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digital transformation (61)

Digital Transformation is moving any company into the future. Well, this statement is true for Disney, Nestle, Apple, Amazon and other leaders as they focused mostly on the customer/user experience.
 
Digital Transformation is in almost every c-level magazine, blog and whitepaper and executives do not want someone comes in and disrupt their business.
 
If you want to reap the rewards of the digital revolution, a smooth, easy and positive user experience is vital.
 
People may not be getting technically proficient, but they have become more comfortable using their smartphones to download music, find the nearest movie theatre or pay for purchases. This raises the bar for user experience.
 
Today organizations are adopting MobilityAnalytics, and the Internet of Things for Digital. However, solutions, which are not intuitive, responsive and social, does not have a place in the customer’s list. So it becomes appropriate for companies to get into the user experience space.
 
A UX design can supercharge productivity, add immense value to customer interactions, and help employees love their jobs.
 
It is extremely important to do an accurate analysis of users, their needs by conducting surveys, workshops to design the UX.
 
Here are six major criteria for UX design:
  • Easy to find: How easy it is to find a site or application
  • Ease of use: How easy it is to use the site or application, how easy to learn
  • Easy to access: How easy it is to access the site or application, easy to understand, easy to reach
  • Usefulness: How useful the features and functions are and they meet my needs
  • Elements of desirability: Will make users like the product’s looks and feel and visual appeal
  • Credibility: How much users trust the site or application, creating the overall brand experience
 
Overall UX design should have short navigation steps so users require very few clicks to get the information they want. It should be based on responsive web designs so application maintain full functionality, usability and appeal on different browsers and screens from desktop to laptops to tablets to smartphones.
 
Once you have applied these criteria it is also important to measure the results, for future course correction. One initial KPI is user adoption rates, which should be higher than 60%.
 
The great user interface makes the experience better, transactions easier, decision making simple and cuts down the operational costs. 
 
It is the deciding factor for keeping/loosing or successfully engaging a customer.
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A field guide describing the 5 approaches to industrial IoT platform development and how to know which approach is the right one for your enterprise based on your goals, requirements, constraints, and where you are today in your digital transformation journey.
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What is a smart city? The answer depends on who you ask. Solutions providers will tell you it’s smart parking, smart lighting or anything to do with technology. City officials may tell you it’s about conducting city business online, such as searching records or applying for permits. City residents may tell you it’s the ease of getting around, or about crime reduction. Everyone is right. A smart city, built properly, will have different value for different stakeholders. They may not think of their city as a “smart”city. They know it only as a place they want to live in, work in, and be a part of. To build this type of city, you have to first build the smart city ecosystem.

 

A smart city is built on technology, but focused on outcomes

A scan of the various smart city definitions found that technology is a common element. For example, TechTarget defines a smart city as “a municipality that uses information and communication technologies to increase operational efficiency, share information with the public and improve both the quality of government services and citizen welfare”. The Institute of Electrical and Electronics Engineers (IEEE) envisions a smart city as one that brings together technology, government and society to enable the following characteristics: a smart economy, smart mobility, a smart environment, smart people, smart living, smart governance.

But what does a smart city really do? Our scan of smart city projects worldwide showed that initiatives fell into one or more smart city “outcomes” (Figure One).

Figure One. Smart city projects are aligned to one of seven outcomes.

 

As a starting point, we define a smart city is one that uses technology extensively to achieve key outcomes for its various stakeholders, including residents, businesses, municipal organizations and visitors.

 

The smart city ecosystem framework

Figure Two shows our framework for a smart city ecosystem. A vibrant and sustainable city is an ecosystem comprised of people, organizations and businesses, policies, laws and processes integrated together to create the desired outcomes shown in Figure One. This city is adaptive, responsive and always relevant to all those who live, work in and visit the city. A smart city integrates technology to accelerate, facilitate, and transform this ecosystem.

Figure Two. The smart city ecosystem framework.

 

Four types of value creators

There are four types of value creators in the smart city ecosystem. They create and consume value around one of the outcomes listed in Figure One.

When people think of a smart city, they automatically think of services provided by municipal and quasi-government agencies, such as smart parking, smart water management, smart lighting, and so on. In fact, there are three other value providers and users that co-exist in the smart city – businesses and organizations, communities, and residents.

Businesses and organizations may create services that use and create information to create outcomes for its stakeholders. Some examples of “smart” businesses include Uber and Lyft for personal mobility, NextDoor for information sharing, and Waze/Google for traffic and commute planning.

Communities are miniature smart cities, but with very localized needs. Some examples of potential smart communities include university campuses, office parks, airports, cargo ports, multi-dwelling unit (MDU) or apartment complexes, housing developments/neighborhoods, business districts and even individual “smart” buildings. They have needs for smart services that may be tailored specifically for their stakeholders.

Residents or individual citizens are also smart services providers in the smart city. A resident living near a dangerous street intersection can point a camera at the intersection and stream that information live to traffic planners and police. Residents place air quality measurement sensors on their properties to monitor pollution and pollen levels during certain times of the year, and make that information available to other community members. Residents can choose to make these smart services temporary or permanent, and free or fee based.

 

The Smart City is built on layers

A smart city is an ecosystem comprised of multiple “capability layers”. While technology is a critical enabler, it is just one of many foundational capabilities that every smart city must have. No one capability is more important than the rest. Each capabilities plays a different role in the smart city. These capabilities must integrate and coordinate with each other to carry out its mission.

 

Value layer. This is the most visible layer for city residents, businesses, visitors, workers, students, tourists and others. This layer is the catalog of smart city services or “use cases”, centered around the outcomes (Figure One), and offered by value creators and consumed by the city stakeholders.

Innovation layer. To stay relevant, value creators in the smart city must continuously innovate and update its services for its stakeholders. Smart cities proactively facilitate this through a variety of innovation programs, including labs, innovation zones, training, ideation workshops, skills development and partnerships with universities and businesses.

Governance, management and operations layer. The smart city creates disruption and results in digital transformation of existing processes and services. Smart city management models must integrate a new ecosystem of value creators and innovators. They must plan, support and monetize new business models, processes and services. They must upgrade their existing infrastructure and management processes to support “smart” services. Finally, they must measure the performance of the city with a new set of metrics.

