Archive for the ‘Placement’ category

Four Principles For Using AI

April 30th, 2018

Pick a basic problem — it is the single biggest determinant of success. The first version of Vymo only solved a basic need. Salespeople around the world found it tedious to report sales data. Without sales data, managers and leaders couldn’t forecast accurately or help their teams achieve targets, which impacted their topline directly. So, we built a mobile-first solution to detect all sales activities and then, based on sales data, our solution did what a manager would do. This is quite contrary to the general perception of artificial intelligence (AI) solving — or exacerbating, depending on whose views you subscribe to on the matter — all of the world’s most complex problems. Basic problems exist all around us, regardless of industry. To paraphrase Anand Sanwal’s advice on running a successful newsletter, it’s best if you can find the things people in your industry say but nobody actually ever says out loud. That’s not to say a basic problem is an easy problem. In fact, it’s often quite the opposite.

AI Solves Basic Problems Efficiently

The major edge data-driven software has over software that just implements standard business logic is that it is more contextual and evolves progressively over time. For example, Vymo’s intelligent suggestions have different intervention thresholds for different types of salespeople and it varies over a period of time. The cumulative impact of this is real and tangible. Its impact is even greater if you can work with businesses to pick out the most useful data sources, find out where the bodies are buried in the data and construct good features to feed into your algorithm. The other advantage of solving a basic problem is that it is generally prevalent (and present in usable formats).

Build Based On Observations

The suggestions our AI gave also evolved. Our first version of suggestions was based on the premise that more sales activities led to more revenue. In simple terms — more calls, meetings and other such interactions with prospects and customers increased your probability of meeting your sales quotas. It seemed like a perfectly rational thing to assume. In reality, though, only 30% of the best reps were in the top quartile with respect to meetings — they just averaged higher conversions. This led us down a path toward understanding what activities had a higher return on investment (ROI). As an example, lunch meetings offered disproportionately high ROI for sales reps in wealth banking. We also looked at what leads, prospects or customers had to be prioritized for engagement (spoiler alert — it’s not just the leads that are funnelled by marketing).

The first major pivot was based on an important lesson — build based on observations and not how helpful you think your application can be. Of course, you start with a basic premise, but once you have enough data to prove or disprove your model, your algorithms should run based solely on field data from end users. We prioritize builds based on what user data is telling us rather than cool new machine learning (ML) or AI capabilities we are excited about. Yes, we do try to stay cutting edge, but that never comes at the cost of being relevant to the user.

Tie Your Application To An End Goal

This is all a user really cares about — how does your application tie to my end goal? We still use notepads in the digital age because they still serve a purpose. The same is reflected in an app’s usability, too. One of our most popular new features is “nearby,” which shows the sales rep prospects and customers that are around his location. Compared to some of our other, more complex builds, this requires us to build a layer of intelligence on Google application programming interface (API) and then make it functional across devices and modes, which, while non-trivial, is definitely simpler than figuring out how prospects ought to be prioritized. So, forget your fancy models and algorithms — what is the value that you are adding to the end user? A sobering test for this is the usability statistics of the app, which reflects, in reality, the most useful aspects of the app.

It Is Better To Be Vaguely Right Than Precisely Wrong

This brings me to the final point — it is better to be vaguely right than precisely wrong. AI presents a tremendous opportunity to analyze and learn from large data sets. Often, the payoffs are disproportionately large relative to the costs (which are self-correcting, anyway). For instance, maybe the first few suggestions your algorithm makes are way off the mark, but if your experimental setup is right and your data is sufficiently large, it is bound to get progressively better. At Vymo, we run into corner cases, but if we didn’t expose our models to those data points, then who knows what we could be missing? If you had all of the power in the universe, would you prioritize doing great things or not doing bad things?

So, go forth and conquer!


Source: All the above opinions are personal perspective on the basis of information provided by Forbes and contributor Venkat Malladi.

11 Project Management Tips To Keep Your Employees On Track

April 23rd, 2018

Good project management is essential for any team tackling large, multi-faceted initiatives. This is especially true in the tech industry, where individual tasks are often highly specialized, complex and time sensitive. Without a solid process in place, it’s easy to lose track of progress and issues that may arise.

To find out how leaders can keep their teams’ tasks organized and transparent, we asked a panel of Forbes Technology Council members for their top project management tips. Their best answers are below.

  1. Create Squad-Based Teams

What helps our teams manage tasks is breaking down team silos with squad-based development to reduce miscommunication among team members. Squads are small, flexible teams that are responsible for the end-to-end delivery of each product. Each member is involved in sprint planning so that every person is allocated specific tasks that cumulatively match the capacity of the squad. – Sanjay Malhotra, Clearbridge Mobile

  1. Directly Align Tasks and Performance with Company Goals

Make sure everyone is aligned with the organization’s critical objectives with specific, individual performance goals paired with measurable outcomes. Tie the individual contributors’ performance directly to the organization’s goals with frequent progress reviews. This will naturally motivate your team to keep its eye on the ball and to avoid tasks that do not contribute to overall success. – Kevin Vliet, Target Corporation

  1. Use AI to Tackle Menial Tasks

The champions of the IT department have been struggling through some less-than-ideal work environments. It’s long been the fate of IT pros to handle mundane tasks that “keep the lights on.” Yet with the dawn of AI ops, noise reduction and alert clustering can be automated, granting IT pros the time and opportunity to focus on initiatives that drive the business forward. – Chad Steelberg, Veritone

  1. Follow Kanban Principles

While this system originated in the dev world, we at HyperGrid extensively use Trello and Kanban principles for organizing across the company. This has proved very useful as a way to quickly inspect and see how backlog is growing, who is overloaded and help with the reprioritization of tasks. – Manoj Nair, HyperGrid

