has magnified tremendously and the enterprises no longer have the luxury to take their time with the change. Inaction risks getting left behind and other competitors who leverage and change faster stand to capture the largest market shares and customer mind share. Self preservation is the tendency of the enterprise to ignore, undermine or postpone the adoption and integration of new technology in the enterprise to avoid a change in the status quo across technology, products, services and most importantly, day to day operations and organizational structure. Self-preservation can lead to what is termed as "politics" in an org, it can stifle innovation and innovative individuals & teams and it can favor business driver stagnation over risk taking. 5 Signs of Self-Preservation The following are signs of self-preservation Highlighting the Journey of Innovation as Failure Adversarial teams and individuals within an enterprise who are interested in self-preservation often go out of their way to highlight the tough, risky journey of true innovation as a failure citing the cost and the time being taken to address the real problems in a truly innovative manner. While the individuals and teams trying to

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For many enterprises, transforming into a digital organization is a very big priority. Digitization is more than a passing fad; instead it almost is a precursor to survival in the next decade. Analog mechanisms of running businesses are no longer sustainable nor likely to give confidence to customers, employees, stakeholders and shareholders. Measuring Digital A digital organization is characterized by the following Time to Customer Insight The Time to Customer Insight in a digital organization is the time it takes to collect, process, analyze information to determine the health of a customer, their satisfaction with current products and services, their unmet, possibly unstated needs and the impact that external market events might have on the customer. Time to Reaction Time to Reaction is the time taken to react to a customer insight through the introduction of a new product/service to solve an existing or a new problem or through better packaging of existing solutions to address otherwise existing problems. Time to Market Time to Market is the time taken to bring a new capability, product or service to market often as reaction to a customer or market insight or feedback Time to Iteration Time to Iteration is the time taken to solicit, gather, process, analyze customer feedback and effect a change in existing products or services or bring new products and services to market to address the customer feedback. Digital Organizations Digital organizations are characterized with minimal Time to Customer Insight, Time to Reaction, Time to Market, Time to Iteration and a constant effort and investment into further optimizing and minimizing these metrics. Digital organizations focus on the flow of information through the organization and use of the information to generate and deliver more value for the customers. Key Characteristics of Digital Organizations Instrumentation of Interfaces, Products, Systems, Applications, Processes A digital organization ensures