Policy, processes, and public-private partnerships, and financing layer. The smart city doesn’t just magically appear one day. An entirely new set of engagement models, rules, financing sources, and partners are required to build, operate and maintain the smart city. Cities must develop a new set of “smart” competencies in order to get and stay in the “smart city game”.

Information and data layer. The lifeblood of the smart city is information. The smart city must facilitate this in several ways, including open data initiatives, data marketplaces, analytics services, and monetization policies. Equally important, they must have programs that encourage data sharing and privacy policies to protect what and how data is gathered.

Connectivity, accessibility and security layer. People, things and systems are interconnected in the smart city. The ability to seamlessly connect all three, manage and verify who and what is connected and shared, while protecting the information and users is crucial. The highest priorities for smart cities are to provide a seamless layer of trusted connections.

Smart city technology infrastructure layer. Most people automatically think of technology when talking about smart cities. The smart city technology infrastructure must scale beyond the traditional municipal users and support a new class of value creators, and city/user stakeholders.

 

Leveraging the smart city ecosystem framework

The smart city is a complex ecosystem of people, processes, policies, technology and other enablers working together to deliver a set of outcomes. The smart city is not “owned” exclusively by the city. Other value creators are also involved, sometimes working in collaboration and sometimes by themselves. Successful and sustainable smart cities take a programmatic approach to engage its stakeholders across the ecosystem.

Our research has found that many cities are not taking an ecosystem approach to smart city projects. This is due in part to smart city projects being managed by the Information Technology (IT) organization where their charter is on systems development and deployment. In contrast, more experienced smart cities manage their smart city programs through internal cross functional “Transformation” or “Innovation” organizations.

Regardless of where cities are in their smart city journey, they must get ahead of the “curve” with smart city projects. They begin by thinking in terms of building the broader ecosystem in order to create a sustainable and scalable smart city. Key next steps include:

  1. Understand the smart city ecosystem framework and tailor it to the realities of their specific city. Incorporate this model into the development of their smart city vision, strategy and execution plans.
  2. Relative to the smart city ecosystem framework, identify current capabilities and gaps across the various layers. Understand what is needed to support the four types of value creators.
  3. Evaluate existing and new smart city projects and initiatives against the ecosystem framework. Use this framework to identify what is missing from the project plans and what is needed to make the projects fully successful.
  4. Prioritize and develop competencies across the various ecosystem layers. A smart city requires new skills and competencies. Augment existing capabilities through strategic partnerships and contracting with service providers, as required.

 

About:

Benson Chan is an innovation catalyst at Strategy of Things, helping companies transform the Internet of Things into the Innovation of Things through its innovation laboratory, research analyst, consulting and acceleration (execution) services. He has over 25 years of scaling innovative businesses and bringing innovations to market for Fortune 500 and start-up companies. Benson shares his deep experiences in strategy, business development, marketing, product management, engineering and operations management to help IoTCentral readers address strategic and practical IoT issues.

This post was co-authored with Renil Paramel, an IoT Innovation Catalyst, Strategist and Senior Partner at Strategy of Things.

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Technologists and analysts are on a path to discovery, obtaining answers on how technology and the data collected can make our cities more efficient and cost effective. 

While IoT may be seen as another buzzword at the moment, companies like SAP, Cloud Sigma, Net Atlantic and Amazon Web Services are working to make sure that for businesses, IoT is a reality. It’s companies with this willingness to change, adopt and invent that will win the new economy. Mobile phones, online shopping, social networks, electronic communication, GPS and instrumented machinery all produce torrents of data as a by-product of their ordinary operations. Most companies want their platform to be the foundation of everything it does, whether it is with big data, data analytics, IoT or app development. The same  rub off phenomenon was emulated in Latin American countries  like Brazil, Argentina, Mexico and European countries like Brussels, Italy,  Germany, Denmark , Poland and Prague in recent times.

It is important to realize that technology is exploding before our very eyes, generating unprecedented opportunities. With easy access to cheap cloud services, smarter people came up with these platforms, and it has fundamentally changed businesses and created new ways of working. Mobile cannot be an afterthought. It needs to be integrated in everything you do and positioned at the forefront of your strategy. You have no valid reason to avoid migrating to the cloud. Cloud provides a ubiquitous, on-demand, broad network with elastic resource pooling. It’s a self-configurable, cost-effective computing and measured service. On the application side, cloud computing helps in adopting new capabilities, meeting the costs to deploy, employing viable software, and maintaining and training people on enterprise software. If enterprises want to keep pace, they need to emulate the architectures, processes and practices of these exemplary cloud providers.

One of the main factors of contributing value additions is the concept of a Smart City which is described as one that uses digital technologies or information and communication technologies to enhance the quality and performance of urban services, to reduce costs and resource consumption and to engage more effectively and actively with its citizens. We will interact and get information from these smart systems using our smartphones, watches and other wearables, and crucially, the machines will also speak to each other.The idea is to embed the advances in technology and data collection which are making the Internet of Things (IoT) a reality into the infrastructures of the environments where we live. We will interact and get information from these smart systems using our smartphones, watches and other wearables, and crucially, the machines will also speak to each other. Technologists and analysts are on a path to discovery, obtaining answers on how technology and the data collected can make our cities more efficient and cost effective. The current model adopted for IoT is to attract businesses to develop software and hardware applications in this domain. The model also encourages businesses to put their creativity to use for the greater good, making cities safer, smarter and more sustainable.

A few years ago like many others  I predicted  that Business models will be shaped by analytics, data and the cloud. Moreover, the IoT is deeply tied in with data, analytics and cloud to enable them and to improve solutions. The key goal is to ensure there is value to both customers and businesses. You can effectively put this strategy into action and build a modern data ecosystem that will transform your data into actionable insights.  

Till we meet next time...