  1. Make Sure Employees are Working on the Right Tasks

Unless employees are busy doing the right tasks, the business will suffer. Let intelligent data drive the framework, determining what each employee should focus on to achieve specific tasks. – Manish Sood, Reltio

  1. Train Everyone on Time Management

One-on-one time management training will help employees get the most out of their personal work times, which will help smoothen workflow among teams. Much emphasis, especially for tech employees, should be placed on blocking extended periods of time to focus on one sole task without distractions and breaking up longer projects into smaller, easily digestible parts. – Scott Stiner, UM Technologies

  1. Set Clear Expectations and Checkpoints

Strategic over-communication is key. Before teams start on a project, I like to make sure that everyone has a clear idea of deliverables, timelines and a measure of what success looks like. We also develop checkpoints along the way with our teams to figure out what is working and what is holding up progress. It’s vital to strike a balance between project management and employee independence. – Gregor Carrigan, Course Hero

  1. Encourage Communication, Feedback and Collaboration

Schedule daily stand-ups, weekly syncs and monthly alignment meetings. Provide ongoing feedback whether positive or negative. Don’t wait for periodic performance reviews. Everyone should know where they stand and where to improve. Foster an engineering team culture of close collaboration to solve siloing and project delays and to keep an overall tight adherence to a roadmap. – Bojan Simic, HYPR Corp.

  1. Choose the Most Important Thing For Employees To Focus On

Daily stand-ups are great to help share info but also for making sure that people rank the most important thing. If they have too many tasks, then they can’t be working on them all equally. The length of the list is just as useful as the top item on the list. Things in the middle of a long list are not likely to move forward and give a false illusion of progress because of constant status updates. – Joshua Greenough, InfoScout

  1. Prioritize Based on Urgency and Importance

Critical to task management is to identify tasks around two vectors: urgency and importance. Obviously, we want to tackle important things before less important things, so it’s critical to balance between important-urgent matters versus important-not-urgent matters. Regardless of how many important-urgent tasks teams have, it is always important to tackle the important-not-urgent tasks as well. – Han Yuan, Up work

  1. Trust Members of Your Team to Decide How They Work Best

Stop imposing process and overhead that prevents teams from being productive. Leaders should hire great talent, challenge them with an inspiring vision and then let teams decide on the tasks to best accomplish. As Laszlo Bock wrote, “Give people slightly more trust, freedom and authority than you are comfortable giving them. If you’re not nervous, you haven’t given them enough.” – Mike Weaver, Monsanto



Source: All the above opinions are personal perspective on the basis of information provided by Forbes and contributor Forbes Technology Council

4 Supply Chain Strategies To Drive Digital Transformation

April 16th, 2018

We see that industry boundaries are blurring due to new business models enabled by the digital economy. But are you equipped with the strategies you need to drive digital transformation and succeed in this fast-paced, ever-evolving landscape?

To meet the challenges of today’s digital economy, where customers want both products and services quickly and tailored to their unique specifications, your organization needs to fundamentally reimagine its business processes across the digital supply chain with the following four foundational principles:

  1. Customer centricity: Plan and deliver to the segment of one

In a digital economy, customer centricity is more than just an aspiration. It needs to be integrated with digital supply chain capabilities to serve segments of one consistently.

The experience starts with a touchless supply chain, where you automate wherever possible and manage by exception. This approach enables supply chain practitioners on the ground to focus on the value-added activities and processes that focus on customers first.

Automation at this level requires an accurate picture of actual demand. Improving forecasting accuracy remains essential, but it’s not enough. You need to capture demand signals in real time from multiple data sources. These sources include structured data – such as orders, point of sale, and Internet of Things (IoT) sensor data – as well as unstructured data – including texts, e-mails, social media, sentiment analyses, and predictive algorithms. All of this information must be brought together to deliver a true picture of actual demand to yield insights that facilitate improved business performance and superior customer service.

This demand drives integrated business planning processes that must be responsive and flexible to changes in supply, demand, and other signals across the supply chain. These improved processes enable companies to better manage collaboration across partner networks and more efficiently handle everything from a shipment of one item to multiple truckloads headed across borders. The result is the ability to deliver the outcomes customers want – even as preferences, requirements, and the digital economy continue to evolve.

  1. Predictive business: Design, make, and maintain the product of one

In the face of growing complexity and rapid change, how do you keep pace? One way is to see what’s coming before it happens:

  • Addressing issues before they become major concerns
  • Fixing machines before they break down
  • Adjusting shipments to avoid traffic or weather problems
  • Realigning manufacturing to adjust to sentiment analysis

Thanks to the emerging technologies available in the digital economy, all of this is possible. The leading-edge practice for a predictive business is to build and manage networks of  digital twins. A digital twin uses IoT sensor data to maintain a direct connection between a physical product or asset and its designed, manufactured, and deployed digital representation.

Through the use of digital twins, you can gain a 360-degree view of your entire network’s equipment, products, and assets – from products running in customers’ homes and full deployments of commercial-grade assets out in the field to machines and equipment operating within your business.

Visibility has little value in and of itself, however. You need to use the data available to create true product and asset intelligence and then act on it. The more you know about how products perform and how they’re used, the more accurately you can predict service disruptions and detect what customers want most.

By capturing and incorporating customer demand and usage data across a network of products and assets represented by a digital twin, you can create valuable insights about what’s on the horizon. This advantage can lead to more relevant product design, higher availability in the field, and improved customer service with the outcomes that consumers crave.

