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digital transformation (57)

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 issuperman 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 forchurn and retention but more focus is going on how to improve thecustomer 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 toprescriptive. 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 areomni-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 theirpreferred 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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What are Digital Twins?

Digital Transformation has brought in all the new concepts and technologies at the hands of consumers and businesses alike.
Digital Twin is one of them. It is a virtual image of your machine or asset, maintained throughout thelife cycle and easily accessible at any time. It involves internet of things connected devices generating real time data in Big Data platform.  This data is further analyzed in the cloud.
With a digital twin, machine manufacturers are able to use the power of digitalization to achieve improved efficiency and quality. This approach helps ensure optimized machine design and smooth operation.
Today, machine intelligence and connectivity to the cloud allows a huge potential of digital twin technology for companies in a variety of industries
Digital Twin allows the asset operator to predict precisely when maintenance will be required based on the unique conditions, experienced by that particular asset.
GE has built a digital wind farm collecting data from turbine sensors, which uses big data and the Industrial Internet to drive down the cost of renewable electricity.
Here are the several advantages of Digital Twin technology:
·        Explore the impact of various design alternatives
·        Do simulations and testing to ensure that product designs will meet requirement
·        Understand how a projected change to a manufacturing process might impact costs or schedule
·        see the current operating status along with any recent alarms and maintenance performed on a machine
·        be instructed on how to perform proper maintenance procedures, for the specific problem they’re addressing
·        Preventing the failure, or anticipating it and doing the required maintenancebefore failure occurs, can shorten outages
Digital twins give airlines a better idea of what happens when a jet flies through a flock of birds, or through dust storms in hot environments.
The digital twin, combined with advanced analytical tools and machine learning, will provide a platform that changes the traditional way of how we look at the analysis of asset’s condition and performance.

It will enable a new generation of advanced predictive analytics.
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Top 5 uses of Internet of Things!!

While many organizations are creating tremendous value from the IoT, some organizations are still struggling to get started.  It has now become one of the key element of Digital Transformation that is driving the world in many respects.
It is really a time to look beyond the hype and get real about Internet of Things.
Just putting IoT in place may not help organizations but applyinganalytics is extremely essential for the success of IoT systems for better decision making.
Here are top 5 areas where IoT is making the disruption:
1.     Wellness - IoT helps continuously monitor the patients and symptoms to early detection, diagnosis & accelerate breakthrough drug development. Wearables like Fitbit, Apple watch, and Samsung have all created new revenue streams from giving their users workout analytics and the ability to set daily health goals. Mobile apps around wellness have been around for years now to track your sleep, weight, nutrition, and more. 
2.     Safety and Security – Sensor based monitoring of elevators, escalators improves travelers safety at airports.  Sensors, which are much cheaper these days, can let you know whether or not your water pipes are leaking or are about to burst. The droneswill allow the handful of rangers to quickly investigate reports of fires, than traveling into remote parts of the jungle over unpaved roads. Connected cars allows vehicle diagnostics and real time intervention from technicians for better safety.
3.     Marketing – with use of IoT, businesses can reach to right customer at at right time using geofencing. It is a virtual field in which apps are capable of sending alerts depending on your entrance or exit from a vicinity. With geofencing, your shopping experience can be more hyper-personalized to what you’re looking for. 1-800-Flowers covered the area around jewelry stores that were close to their flower shops to encourage customers to buy flowers with jewelry. Amazon Go is Amazon’s store concept without a check-out line. 
4.     Smart Cities & Smart Infrastructure – IoT is helping build the infrastructure which is really smart in quick response and improves the life of residents. Real time weather response systems, better traffic management, waste management, and optimal utilities management helps governments around the world.  Smart Homes helps people more peaceful life.
5.     Energy, Aviation & Manufacturing – Using IoT to do predictive maintenance can reduce downtime up to 50%. Companies like GE have put up 100s of sensors across the plant that provide round-the-clock monitoring and diagnostics of existing hardware. IoT enabled engines consume almost 15% less fuel than average jet engines, and also have reduced emissions and noise.  Smart grids helps in increasing the reliability and efficiency of grid, avoid thefts.
In future IoT will continue to enhance our lives more and more by tracking our needs in real time giving opportunity to businesses to react accordingly and immediately.
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Cybersecurity in Digital age