Best,

Raj Kosaraju

CIO 

 

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Digital transformation is no longer a buzzword. No industry is left behind. 
We’re currently in a new wave of  digital transformation with new technologies, processes, business models and opportunities popping up in the market faster than we can blink & think.
All the companies are using  big datamachine learningcloud, smart devices and  Internet of Things to achieve digital. But these are just means or vehicle to achieve it whereas you need a human to drive it.
It is easy to get wrapped by technology but without considering human element the transformation process will fail.
CEOs are taking a digital-first approach to change the  culture of organizations. This shift starts at the top and requires complete employee buy-in to achieve success.
Digital transformation can’t thrive unless your organization has a culture that’s willing and able to embrace it. Organization-wide adoption requires teams to change their attitude, automate the processes, shift their thinking and reject the status quo.
People are engaged by people. Productive and satisfied employees who like their work, go out of the way to satisfy customers. 
How to get this human element on your side in Digital Transformation?
·        Know your customers – customers are not just records but they are also humans, know their  behaviors, their motivations, what they like, dislike and their desires
·        Engage with employees – elaborate on what is in it for me, people need to know what is the change and how it will benefit them
·        Focus on human collaboration, learning, and innovation for digital which yields better ideas, better results
Digitization is by no means de-humanization. It is 20% technology but 80% human touch. Without a strong involvement and without taking the human element into account on all levels, digital projects are going to fail.

The best results will occur when technology and humans collaborate to create an entire ecosystem, which technology alone cannot achieve.

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Rise of the Intelligent Revenue Machines

An early theme of digital transformation was the notion of selling services rather than products. A contract with the “thing maker” to circulate cooling fluid throughout my factory rather than a purchase order for me to buy the pumps and filters needed to do it myself, for example. The contract lets me focus on creating products for my customers rather than maintaining the machines making this possible. I don’t want to spend time on the process (pumps and filters), I just need the outcome (properly cooled machines) in the least distracting way possible to my core business of producing goods, medicine, energy, etc. The contract lets you, purveyor of the connected pumps and filters, build a closer relationship with me, streamline your business, and avoid competing in an increasingly commoditized space.

The fundamental shift happening today goes beyond providing guaranteed services rather than just hardware. Ensuring my lights stay on rather than selling me light bulbs solved your commodity hardware problem, but over time service offerings will face similar pressure as your competitors follow your connected product path and undergo digital transformations of their own. Your long term return on investment in IoT depends on more than keeping my lights on and water flowing. The value your IoT system creates for you depends on your IoT system’s ability to generate more business for me. There’s no such thing as a cheaper “good enough” replacement part when it comes to generating new revenue.

In healthcare for example, when your IoT system enables me to perform procedures in 24% less time, my clinics can perform 24% more procedures each day, increasing my revenue by 24% and delivering a 24% better patient experience. That’s what I’m looking for when I’m buying medical equipment. Depending on my corporate agility, the adoption and rollout of your connected machines may be a phased approach, following a progression of business outcomes. Asset Management means knowing the status of each device at all times and controlling them accordingly. This first step helps me see the potential value of incoming data and better understand my current utilization. Workflow Integration is connecting this information with my enterprise systems, which enables Predictive Maintenance and automatically alerts service technicians when a machine shows signs of impending failure. Where everything comes together and bonds me securely to your connected product service is Yield Optimization.

At this point your IoT system is collecting data from machines in my facilities as well as external data like weather and information from my other enterprise systems, correlating this information and uncovering patterns and ways for me to achieve more with less. Your “things” are now more than hardware installed in my facility performing physical tasks. They’re active components in a new System of Intelligence engaged in a loop of continuous learning and improvement.

This is true digital transformation, the creation of business value out of data collected and processed by your IoT solution.

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Digital has brought in so many technological advances to this age and one of them is Robotic Process Automation (RPA).
A simple definition of RPA is, automation of business processes across the enterprise using software robots. Any repetitive task which requires some decision making is an ideal candidate for RPA. Automation has become an integral part of  Digital Transformation. Implementing these software robots to perform routine business processes and eliminate inefficiencies is the key for business leaders.
Today’s organizations often need to execute millions of repetitive and time-intensive business processes each day. Using RPA they can automate administrative functions such as customer address changes, registrations and other high-volume tasks and transactions. This helps avoids human errors & also allows employees to spend more time & focus on customer-related functions for better  customer experience.
RPA is well suited for processes that are clearly defined, repeatable and rules-based. Any company that uses workforce on a large scale for general knowledge process work, where people are performing high-volume, high transactional process functions, will boost their capabilities and save money and time with RPA software.
Process automation can expedite back-office tasks in finance, procurement, supply chain management, accounting, customer service and human resources, including data entry, purchase order issuing, a creation of online access credentials.
By adding the  cognitive computing power of  Natural language processing, speech recognition, and  machine learning, businesses can achieve high-end tasks which require human interventions.
Automation of front-end operations typically involves  chatbots or conversational agents. RPA can provide answers to employees or customers in natural language rather than in software code. This can help to conserve resources for large call centers and for customer interaction centers.
As RPA brings more technologically-advanced solutions to businesses around the world, they bring a multitude of benefits as below.
·       Increased Speed: routine tasks are carried out swiftly by RPA without any intervention, thereby faster time to resolution
·       Reduced labor costs due to software robots than humans
·       Enhanced employee experience: since repetitive tasks as taken care by RPA, employees can spend quality time for strategic work and enjoy their work life
·       Higher quality: better consistency & accuracy due to minimized variations and better customer service
·       Enhanced insights: by automating the data collected and applying Big Data analytics for improved efficiency
·       Scalability: robotic workforce can be scaled to any level required
BPO industry is the most benefited sector due to RPA. Insurance, Banking industries use RPA for KYC, claims processing, policy admin, statement reconciliation, credit card application processing etc.
Automation Anywhere, Blue Prism, UiPath & Verint are some of the few top vendors in the market today.

Be ready for RPA storm coming in near future with the addition of artificial intelligence capabilities. 

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To paraphrase Geoffrey Moore, smart “thing makers” are investing in IoT solutions for their customers today in order to generate more revenue for themselves tomorrow. Traditional hardware vendors are being commoditized and replaced whenever a cheaper “good enough” option comes along. To thrive in the long run, your value must be “sticky”, embedded in your customer’s business, providing benefit to their customers as well. The “things” you sell now simply enable your customers to run their basic operations. Whenever a part breaks, customers make a decision to order a new one either from you or a competitor. How differentiated is your equipment from the rest of the market? Your business is constantly at risk.

What we’re seeing as a result are “thing makers” creating smart systems that empower their customers to not just operate, but to *optimize* their operations. These devices still perform their physical functions as before, but also collect and share a stream of data about their status and conditions in the world around them. It’s the data they produce, and the insights your system derives from this data, that enable your organization to offer far more valuable products and services to your customers that are not so easily replaced.