  1. Smart automation: Manufacture the lot size of one

Automation is everywhere across the supply chain, from robotics and autonomous forklifts in the warehouse to the potential of drones delivering goods. But when it comes to smart automation, manufacturing is leading the way – motivated in large part by the move from mass production to mass customization of individualized and personalized products.

To seize this opportunity, leading companies are rethinking their design, manufacturing, and logistics processes. A key trend is the transformation from continuous production lines to flexible production cells that can be moved and used in a nearly plug-and-play manner. Smart sensors that provide critical status data can assist in the automatic routing of products to the next cell in the production process.

As a result, companies can better manufacture the lot sizes of one that personalized products demand. In conjunction with more agile manufacturing processes, businesses are also retooling their distribution and delivery processes. Traditionally seen as cost centers, distribution centers are now viewed as strategic assets that can present a competitive advantage for savvy companies.

A range of powerful emerging technologies is enabling organizations to realize this advantage. To maximize flexibility without carrying the cost of large amounts of inventory, for instance, many companies are turning to 3D printing to generate products on demand. Other enterprises are turning to technologies such as machine learning, IoT, and robotics.

  1. Total visibility: Analyze and manage the supply chain of one

In addition to the individualization, automation, and responsiveness required to succeed in the digital economy, it’s vital to provide real-time visibility to every role across the extended supply chain. But how, exactly, do you achieve that?

Total supply chain visibility requires nothing less than a digital mirror of your business. The goal is to see everything – from the movement of goods in production or transit to demand signals and relevant data from sentiment analysis, point-of-sale systems, and other critical sources. Total visibility also means the ability to see traffic jams, accidents, and weather patterns that can affect sales and deliveries or cause supply chain disruptions.

Since modern supply chains always extend beyond the four walls of your organization, you need to flexibly coordinate and collaborate across complex business networks of partners, manufacturing facilities, warehouses, and distribution centers.

With a digital mirror of your extended supply chain, you can connect the real world to the planned world, enabling you to:

  • Improve sustainability and compliance across your global supply
  • Help ensure ethical product sourcing
  • Streamline cross-border transactions
  • Minimize exposure when performing product recalls

The objective is to identify potential disruptions and sense surges in demand. Gaining this ability will help you improve business responsiveness, minimize risk across the supply chain, and provide the kinds of experiences and outcomes that customers crave.



Source: All the above opinions are personal perspective on the basis of information provided by Forbes and contributor Richard Howells.


What Is Blockchain And What Can Businesses Benefit From It?

April 9th, 2018

It seems the blockchain revolution is in full swing. Over the course of a one-year period, Google search requests for the keyword “blockchain” have increased by 250%. The U.S. Senate recently had a public discussion about the blockchain’s most prominent application, cryptocurrency. And several public entities have added “blockchain” to their company name. So what’s all the hype about? What is blockchain and how will businesses benefit from it?

What is a blockchain?

In simple terms, a blockchain can be described as an append-only transaction ledger. What that means is that the ledger can be written onto with new information, but the previous information, stored in blocks, cannot be edited, adjusted or changed. This is accomplished by using cryptography to link the contents of the newly added block with each block before it, such that any change to the contents of a previous block in the chain would invalidate the data in all blocks after it.

Blockchains are consensus-driven. A large number of computers are connected to the network, and to reduce the ability for an attacker to maliciously add transactions on the network, those adding to the blockchain must compete to solve a mathematical proof. The results are shared with all other computers on the network. The computers, or nodes, connected to this network must agree on the solution, hence the term “consensus.”

This also makes the work of appending data to the ledger decentralized. That is, no single entity can take control of the information on the blockchain. Therefore, we need not trust a single entity since we rely on agreement by many entities instead. The beauty of this construct is that the transactions recorded in the chain can be publicly published and verified, such that anyone can view the contents of the blockchain and verify that events that were recorded into it actually took place.

So to summarize, blockchains are:

  • Transaction ledgers
  • Immutable
  • Consensus-driven
  • Decentralized
  • Trustless (it’s not based on a system of trust)
  • Secured by cryptography
  • Can be made public


What businesses benefit?

Prior to the advent of the blockchain, there was no way to secure and validate ownership in a digital asset or verify a transaction in a trustless, public manner. Take, for example, the act of utilizing a software license to gain access to a program like Microsoft Word. To enforce the right to use the software, it must check a centralized server operated by Microsoft. If Microsoft wanted, it could deny access to the software or transfer those permissions to another user. While we consider Microsoft a trusted entity, the risk of illicit behaviour increases when an untrusted party is introduced.

Perhaps a better example is ownership of a more valuable asset, such as a substantial share in a company or valuable digital asset such as a one-off piece of digital artwork. To transfer shares of ownership in a company, the current model requires stacks of paperwork, a lawyer or a centralized and trusted entity, such as the New York Stock Exchange.

What about transferring a digital asset like art? How do you prevent people from copying the digital file and sending many others a copy? If there’s no way to publicly verify the transfer of a single asset to a single entity, then there’s no way to enforce ownership or authenticity. This is why the value in art is always in the physical good.

The blockchain is the first technology that enables the transfer of digital ownership in a decentralized and trustless manner. In fact, there are companies like Polymath that are disrupting the industry by creating digital tokens that can represent ownership in a company, or DAEX, which is seeking to disrupt the world of digital art by publishing ownership on the blockchain.

While technology and supporting platforms around the blockchain ecosystem are sure to evolve, to answer the question of which businesses will initially benefit from its use, are the ones which possess the following traits:

  • Transaction-based
  • Benefits from public scrutiny
  • Benefits from history that can’t be rewritten
  • Decentralization benefits the end user or customer


Revolutionary But Limited

It’s easy to get sucked into the hype of one of the fastest-growing new technologies. But it is important to understand that blockchain has its practical limits. It may not be a suitable replacement for where centralization is needed (or at least where there is no added benefit to decentralization) or where transaction malleability is needed.