If you know the state of your machines at all times, you can build predictive maintenance and service models enabling guaranteed uptime and automatic replenishment. If your equipment never breaks or runs empty, your customer is unlikely to replace it with a competitor’s version.

If your products provide not just lighting and temperature control but also insights correlating usage patterns with time, weather, and utility data that reduce your customer’s costs, you can sell them this information for a percentage of these savings.

It’s the future. Your connected product system is part of your customer’s operating procedures, continuously generating insights for maximizing productivity. Improved asset utilization, faster turnarounds, synchronized workflows, and more. Smoother operations and reliable performance deliver better experiences for their customers, further expanding your customer’s business, because of your IoT solution. You don’t just sell “things.” You sell outcomes, which is what your customers really wanted in the first place.

That’s pretty smart.

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Digital disruption is omnipresent, get on board or get thrown off the track.

Digital is no longer a purview of only BankingInsuranceHealthcare or Retail. The Restaurant industry is having pressure from multiple directions. 

Today’s consumer expects fresh food, whether it is in season or not, with an exotic dining experience.

Successful restaurants recognize that the easy path to their customers' stomachs begins in their minds. They need to grab customer's attention and entice them with a memorable experience in order to trigger repeat visits.

Here are some of the applications of Digital disruption in the restaurants & food service industry:



  • Digital Signage to deliver eye-catching graphics to engage customers the moment they walk through the door
  • Online reservations using mobile app & flexibility of customization of menu as per customer taste
  • Chatbots: Restaurants are using virtual assistants to respond to customer inquiries and to process and customize customer orders. Taco Bell, Pizza hut have adopted chatbots to automate ordering process from a social media platform.
  • Robots – Restaurants are using AI-driven robots to increase capacity and speed of food preparation and delivery.
  • Recommendation engines – Developers are designing applications which use AI to help consumers choose meals & suggest foods based on their eating preferences.
  • Wi-Fi enabled dining spaces for truly engaging customer experience
  • Kiosks – Restaurants are integrating AI-driven self-service Kiosks to reduce customer waiting time and enhance the customer ordering experience.
  • Pay by phone and flexible paying options
  • Loyalty programs based on frequent visit
  • Digital supply chains to accurate demand forecasting, inventory optimization, and cost reduction.

Restaurants generate vast quantities of data through software that controls everything from scheduling food delivery and shift staffing to taking reservations to managing vendors and inventory to paying bills.

Today almost every consumer is making dining decision on their smartphone. They have tried new menu item based on the mobile ad.  Mobile payments have become the norm now in this industry. Customers would like to order quick meals via mobile and want to use mobile payments.

McDonald’s was the first store to accept Apple Pay.

Starbucks is a leader in digital transformation. Using more than 50mm Facebook fans & over 15mm Instagram followers at their disposal they mastered the social media engagement. First, they created an app to pay for coffee and food in their restaurants. Then they added the loyalty program, starting to craft hyper-personalized offers and experiences for their 24-hour connected customers. The company also developed new digital services to be enjoyed in their physical stores, achieving a highly praised omnichannel approach.

Pizza Hut has started an order and payment-enabled pepper robot. Customers can now have a personalized ordering, reduce wait time for carryout, and have a fun with the frictionless user experience.

TGI Fridays, Wendy’s and other big names have all adopted digital technology to lure their customers.

OpenTable, GrubHub, and Zomato are some of the latest apps showcasing nearby restaurants with high-quality pics, presenting a menu with exotic pictures, price, ratings etc. you can also get offers, deals instantly.

The digital technology available to restaurants has streamlined the lives of restaurant owners much like smartphones have bettered our daily lives.

Digital has entered the restaurants and food industry through the front door and brings many exciting trends.

As consumers expect Apple to come up with a new iPhone every year that makes the earlier model obsolete, similarly they want fresh ways of serving food with fantastic dining experience which is made possible by Digital disruption.

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Digital Transformation in the Fashion Industry

Gone are the days when brand communication was mostly made up of ads that appeared on billboards, in magazines and/or on television. Today, all of this is augmented with Digital revolution.
The fashion industry is engaging with digital technology in new and different ways, in order to stay competitive and to engage with the ways that consumers are searching for jewelry, clothes, and accessories.
Technology is turning the fashion industry inside out. Today, consumers are most active as digital shoppers in the Fashion industry and are demanding a heartening digital experience across channels. People love the brick-and-mortar stores but also exploit online channels through social media, while on the go and online. These  Omni-channel experiences should provide customers with a “wow” factor and  Digital Transformation is the way to achieve this objective.
In today’s fashion world, competition is fiercer than ever, giving consumers’ far greater power & they demand only the very best customer service. Most of the fashion brands now have a  social media presence on Pinterest, Instagram presence, tapping into our heightened engagement with imagery.
It can take many years to build a successful brand, but only a short time to destroy it. Fashion brands have always needed to be ready and able to respond to issues of uncertainty, risk, and reputation, all at varying times.
Burberry is the poster child in digital for fashion that started with live streaming runshows. Then came iPads and mobile apps for consumers to try out different outfits.
In Paris, a window front invites passers-by to download the Louis Vuitton Pass app in order to interact with the window and explore.
L’Oréal has put up a 'social wall' on its main website so consumers can share posts while shopping.
Harrods is the latest luxury retailer to transform its in-store experience with digital technology. They have many new super-high resolution stairwell displays at the flagship Knightsbridge, London store
Adidas has a store wall which shows shoe collections in 3D to see shoe designs from all angles.
With this availability of streaming  big data and resultant analytics, fashion brands use the insights for hyper-personalization, align consumer experience and to track customer trends. The customer’s data is the core component of digital transformation in the fashion industry. So, hyper-personalization of mobile retail experiences will be huge in the near future.
Today, dressing rooms enhanced with  augmented reality and social media features have transformed the shopping experience altogether. L’Oreal, Maybelline have already started testing special kiosks that enable shoppers to virtually try on makeup by simply taking a picture.
Even the most successful digital  retail experiences are built from desktop experiences but the future is in mobile with a predicted 80% of sales traffic coming via this medium.

With digital at a side, fashion weeks across London, Paris, Milan & New York witness runway shows streamed online, Instagram & snapchat stories in real time, creating a close connection between consumers and brands. 
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In this  Digital age, every organization is trying to apply machine learning and  artificial intelligence to their internal and external data to get actionable insights which will help them to be closer to today’s customer.

A few years back it was the field only for  data scientists and statisticians, who used to analyze the data, apply several techniques and provide results.

Today many of the organizations are using  APIs to access the ready-made algorithms available in the market as they make it easy to develop predictive applications. In fact, you don’t even need to have an in-depth knowledge of coding or computer science to introduce them into your apps.

APIs provide the abstraction layers for developers to integrate  machine learning into real world applications without worrying about which technique to use or how to scale the algorithm to their infrastructure.

These APIs can be categorized broadly into 5 groups:

  • Image and Face Recognition: It understands the content of the image, classifies the image into various categories, detects individual objects and faces, detects labels and logos from the images.
  • Language Translation: Translate text between thousands of languages, allows you to identify in which language any text that you need to analyze was written. Some APIs allows organizations to communicate with the customer in their language.
  • Speech Recognition and Conversion: Today most of the customer service is handled by Chatbots with underlying APIs helping simple question and answer. Speech to text APIs are used to convert call center voice calls into text for further analysis.
  • Text /Sentiment Analytics using NLP: With the rise of Social Media, consumers easily express and share their opinions about companies, products, services, events etc. Companies are interested in monitoring what people say about their brands in order to get feedback or enhance their marketing efforts. These APIs can identify, analyze, and extract the main content and sections from any web page. They further help in to analyze unstructured text for sentiment analysis, key phrase extraction, language detection and topic detection. There are some tools also helps in spam detection.
  • Prediction: These APIs, as the name suggests helps to predict and find out patterns in the data. Typical examples are Fraud detection, customer churn, predictive maintenance, recommender systems and forecasting etc.

Google Cloud, Microsoft Cognitive Services, Amazon Machine Learning APIs & IBM Watson APIs are the leaders in the market.

With growing number of free/reasonably priced APIs and tsunami of data generated every day, the race is on as to which is the best Machine Learning API.
These machine learning APIs are not yet perfect or matured and they will take some time to learn and act accurately. But they allow faster time to market-based on ready availability, rather than asking data scientist to code the algorithms.

In future, machine learning will lead to revolutions that will intensify human capabilities, assist people in making good choices and help navigate through the world in powerful ways, like Iron Man's Jarvis.
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Digitization is disrupting every business and is spreading like a wild fire across every sector such as Banking, Financial Services, Insurance, Retail, and Manufacturing.

Digital Transformation does not happen overnight. It is a continuous process. That is why it is very hard to plan too far ahead in a digital transformation program. The technology is evolving so rapidly that your plans will certainly change.
How do you measure return on digital transformation in order to make the timely course correction and improve its success rate? It is even more important that people who will measure the progress know the actual meaning of digital and customer behavior. You will be surprised to know that how many employees/leaders take the  customer journey themselves – buying an online policy on their own website, purchasing a merchandise or calling their own customer center to complain.
One of the ways is to break the long term plan into small doable projects with specific KPI’s. These should not last more than six months.
While traditional metrics of revenue, costs, customer satisfaction should be measured, companies should move beyond these quarterly revenue and margin guidance as they keep pulling them back to short term tactical focus. The new metrics have to be added to get the right control and visibility of progress.
Some of the new metrics which can be considered are:
·       % of  marketing spend that is digital
·       Brand value in market
·       Reach of organization in the market
·       Digital  maturity quotient of the employees including board and senior leaders 
·       % revenue through digital  channels
·       Contribution to digital initiatives from each department like purchasing, finance, HR, IT, Sales & Marketing
Customer Focus:
·       Net promoter score
·       Rate of new customer acquisition
·       Number of customer touch points addressed to improve  customer experience positively
·       % increase in customer engagement in digital channels
·       Reduction in time to market new products to customers
·       Change in customer behavior over time across channels
Return on innovation:
·       % of revenue from new products/services introduced
·       % of the profit from new ideas implemented
·       Number of innovative ideas reach concept to implementation
·       Number of new products or services launched in the market
·       Number of new  business models adopted for different class of customers
·       Rate of new apps and APIs to offer new products/services inside and outside the company
Always keep these metrics simple and measure right things and celebrate even the small successes so employees are motivated.
A digital transformation is a big  culture change so there is plenty of fear which leads to resistance. Such inertia has to be changed with clear communication, as to why it is needed to change and what benefits it will bring to each department and employee.

A lack of urgency is the greatest obstacle businesses face when considering the value of digital transformation. Proper planning is important but more than that execution as per the KPIs you select, is what take you through.

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We are all familiar with machine learning in our everyday lives. Both Amazon and Netflix use machine learning to learn our preferences and provide a better shopping and movie experience.
Artificial intelligence (AI) has stormed the world today. It is an umbrella term that includes multiple technologies, such as machine learning,  deep learning, and computer vision,  natural language processing (NLP), machine reasoning, and strong AI.
Organizations are using machine learning for various insights they want to know about consumers, products, vendors and take actions which will help grow the business, increase the consumer satisfaction or decrease the costs.
Here are some top use cases for machine learning:
·     Predicting & preventing  cyber-attacks: With WannaCry making havoc in many organizations, machine learning algorithms have become extremely important to look for patterns in how the data is accessed, and report anomalies that could predict security breaches.
·     Algorithmic Trading: Today many of financial trading decisions are made using algorithmic trading at higher speed, to make huge profits.
·      Fraud Detection: This is still one of the key issues in all the financial transactions. With the help of deep learning/artificial intelligence, the identification and prediction of frauds have become more accurate.
·      Recommendation Engines: In this digital age, every business is trying  hyper-personalization using recommendation engines to give you a right offer at right time.
·      Predictive Maintenance: With embedded sensors of  Internet of Things, many of the heavy industrial machinery manufacturers are applying machine learning to predict the failures in advance, to avoid the costly downtime and improve efficiency.
·     Text Classification: Machine Learning with NLP is used to detect spam, define the topic of a news article or document categorization.
·     Predict patient’s  readmission rates: By taking into consideration patient’s history, length of stay in hospitals, lab results, doctor’s notes, hospitals now can predict readmission to avoid penalties and improve patient care.
·     Imaging Analytics: Machine learning can supplement the skills of doctors by identifying subtle changes in imaging scans more quickly, which can lead to earlier and more accurate diagnoses.
·      Sentiment Analysis: Today, it is important to know consumer emotions while they are interacting with your business and use that for improving customer satisfaction. Nestle, Toyota is spending huge money and efforts on keeping their customer’s happy.
·     Detecting drug reactions: With Association analysis on healthcare data like-the drugs taken by patients, history & vitals of each patient, good or bad drug effects etc; drug manufacturers identify the combination of patient characteristics and medications that lead to adverse side effects of the drugs.
·      Credit Scoring & Risk Analytics: Using machine learning to score the credit worthiness of card holders, defaulters, and risk analytics.
·     Recruitment for Clinical Trials: Patients are identified to enroll into clinical trials based on history, drug effects
With today’s advanced  cognitive computing capabilities, image/speech recognition, language translation using NLP has become a reality which is used in very innovative use cases.
Machine learning is nothing new to us but today it has become the brain of  digital transformation. In future, machine learning will be like air and water as an essential part of our lives.
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Are you drowning in Data Lake?