An example of where I think blockchain may complicate things but not add value to a problem is the case for medical records. Since information privacy is protected by federal regulation, having them accessible to the public may not necessarily be a good thing. The only way to make something like this work would be to encrypt the information, then store the decryption keys on centralized entities to allow other nodes the ability to read the encrypted data. But this would require a few specific parties to be able to read and write the encrypted data. And therefore, a central authority would need to control the licensing of this information to make sure that bad actors do not have the ability to hijack one’s medical records. Also, erroneous information that is added to the chain may be impossible to change.

No doubt, the supporting tech around blockchain will quickly evolve, as will the potential for applications that rely on it. With its growth will come an increase in consumer awareness to its benefits, as well as an equally supportive community. Businesses that believe they might be able to add value by incorporating this technology into their product or service can tap into a growing community of blockchain engineers, be it in a freelance setting or a professional blockchain development agency. As with any nascent industry, talent will initially be scarce, but as the ecosystem develops, the supply should hopefully increase to support it.



Source: All the above opinions are personal perspective on the basis of information provided by Forbes and contributor Forbes Agency Council.

How AI Is Improving The Landscape Of Work

April 2nd, 2018

There have been a lot of sci-fi stories written about artificial intelligence. But now that it’s actually becoming a reality, how is it really affecting the world? Let’s take a look at the current state of AI and some of the things it’s doing for modern society.

How artificial intelligence is improving the workplace

Creating New Technology Jobs

According to Indeed research, demand for workers with AI skills has experienced steady growth over the past few years. When you add the fact that there’s currently a shortage of job seekers who can meet that need, it only makes the skills more valuable for those who do possess them or would like to learn.

What kinds of jobs are being created, specifically? Obviously, they’re mostly tech-related, but there’s actually some variety when you break it down. Job listings that most frequently included “artificial intelligence” or “machine learning” include data scientists, software engineers, software architects, and full-stack developers.

A few non-tech roles made the list as well, including research scientists and product managers, so there are certainly options for others who want to enter the field.

Plenty of big companies like Amazon are doing the hiring, but there are also start-ups finding new and creative ways to utilize AI.

Using Machine Learning To Eliminate Busywork

Just about everyone has experienced that feeling of not having enough hours in the day to accomplish everything they need to. By enabling smart computers to complete certain tasks, workers can free up their time for their more important work.

According to a DigitalOcean report, while only 26% of developers are currently using AI or machine learning tools in their workflows, 81% are interested in learning more about them.

Those in non-developer roles stand to benefit here too, of course. For instance, perhaps accountants could use machine learning to fill out forms. Or clothing companies could use smart algorithms to make outfit recommendations. Or customer service teams could use it to answer basic questions on a support ticket or live chat session.

Preventing Workplace Injuries With Automation

According to this study by Injury Claim Coach, thousands of injuries and fatalities could be avoided by automating the hazardous elements of certain jobs.

The study discovered that across all industries, 5,190 people died from workplace injuries in 2016 (and many more suffered non-fatal injuries). That averages out to 100 people per week.

Particularly hazardous careers included motor vehicle operation and construction (trailed distantly by grounds maintenance). These careers also happen to be quite likely to experience automation in the not-too-distant future.

So, how many lives could automation save? Well, assuming just 14% automation, it could be as high as roughly 3,500 per year by 2030.

So rather than thinking in terms of AI taking jobs away, it might be more accurate to think about how many dangerous jobs humans won’t need to do anymore. Protecting lives (and freeing up those workers to pursue safer careers) is definitely a powerful use case for automation. However, just so you don’t end up in a phased-out career, work on becoming irreplaceable now.

Reducing Human Error With Smart Algorithms

While the human brain is a powerful thing, no one makes perfect decisions all the time. It’s frankly impossible for us to store enough data about past situations, actions, and outcomes, and evaluate the probability of each one occurring, in the time it takes us to make a choice. We’re simply operating with limited data-sets, which hinders our abilities to select the optimal decisions.

With computers, that’s not the case. If an AI can draw upon a database with thousands or millions of scenarios, it can process that information to figure out what decisions are most likely to result in successful outcomes. “That is much of what machine learning and AI is all about–taking complex information and organizing it to help make the correct decisions fast,” says Mark McFarland, Team Lead of Technical Recruitment at Relativity.

Of course, this won’t work for all types of decisions (at least in the current state of AI), as some decisions require uniquely human considerations. But especially in the business world, it can certainly enable businesses to optimize their decision-making as logically as possible.

This is just a fraction of the potential use cases AI could have in the future. If all this has you interested in pursuing a machine learning career, start by developing these key skills to succeed.


Source: All the above opinions are personal perspective on the basis of information provided by Forbes and contributor Laurence Bradford.


How Blockchain Will Transform The Supply Chain And Logistics Industry

March 24th, 2018

Managing today’s supply chains—all the links to creating and distributing goods—is extraordinarily complex. Depending on the product, the supply chain can span over hundreds of stages, multiple geographical (international) locations, a multitude of invoices and payments have several individuals and entities involved, and extend over months of time. Due to the complexity and lack of transparency of our current supply chains, there is interest in how block chains might transform the supply chain and logistics industry.

Let’s look at what is broken, how the unique attributes of blockchain could help and look at a few examples of blockchain already impacting supply chains.

How is the supply chain broken?

Our current supply chain is broken in several ways. Over a hundred years ago, supply chains were relatively simple because commerce was local, but they have grown incredibly complex. Throughout the history of supply chains there have been innovations such as the shift to haul freight via trucks rather than rail or the emergence of personal computers in the 1980s that led to dramatic shifts in supply chain management. Since manufacturing has been globalized, and a large portion of it is done in China, our supply chains are heavy with their own complexity.

It’s incredibly difficult for customers or buyers to truly know the value of products because there is a significant lack of transparency in our current system. In a similar way, it’s extremely difficult to investigate supply chains when there is suspicion of illegal or unethical practices. They can also be highly inefficient as vendors and suppliers try to connect the dots on who needs what, when and how.

What is blockchain and how could it help supply chains?

While the most prominent use of blockchain is in the cryptocurrency, Bitcoin, the reality is that blockchain—essentially a distributed, digital ledger—has many applications and can be used for any exchange, agreements/contracts, tracking and, of course, payment. Since every transaction is recorded on a block and across multiple copies of the ledger that are distributed over many nodes (computers), it is highly transparent. It’s also highly secure since every block links to the one before it and after it. There is not one central authority over the blockchain, and it’s extremely efficient and scalable. Ultimately, blockchain can increase the efficiency and transparency of supply chains and positively impact everything from warehousing to delivery to payment. Chain of command is essential for many things, and blockchain has the chain of command built in.

The very things that are necessary for reliability and integrity in a supply chain are provided by blockchain. Blockchain provides consensus—there is no dispute in the chain regarding transactions because all entities on the chain have the same version of the ledger. Everyone on the blockchain can see the chain of ownership for an asset on the blockchain. Records on the blockchain cannot be erased which is important for a transparent supply chain.

Examples of blockchain being used in supply chains today

Since blockchains allow for transfer of funds anywhere in the world without the use of a traditional bank, it’s very convenient for a supply chain that is globalized. That’s exactly how Australian vehicle manufacturer Tomcar pays its suppliers—through Bitcoin.

In the food industry, it’s imperative to have solid records to trace each product to its source. So, Walmart uses blockchain to keep track of its pork it sources from China and the blockchain records where each piece of meat came from, processed, stored and its sell-by-date. Unilever, Nestle, Tyson and Dole also use blockchain for similar purposes.

BHP Billiton, the world’s largest mining firm, announced it will use blockchain to better track and record data throughout the mining process with its vendors. Not only will it increase efficiency internally, but it allows the company to have more effective communication with its partners.

The transparency of blockchain is also crucial to allow consumers to know they are supporting companies who they share the same values of environmental stewardship and sustainable manufacturing. This is what the project Provenance hopes to provide with its blockchain record of transparency.

Diamond-giant De Beers uses blockchain technology to track stones form the point they are minded right up to the point when they are sold to consumers. This ensures the company avoids ‘conflict’ or ‘blood diamonds’ and assures the consumers that they are buying the genuine article.

There are several supply chain start-ups such as Cloud Logistics who saw an opportunity to provide blockchain-enabled supply chain solutions to improve efficiencies and reduce costs for the massive supply chain industry. More will most certainly join them as they realize the potential and demand for blockchain-enabled solutions to transform the supply chain and logistics industry.


Source: All the above opinions are personal perspective on the basis of information provided by Forbes and contributor Bernard Marr.


Bitcoin Facts You Should Know

March 18th, 2018

Bitcoin is not a fraud, nor is it a golden nugget. People continue to have strong views and positions on what bitcoin is and debate on its potential, legitimacy and relevance. The discussions are meaningful and leave many more thoughts for us to ponder. But those are opinions, and while useful, facts are critical and important to know. Knowing facts will contribute to meaningful dialogue and questions. Here are some to start with.

Bitcoin is programmable money. Bitcoin introduced a new form of money – programmable money. Bitcoin and other cryptocurrencies (or cryptoassets) operate under the same philosophy as past monies and money we are more familiar with. What determines money is a shared set of rules for exchanging value. The difference with cryptocurrency is that the rules are determined by the payer and payee. They decide the terms and conditions of the transaction, which are codified. This system will, and has started to, extend beyond cryptocurrency and ultimately allows for a huge array of transactions including contracts, expertise, assets and services.

In the analog world, we have physical forms of money such as goods and paper money and are limited by distance. In the digital world, we attained further reach with our transactions, eliminating the constraint and dependency of human distance and speed. However, in the digital world, we are governed by the speed and mercy of banks. In the crypto world of programmable money, we eliminate both human and institutional constraints. These frictions are expensive and reduced.

Bitcoin is not created out of thin air. Bitcoin is created through a process called mining. Blockchain, the technology that bitcoin is built on top of, is dependent on a network of nodes that ensures the integrity of transaction history by achieving consensus. Validation is one part of the process. After validating a transaction, the nodes then need to race, using trial and error, to solve a difficult mathematical puzzle that requires heavy computing resources. The first computer in the network that solves the equation will be rewarded with bitcoins. This is known as ‘mining bitcoins’. This protocol is referred to as Proof of Work (PoW).

Bitcoin mining serves two purposes: it allows for the creation of new coins and facilitates the processing of transactions in the network. Mining requires energy, hardware and bandwidth. If you try to mine bitcoins on your computer, you will find the cost of electricity will likely outweigh the value of bitcoins you can mine. Other cryptocurrencies also use PoW. Another emerging protocol is Proof of Stake (PoS) which does not need energy or hardware to achieve consensus, but rather uses staking or bonding tokens to determine the next block.

Bitcoin has value. There will only ever be 21 million bitcoins created, which is deflationary and the opposite of paper money which is inflationary. Bitcoin’s value and security is derived from the fact that it is easy to prove that substantial computing power and electric energy was expended to solve a math puzzle. This protects against fraud and counterfeit information. When bitcoin is created by PoW, the mining is authenticated and backed by a verifiable network.