Today more than even, every business is focusing on collecting the data and applying analytics to be competitive. Big Data Analytics has passed the hype stage and has become the essential part of business plans.

Data Lake is the latest buzzword for dumping every element of data you can find internally or externally. If you Google the term data lake, you will get more than 14 million results. With entry of  Hadoop, everyone wants to dump their siloes of data warehouses, data marts and create data lake.
The idea behind a data lake is to have one central platform to store and analyze every kind of data relevant to the enterprise. With the  digital transformation, the data generated every day has multiplied by several times and business are collecting this  consumer data, Internet of Things data and other data for further analysis. 
As the storage has become cheaper, more data is being stored in its raw format in the hopes of finding nuggets of information but eventually it becomes difficult. It is like using your  smartphone to click photographs left, right and center, but when you want to show some specific photograph to someone it’s very difficult.
Data Lakes, if not maintained properly, have the potential to grow aimlessly consuming all the budget. Some companies have their data lakes overflowing on premise systems into the  cloud.
Most data lakes lack governance, lack the tools and skills to handle large volumes of disparate data, and many lack a compelling business case. But, this water (the data) from your data lake has to be crystal clear and drinkable, else it will become a swamp.
Before getting into bandwagon of creating the data lake that may cost thousands of dollars and months to implement, you should start asking these questions.
·        What data we want to store in Data Lake?
·        How much data to be stored?
·        How will we access this massive amounts of data and get value from it easily?
Here are some guidelines to avoid drowning into data lakes.
·        First and foremost - create one or more business use cases that lay out exactly what will be done with the data that gets collected. With that exercise you will avoid dumping data, which is meaningless.
·        Determine the Returns you want to get out of Data Lake. Developing a data lake is not a casual thing. You need good business benefits coming out of it.
·        Make sure your overall big data and  analytics initiatives are designed to exploit the data lake fully & help achieve business goals
·        Instead of getting into vendor traps and their buzzwords, focus on your needs, and determine the best way to get there.
·        Deliver the data to wide audience to check and revert with feedback while creating value
There are many cloud vendors to help you out building data lakes – Microsoft Azure, Amazon S3 etc.
By making data available to  Data Scientists & anyone who needs it, for as long as they need it, data lakes are a powerful lever for innovation and disruption across industries.
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Do you want to hire a Data Scientist?

As mentioned by Tom Davenport few years back, Data Scientist is still a hottest job of century.
Data scientists are those elite people who solve business problems by analyzing tons of data and communicate the results in a very compelling way to senior leadership and persuade them to take action.
They have the critical responsibility to understand the data and help business get more knowledgeable about their customers.
The importance of Data Scientists has rose to top due to two key issues:
·     Increased need & desire among businesses to gain greater value from their data to be competitive
·     Over 80% of data/information that businesses generate and collect is unstructured or semi-structured data that need special treatment
So it is extremely important to hire a right person for the job.Requirements for being a data scientist are pretty rigorous, and truly qualified candidates are few and far between.
Data Scientists are very high in demand, hard to attract, come at a very high cost so if there is a wrong hire then it’s really more frustrating. 
Here are some guidelines for checking them:
·     Check the logical reasoning ability
·     Problem solving skills
·     Ability to collaborate & communicate with business folks
·     Practical experience on collaborating  Big Data tools
·     Statistical and  machine learning experience
·     Should be able to describe their projects very clearly where they have solved business problems
·     Should be able to tell story from the data
·     Should know the latest of  cognitive computingdeep learning
I have seen smartest data scientists in my career who do the best job best but cannot communicate the results to senior leaders effectively. Ideally they should know the data in depth and can explain its significance properly. Data visualizations comes very handy at this stage.
Today with  digital disrupting every field it has an impact on data science also.
Gartner has called this new breed as citizen data scientists. Their primary job function is outside  analytics, they don’t know much about statistics but can work on ready to use algorithms available in APIs like Watson, Tensor flow, Azure and other well-known tools.
The good data scientist can make use of them to spread the awareness and expand their influence.
It has become more important to hire a right data scientist as they will show you the results which may make or break the company.
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How Customer Analytics has evolved...