Anyone can create their own currency. But a community is needed to accept the creation in order for it to have value. The world has been transacting with bitcoin for over nine years with a global community. Bitcoin also acts like a stock in that the price can go up and down arbitrarily. A stock price represents what another party is willing to pay for it. Cryptocurrencies function in the same way.

Bitcoin can be used for payment locally and globally – A vacuum existed for a faster, more efficient, and hassle free way to exchange money. Bitcoin was the first cryptocurrency to fill this white space and was created for payments and storing value. This new form of money enables online money transfers, peer-to-peer, without an intermediary like a bank. Generally, bitcoin and other cryptocurrencies can be transferred faster and with lower fees. (As bitcoin and other cryptocurrencies have gained more popularity, fees may be impacted by congestion and traffic on the blockchain).

In the earlier years of bitcoin, one could buy everyday items such as coffee, beer and dinner and transfer money for a few cents. The price wasn’t so volatile and the transaction time was fairly quick as usage on the blockchain wasn’t high. The charm was that no banks or financial institutions were involved. It was especially attractive if one wanted to transfer money to someone in another country. One could have sent $1MM worth of bitcoin to someone in another country at a cost of less than USD $1 and the receiver could convert it to fiat (aka paper money) in that country in less than an hour. Today with bitcoin’s price volatility and potential higher fees, it may not be practical for payments of everyday items. However, if you are transferring $1MM worth of bitcoin cross border, it may still be worth it.

Bitcoin as the first successful programmable money on the blockchain gave us universal, virtual and borderless cash – which is only the beginning. Bitcoin and blockchain didn’t just define the future of money. It is shaping the future of economies and transactions, and ultimately the future.

Source: All the above opinions are personal perspective on the basis of information provided by Forbes and contributor Jamie Moy.

10 Ways Blockchain Could Change the Marketing Industry This Year

March 12th, 2018

Bitcoin. Cryptocurrency. Ethereum. These related buzzwords have been in just about every business publication lately, and it seems that everyone wants to learn more about blockchain, the decentralized ledger technology behind it all.

Experts predict that 2018 will be a huge year for blockchain, noting that the technology is poised to dramatically change a wide range of existing industries. What does the rise of blockchain mean for digital marketing? We asked members of the Forbes Agency Council to share their thoughts.

FAC members weigh in on the blockchain.

  1. Brands Will Be Able To Better Target Consumers

Like many emerging technologies, it is very early to truly understand how blockchain will impact marketing. It has the ability to remove the middleman in digital advertising. However, that may take years to displace Google and Facebook, if ever. Because of blockchain’s transparency, it will initially help brands build trust with consumers. – Lisa Allocca, Red Javelin Communications

  1. Malicious Ads Will Grow

JavaScript-based cryptocurrency miners have already been found in the wild, wasting visitors’ CPU power to send “coins” back to website owners. 2018 will see an explosion of this type of shady ad to top-tier sites, especially as “on by default” ad blockers become more popular. Website owners will be searching for new ways to monetize but must balance the ethical use of their visitors’ resources. – Marc Hardgrove, The HOTH

  1. Privacy Concerns Will Be Resolved And Advertiser Trust Will Increase

Giving users control over the amount of personal information they reveal appeases privacy concerns from the user perspective and promotes social responsibility from the advertiser’s side. Studies routinely show that if you ask permission first, users are more than willing to give you personal information if there’s a reward in turn. That reward is paying users directly to view ads. – Kristopher Jones,

  1. 4. Decentralization Will Remove The Media Middlemen

Marketing and advertising start-ups in the blockchain space are already popping up. These aim to tokenize user behaviour and offer a sort of credit system between advertisers and the consumer, which completely removes the massive middlemen managing big media. As we continue to decentralize our world, this is inevitable. Be smart. Move away from being a middleman. Be the source. – Trevor Chapman, Trevor Chapman Group

  1. The Fraud Verification Industry Will Grow

Advertising online is complex when it comes to ensuring media is bought and delivered as intended. Blockchain will make this more transparent. I predict that fraud verification companies will, or have already begun, the blockchain process to evaluate how we can stop bots and fraudsters from stealing ad dollars from brands. Blockchain will allow us to verify who, how and where ads run. – Ashley Walters, Empower Media Marketing

  1. Delivery And Reporting Will Transform

The first marketing area affected last year by blockchain, even on a small scale, was video content delivery. That will extend beyond video to more content producers this year. They will love how they can control how their assets are delivered and ensure it’s properly tracked. Then, once advertisers experience verified delivery and reporting, it will be required. – Todd Earwood, MoneyPath Marketing

  1. Advertising Will Become More Transparent

Marketers love to publish case studies of their outliers that are getting amazing results. The gradual implementation of blockchain will provide transparency on marketing claims by every journey having the ability to be analyzed and validated. This will even lead to the ability to also negotiate contracts and accept terms based on those results. – Douglas Karr, DK New Media

  1. Influencers Will Become Fewer In Number But Better In Quality

Influencer marketing campaigns are going to change dramatically. With blockchain, marketers will be able to see if the influencer’s followers are true people or simply bots. Essentially, it will reduce the number of influencers but leave the top influencers at the top. – Loren Baker, Foundation Digital

  1. Publishers Will Become More Accountable

Technologies like Ethereum make publishers more accountable as transactions become more transparent. Advertisers can see exactly where their traffic is going. Ad data is paramount — it’s shocking how much information we don’t have. Measuring impressions doesn’t cut it. Blockchain technology will unveil everything, decreasing fraud and increasing attribution. – Michael Weinhouse, Logical Position

  1. It Will Solve Numerous Industry Issues

There are blockchain projects being created that might provide solutions around payment processing or fraud prevention within the ad exchange environment. Other areas of interest blockchain technology could solve for are measurement, invoice reconciliation and publisher/advertiser transactions. – Chad Recchia, Awlogy

Source: All the above opinions are personal perspective on the basis of information provided by Forbes and contributor Forbes Agency Council.