Customer analytics has been one of hottest buzzwords for years. Few years back it was only  marketing department’s monopoly carried out with limited volumes of customer data, which was stored in relational databases like Oracle or appliances like Teradata and Netezza.
SAS & SPSS were the leaders in providing customer analytics but it was restricted to conducting segmentation of customers who are likely to buy your products or services.
In the 90’s came web analytics, it was more popular for page hits, time on sessions, use of cookies for visitors and then using that for customer analytics.
By the late 2000s, Facebook, Twitter and all the other  socialchannels changed the way people interacted with brands and each other. Businesses needed to have a presence on the major social sites to stay relevant.
With the  digital age things have changed drastically. Customer is superman now. Their mobile interactions have increased substantially and they leave digital footprint everywhere they go. They are more informed, more connected, always on and looking for exceptionally simple and easy experience.
This tsunami of data has changed the customer analytics forever.
Today customer analytics is not only restricted to marketing for churn and retention but more focus is going on how to improve the customer experience and is done by every department of the organization.
A lot of companies had problems integrating large bulk of customer data between various databases and warehouse systems. They are not completely sure of which key metrics to use for profiling customers. Hence creating  customer 360 degree view became the foundation for customer analytics. It can capture all customer interactions which can be used for further analytics.
From the technology perspective, the biggest change is the introduction of  big data platforms which can do the analytics very fast on all the data organization has, instead of sampling and segmentation.
Then came  Cloud based platforms, which can scale up and down as per the need of analysis, so companies didn’t have to invest upfront on infrastructure.
Predictive models of customer churn, Retention,  Cross-Sell do exist today as well, but they run against more data than ever before.
Even analytics has further evolved from descriptive to predictive to prescriptive. Only showing what will happen next is not helping anymore but what actions you need to take is becoming more critical.
There are various ways customer analytics is carried out:
·       Acquiring all the customer data
·       Understanding the customer journey
·       Applying big data concepts to customer relationships
·       Finding high propensity prospects
·       Upselling by identifying related products and interests
·       Generating customer loyalty by discovering response patterns
·       Predicting customer lifetime value (CLV)
·       Identifying dissatisfied customers & churn patterns
·       Applying predictive analytics
·       Implementing continuous improvement
Hyper-personalization is the center stage now which gives your customer the right message, on the right platform, using the right channel, at the right time
Now via  Cognitive computing and  Artificial Intelligence using IBM Watson, Microsoft and Google cognitive services, customer analytics will become sharper as their  deep learning neural network algorithms provide a game changing aspect.
Tomorrow there may not be just plain simple customer  sentiment analyticsbased on feedbacks or surveys or social media, but with help of cognitive it may be what customer’s facial expressions show in real time.
There’s no doubt that customer analytics is absolutely essential for brand  survival.
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Go Digital or Die - What will you chose?

Just before 2007, we didn't have access to smartphones like iPhone or social media apps like Instagram, Whatsapp and even email was much more limited only to desktops. 
Zoom in to Today -  Digital Transformation has revolutionized everything we do. It has been one of the hottest topics for every business. It’s a subject which keeps the CEOs awake. 
Today it is Digital or Die.
Digital is happening fast and forcefully, whether businesses are ready for it or not. You can’t hide from it. There is a possibility that five of out ten businesses like Blockbuster, Kodak and Borders that will become  digital dinosaur because of their lack of ability to adapt.
Going digital is not about moving to a specific technology like  Cloud or  Big DataAnalytics but it is really about  accommodating a change of how technology enables business. Billions of people across the world are attached to a global high-speed, real-time Internet. 
There are over 7+ billion mobile connections worldwide. In couple of years, Millennials will make up half of the working population. They expect highly personalized products and services, they want instant-gratification and they are omni-channel, online anytime, anyplace and any device. Using  Mobile firstas your strategy to go digital is no-brainer.
As technology becomes an increasing part of our everyday lives, it also becomes a vital part of business strategy to become more efficient in customer service and disrupt the market with exemplary  customer experience.
Business models are changing, from products to services and have to have a sharp focus of extraordinary customer experience with digital, like Apple. To transform to digital, companies must place customer experience at the center of digital strategy.
Customers really want access to support via digital channels without the intervention of customer reps, unless they don’t find what they are looking for at the first point of contact or something goes wrong with the product which needs to be fixed quickly.
Burberry was one of the first players to turn their fashion shows into digital happenings. The company used the buzz around the events to lure its customer base, interact with and strengthen relationships with customers, and attract new ones.
Nike had moved on from a sports apparel company to fitness driven personalized  wearables like FuelBand manufacturer.
Apple, Disney, Nordstrom and Nestle are just a handful of the household names that have mastered digital.
It’s a never-ending program of improvement. As important as the technologies and channels, are the employee training and mastering the skill set that empowers them to thrive in this more integrated and ‘digital first’ environment. 
Working from home is adopted by many organizations and moving to cloud based systems enables your employees to do that more effectively. They can access all relevant work content and more. 
Digital should not be bolt-on to home grown age old systems but must be central theme for every touch point to customer and internal processes.
Every company is a technology company today. The pace of digital is rising exponentially, making it very difficult to be the leaders in market. Your thereat is not your traditional competitor but someone who comes up with innovative ideas to steal your  customers.
As Charles Darvin once said - It is not the strongest of the species that survives, nor the most intelligent that survives, it is the one that is the most adaptable to change

It is Digital or Die. You are an easy prey if you don’t change.

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The digital revolution has created significant opportunities and threats for every industry. Companies that cannot or do not make significant changes faster to their business model in response to a disruption are unlikely to  survive
It is extremely important to do digital maturity assessment before embarking on  digital transformation.
Digital leaders must respond to the clear and present threat of digital disruption by transforming their businesses. They must embed digital capabilities into the very heart of their business, making digital a core competency, not a bolt-on. Creating lasting transformative digital capabilities requires you to build a  customer-centric culture within your organization.
This requires new capabilities that organizations need to acquire and develop which include disruptive technologies like  Big Data, AnalyticsInternet of Things, newer business models.
Digital maturity model measures readiness of the organization to attain higher value in digital  customer engagement, digital operations or digital services. It helps in incremental adoption of digital technologies and processes to drive competitive strategies, greater operationally agility and respond to rapidly changing market conditions.
Business can use the maturity model to define the roadmap, measuring progress on the milestones.
The levels of maturity can be defined as per multiple reports available and

adopt the ones which makes more sense to your business.

·     Level 1 : Project based solutions are developed for a particular problem, no integration to home grown systems, unaware of risks and opportunities
·     Level 2 : Departmentalized projects but still not known to organization, little integration
·     Level 3 : Solutions are shared between the departments for a common business problem, better integration
·     Level 4 : Organization wide efforts of digital, highly integrated, adaptive culture for  fail fast  and improve
·     Level 5 : Driven by CXOs, customer centric and complete transformation changes happen to organization
Here are the 7 categories on which business should ask questions to all the stakeholders to gauge the maturity of Digital Transformation and identify the improvement and priorities.
1.   Strategy & Roadmap - how the business operates or transforms to increase its competitive advantage through digital initiatives which are embedded within the overall business strategy
2.   Customer – Are you providing experience to customers on their preferred channels, online, offline, anytime on any device
3.   Technology – Relevant tools and technologies to make data available across all the systems
4.   Culture – Do you have the organization structure and culture to drive the digital top down
5.   Operations – Digitizing & automating the processes to enhance business efficiency and effectiveness.
6.   Partners – Are you utilizing right partners to augment your expertise
7.   Innovation – How employees are encouraged to bring the continuous innovation to how they serve the customers
Finally you know when you are digital transformed?
·             When there is nobody having “Digital” in their title
·             There is no marketing focused on digital within the organization
·             There is no separate digital strategy than company’s business strategy
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Augmented reality (AR) means amplified reality with graphics, sounds, haptic feedback and smell to the natural world as it exists. Virtual objects and information are displayed on top of the physical world, will make its way to our phones.
Just like the  Internet of Things &  Big dataAnalytics, augmented reality is going mainstream.Search engines are already expanding on image search, allowing you to point your camera at something and search for information based on what the lens takes in.
Both video games and cell phones are driving & exploiting the development of augmented reality. Everyone from tourists to someone looking for the closest McDonalds can now benefit from the ability to place computer-generated graphics in their field of vision.
Unlike  Virtual Reality, which creates a totally artificial environment like you are on the top of Eiffel tower or looking at Taj Mahal right now from your living room couch, augmented reality uses the existing environment and overlays new information on top of it.
Pokemon Go released in 2016 was the most successful game to use AR to superimpose Pokemon on physical background and all children and adults were mad chasing them in real world.
Recent innovation, Heads-Up Display (HUDs) glass with AR superimpose crystal-clear driving directions on top of the real world so you can easily navigate without taking your eyes off the road. It’s like Pokemon Go but all the adorable monsters have been replaced by driving directions.
Digital Marketing will get a boost with AR.  A new augmented reality campaign from Pepsi Max have stunned people in London, giving experiences like a prowling tiger, a meteor crashing, an alien tentacle grabbing people on the street, the bus stop window serves as a scarily realistic screen to bring these scenarios to life.
With AR, you can view your living room on a smartphone and see how virtual furniture would fit into the real world and decide what is good to buy.
Artificial Intelligence has brought virtual assistants like Siri, Alexa, Cortana, Google to life but AR can put a face to it and beef up the experience. Microsoft Hololens is currently leading the AR headset race. 
There are several industries that will benefit from AR applications, including healthcare, tourism and entertainment. However, it is  retailers who are the ones to use it more. With AR, your retail website is brought to life with a 360° online presentation of your store. In-store, augmented reality can easily display information and other visuals on packaged items with a simple image scan.
Lego’s “Digital Box” Provides Customers with an Interactive 3D Digital Experience. Aside from kiosks in stores, soon they will have mobile devices to be equipped with the capability to instantly bring up relevant information about any product in real-time.
Fashion retailer Forever 21 had put up a giant billboard which features a model walking in front of an image of the crowd below. The model occasionally leans over, and pluck someone out of the crowd. Sometimes, she drops them in her bag and happily walks off.
French cosmetic super chain Sephora is one of the leaders in AR marketing area. Their mobile apps & AR mirrors allow people to see how clothing, jewelry, and accessories look on them.
Augmented Reality cleverly blurs the line between the digital and the real by way of specially designed apps and unique visual ‘markers’ to intuitively visualise 3D virtual forms in physical realms.
We are still in the very early days of AR, and all of the future possibilities are difficult to imagine at this point. As this technology advances and gets more affordable, it will be easier for businesses to take advantage of it. AR helps to bridge the divide between the  digital and offline world.
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Digital Transformation is a phenomenon that every company must deal with and it is a reality. It is a top priority for boardroom executives. Most companies know that digital transformation is vital to survival.
Customers are demanding new instant experiences, partners want more visibility & greater access, and employees want greater convenience and work from anywhere.
Many companies are claiming that they have started it but those initiatives are isolated or tactical.  If not executed properly the only result is failure.
As you will look at weather reports, travel times, flight connections, hotel reviews before going on holiday journey, similarly you will need a road map for navigation from point A to point B.
The digital roadmap has 3 main leavers:
·        Strategy: to make it completely clear how digital transformation support overall business strategy,  define 30,60,90 days & beyond plan for measurements
·        Technology:  what are the tools and technologies you will need to go from current state to future state –  big dataanalyticsmobilityIoTcloud, microservices etc, dedicated hardware, software innovation labs, standards, guidelines, security
·        Processes & People: who are the leaders to drive the digital, what is the organization structure, operational integration of all processes, how to change to customer centric culture, training to employees and empower them
It is all about starting with  baby steps, gaining trust from business by delivering quick value and celebrating and marketing the successes to generate internal buzz.
The roadmap begins with a digital vision, mission & assessment of the digital maturity of your business today. Once the assessment and vision are completed, then next step it becomes possible to identify the systemic gaps that need to be filled. Then those steps can be built into the roadmap.
Here are the broad milestones of a successful digital transformation roadmap:
·        Boardroom/Senior management buy in, decision to go Digital and drive it across organization
·         Cultural alignment & commitment to Digital from board of directors to entry level employees
·        Identify and assess the current state of the organization on Digital
·        Put Customer first - Prepare customer  journey maps to identify all the touch points with organization
·        Find out pain areas at each touch point and respective stakeholders involved who can correct them
·        Prioritize and break them in small projects to adopt  fail fast approach. If anything did not work, just accept the failure, publish the learnings and move on.
·        Seek partners to help you in your journey, who take shared risk and shared rewards
·        Deploy agile implementation approach for quick results
·        Market your successes to whole world and repeat the process for next pain area
Transformation programs may be massive and take place over multiple years, but understanding the ROI for each phase helps keep a multi-year journey on track. With a structured approach, all of the moving parts can be managed and progress sustained throughout this journey.
Finally, you know when you are digital transformed?
·        When there is nobody having “digital” in their title
·        There is no separate digital strategy than company’s business strategy
·        There are no posters or marketing focused on digital within the organization
Enterprises that adapt, evolve and exploit this new digital reality will thrive, while those that do not, will be lost to the sands of time like  Dinosaur.
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