How Data Protection Platforms Can Power A New Generation Of Apps, AI And Data Science

March 5th, 2018

One of the strongest beliefs is that companies that learn to make the most of their data by effectively building, managing, and evolving their data supply chains will gain a lasting competitive advantage. With so much data now available, companies have to treat their data as one of their most valuable assets. These data supply chains must operate as smoothly as any other system or distribution network.

Yet data supply chains present unique challenges. It’s very difficult to get a data supply chain working seamlessly because it must gather data from many sources, distill it into a useful form, and then be able to deliver the specific subset as needed to the business. Data is not one-size-fits-all, so your data supply chain must be as flexible as your data is diverse.

To build the best data supply chains, companies should recognize an asset they already have in their inventory. And it’s one they often overlook, as there is one repository at almost every company that is woefully underutilized as a source of business insights: Backups.

Backups don’t just have to sit on a shelf and be pulled in only when other data is lost. In fact, they can drive innovation. How? Well, the whole process of what is now called data protection has become far more sophisticated. In this story, we’re going to use Commvault as an example of how data protection systems have created a central and comprehensive repository of data that can not only serve as a backup, but can also be the foundation for new ways of using data to create value.

In other words, we will explore how a modern data protection platform can help you build and run a data supply chain that supports new types of apps, AI, and data science.

How data protection has become a comprehensive data platform

In the past, data protection was all about backups. We all remember floppy disks and how no great late 80s tech movie could avoid involving some drama about the state of a backup. But for the enterprise writ large, backups have served as a key form of insurance. The whole backup system existed as a worst-case scenario setup, a way to transfer data to a safe place and then restore it if something went wrong.

But we need to expand how we think about backups to catch up with today’s technology. In the modern world, data protection platforms have gone far beyond traditional backups in the following ways.

Creating metadata catalogs. Today, a massive amount of metadata is captured, so companies know much more about where data came from and how it is being used. These catalogs can help companies:

  • Analyze data usage
  • Understand growth of data
  • Track down data
  • Observe and monitor data sprawl
  • Establish thresholds and institute alerts about capacity limitations
  • Use REST APIs to add data to a dynamic index (for example, adding GPS data to an entity such as an asset)

Using data crawls. Data protection platforms can also empower companies to crawl their data and create an index of the results usable by anyone in the business, to find and categorize people, products, locations, and other vital information, such as:

  • Entity identification and extraction
  • Harvesting of data related to a particular analysis or AI use
  • Identification of data needed for regulatory compliance

Establishing better search functionality within the data. Data protection platforms can create inverted indexes to make their data more searchable. Commvault’s dynamic index creates such indexes to make searches go faster.

Serving as a transformation engine. The data within the platform can help to drive innovation across the business, as its accessibility allows users from data science to development to:

  • Work with data masking
  • Perform live Dev/Tests on cloud data
  • Employ appropriate redaction techniques on data, while still being able to use data while it’s live and relevant

Operating as a workflow engine. Once the platform is fully operationalized, companies can create workflows using visual coding and simplified methods to automate to expedite processes, including standard workflows and processes as well as third-party integration with platforms such as ticketing systems.

Analyzing the use of data over time. Finally, because of the nature of data protection platforms, users can get multiple viewpoints of the same dataset across time to see what has occurred with it. Such temporal analysis offers valuable insights.

What these platforms and data lakes have in common

When we look at the capabilities a data protection platform like Commvault offers, we see that it has many properties that people have been striving to gain from data lake projects, such as:

  • All important data kept in a repository with a common metadata layer
  • Ensuring data is indexed and searchable
  • The ability to run transformation jobs to analyze and distill data, and to use a workflow engine to manage execution of such jobs
  • API access to data, supporting processing and retrieval

Granted, there some key aspects of data lakes missing from data protection platforms, such as programming models for creating and running advanced analytics, and the ability to create new engines such as SQL engines and other machine learning technology that runs on Hadoop.

But when you include data protection platforms as part of your data infrastructure, you gain a tremendously powerful component in a data supply chain. The platforms might not do everything, but they do a lot, and no one data repository can actually provide companies with everything they need.

Putting a data protection platform to work

Now let’s imagine how applications, AI, and data science can be all made more powerful with a data protection platform. Here’s what these platforms provide.

Understanding what you have. You have a comprehensive view and index of your data. There’s no more guessing about what you have and what’s missing. This can be helpful, for instance, when you’re in an app and want to know everything about a customer, or in a data science context and need context about the data. The platforms provide a metadata repository that aids understanding.

Getting access to all the data. Because of its basis in providing data recovery, data protection platforms have all your data. Once you’ve understood there might be something interesting in a particular dataset, the platform can give you direct access to the data itself and not just the metadata. This is a huge advantage as you can get access to a lot of data that you couldn’t access otherwise. This expedites results, as applications, AI, and data scientists don’t have to wait around for data to be delivered — it’s readily available.

Extracting nuggets. Data protection platforms break through barriers. We all know that some data is harder to find and mine for value than others. By consolidating all your data in one place, this ornery data becomes more manageable. For instance, if you want to find all the places in your data where a product or customer was mentioned, you can run a crawl through the platform and retrieve relevant data, and use it to feed analysis, apps, or AI.

Looking back in time. As mentioned earlier, a temporal analysis that companies gain from data protection platforms is invaluable. You can see how data is changing over time, monitor key trends, document and track changes, and perform analysis based on this information, allowing you to make better decisions based on historical data.

Performing metadata analytics. The same temporal analysis can also be used on your metadata. Companies can look back at all metadata and understand the changes and relationships between data sets, as well as who has accessed data and when to get a better sense of the most vital data to the business.

A backup plan that is anything but

The great thing about a data protection platform is that it is created and updated automatically. Companies still have to work on the data to distill it and put it to use, but with such a platform, you’re starting with an incredibly powerful view of all the important data in your enterprise in one place.

Data protection platforms offer ready access to a vast amount of historical data that can add an untapped dimension to your data supply chain. In short, app developers, AI experts, and data scientists who have access to a data protection platform will crush those who don’t have access to one.

Source: All the above opinions are personal perspective on the basis of information provided by Forbes and contributor Dan Woods.



SAP Partnership with Google Maps Indicates a New Openness

February 26th, 2018

Last week, SAP and Google made an announcement about a partnership based on Google Maps that is reflective of a refreshing new openness at SAP to doing things that were essentially unthinkable under past management regimes.

Under the deal announced last week, Google is going to support SAP Business Analytics use of Google Maps as part of all different types of SAP applications. This means that SAP products will eventually come with geographic mapping capabilities that offer the ability to visualize data that are powered by Google Maps. SAP applications will start to look a bit more like consumer web sites that use Google Maps used to find stores or to show statistics by region or any number of things.

Another implication is that the ability to manage and explore large data sets using Google Maps, SAP’s HANA in-memory architecture and other capabilities will become productized. Geo-spatial visualizations will be designed and delivered in the context of a business process. Given the capacity of HANA and the amount of data stored in a typical SAP application, it is likely that the ability to manage and use so-called big data will also start to be productized.

One might ask, what’s the news here? After all, SAP has supported use of the data in its applications by firms like ESRI that offer advanced geo-spatial mapping capabilities. In addition, SAP customers have used Google Maps with SAP data anytime they wanted to.

The news here, to me, is that SAP is now saying that a core capability that could potentially be used in all of its products will come from the cloud and come from a third party. This means that the more than 10,000 developers who work at SAP will now be able to incorporate Google Maps type functionality into its core functionality. For SAP Business By Design, the Software-as-a-Service offering, using cloud based services is natural, because Business By Design is delivered in the cloud. But for SAP Business Suite, that includes SAP’s flagship ERP application, this is a radical departure. SAP takes the operational quality of its products very seriously. The company was publicly disappointed by the recent outages at Amazon Web Services. Now, despite the worry that was raised by that event, the company seems to be going full speed in using a cloud-based component. There is little doubt in my mind that this attitude of openness will lead to more such announcements about approving other cloud based components into its arsenal.

Again, it is fair to ask, “Isn’t this obvious? Why wouldn’t SAP use the best components to build its applications regardless of where they came from as long as they were high quality?” The answer to anyone who has watched SAP or any large company is simple. It is big news when SAP or any large company can overcome its cultural barriers and do what makes sense without some painful prompting

In this case, SAP is overcoming a legacy of an insular engineering culture that could accurately be accused of suffering from a “not invented here” complex in the past. In a sense, how could it be otherwise? Most leading companies suffer from their success. SAP is rightly proud of its engineering history. The company created a system that started at the dawn of the software industry in the early 1970s based on some key principles — what SAP CTO Vishal Sikka calls Timeless Software — and is still going strong today. In that same time period, several generations of software companies have come and gone. SAP built and deployed many software innovations before they became widespread. The ABAP language used p-code and a virtual machine long before Java did the same thing. Abstractions of the data layer, devices for inter-application communication, synchronization of master data, and client/server UI found their earliest and widest deployments in SAP applications. To this day, practices like the nightly build that is used by Java development shops is really a remediation for the fact that there is no formal way to track dependencies between modules. Such capability has long been a part of ABAP Workbench. You don’t need a nightly build because you know what to recompile when something has changed.

The only problem with SAP’s pride in its history is that it has sometimes shut the company’s eyes to new ways of creating software. It appears that this announcement may mark a turning point to increased awareness and use of outside components. If SAP becomes truly open to using more and more outside components, and learns how to use them to create stable, reliable software, SAP could accelerate the pace of change, keeping the stable parts of its applications, but adding the best of what has newly arrived.

SAP has long been open to having other companies use its software. In October 2009, SAP published a guide, “SAP Guidelines for Best-built Applications that integrate with SAP Business Suite”, that has been updated about every other month since that date. This guide explains how to write applications that are compatible with SAP’s software guidelines and standards. This guidance is provided because SAP recognizes that other companies will be building solutions to meet needs that SAP is not going to address. By following this guidance, other companies can create solutions that fit naturally into the SAP Business Suite.

Now SAP will either need a new guide or a new chapter in its current guide that covers how to use Google Maps SAP style. Once SAP developers take up this challenge, and there is no doubt in my mind that they will, it is likely that Google Maps will be adapted by Google to better meet the needs of enterprise applications.

Two vital questions seem worthy of exploration in further columns. The first is: What’s next? What other cloud components will SAP start to incorporate? The second is: Is a bigger partnership possible? Google’s mission is “to organize the world’s information and make it universally accessible and useful.” Much of the information that runs the world is in SAP. Why aren’t Google and SAP working together to make it more universally accessible and useful?

Source: All the above opinions are personal perspective on the basis of information provided by Forbes and contributor Dan Woods.