You must have heard about the global cyberattack of WannaCry ransomware in over 200 countries. It encrypted all the files on the machine and asked for payment. Ransomware, which demands payment after launching a cyber-attack, has become a rising trend among hackers looking for a quick payout.
Every day it seems another news breaks about cyber-criminals hacking in and stealing data, & information. Private companies, government agencies, hospitals…no one is immune. Cybersecurity is no longer buried in the tech section of organizations, newspapers and websites - its front-page news.
With the penetration of the digital movement, cyber-attacks have also doubled year over year, making businesses and government sites more vulnerable.
In simple terms cybersecurity is use of digital technologies to protect company networks, computers and programs from unauthorized access and subsequent damage.
In recent times, every organization has launched a “go-digital” initiative. This has led to explosion of connected environments.
The growing mobility trend has sparked a rapid growth of endpoints that must be secured, and bring-your-own-device (BYOD) programs mean that employees could be accessing sensitive data on unsecured devices.
The prevalence of cloud based services and third party data storing has opened up new areas of risk.
As businesses adopt the new technologies like Big Data, Analytics, IoT & Mobility, the focus must be on how to safeguard the data spread across devices and cloud.
Cybersecurity must be a key factor during your journey to digitally transforming your business, just as you would ensure that your offices, brick-and-mortar store has locks and security systems of the highest quality, your digital storefront must have the same levels of security. If consumers do not trust these digital storefront with their data, or if that trust is broken because of a data breach, the cost to rebuild that trust is incredibly high.
The best way to protect yourself is to be suspicious of unsolicited emails and always type out web addresses yourself rather than clicking on links.
There are different types of attacks we have seen so far:
·        Hackers target the software vulnerabilities that are yet to be discovered  and patched
·        Attack on mobile devices: malwares designed specifically for smartphones to steal data
·        Data leakage: hackers steal the data by interrupting the traffic between organization and cloud environments
·        Programming: hackers use malicious code on any server that gets replicated and allow them to delete, steal data
There are multiple ways to combat these cyber-attacks:
·        Network defense: detect unwarranted traffic e.g. someone communicating with malicious host, malware entry into the network, unauthorized data transfer
·        Detect user access violations: misuse of user access within the system, ensure proper authentications, use of antivirus, malware to prevent steal user information
·        Mobile device protection: detect unauthorized devices or prevent hackers from compromising individual devices.
·        Protect data in motion & rest: ensure data transfers protected within various environments
·        Investment in securing IoT devices – today with everything is connected it is extremely important to secure all access points.
Today with machine learning organizations are in a very good position to know what users are doing that can affect the network and increase risk. Artificial Intelligence is used to constantly learn new malware behaviors and recognize how viruses may mutate to try and get around security systems.
Traditional IT security practices like network monitoring and segmentation will become even more critical as businesses and governments deploy IoT devices.

Recent events have highlighted the growing need for enhanced cybersecurity.

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18 Big Data tools you need to know!!

In today’s digital transformation, big data has given organization an edge to analyze the customer behavior & hyper-personalize every interaction which results into cross-sell, improved customer experience and obviously more revenues.
The market for Big Data has grown up steadily as more and more enterprises have implemented a data-driven strategy. While Apache Hadoop is the most well-established tool for analyzing big data, there are thousands of big data tools out there. All of them promising to save you time, money and help you uncover never-before-seen business insights.
I have selected few to get you going….
Avro: It was developed by Doug Cutting & used for data serialization for encoding the schema of Hadoop files.
 
Cassandra: is a distributed and Open Source database. Designed to handle large amounts of distributed data across commodity servers while providing a highly available service. It is a NoSQL solution that was initially developed by Facebook. It is used by many organizations like Netflix, Cisco, Twitter.
 
Drill: An open source distributed system for performing interactive analysis on large-scale datasets. It is similar to Google’s Dremel, and is managed by Apache.
 
Elasticsearch: An open source search engine built on Apache Lucene. It is developed on Java, can power extremely fast searches that support your data discovery applications.
 
Flume: is a framework for populating Hadoop with data from web servers, application servers and mobile devices. It is the plumbing between sources and Hadoop.
 
HCatalog: is a centralized metadata management and sharing service for Apache Hadoop. It allows for a unified view of all data in Hadoop clusters and allows diverse tools, including Pig and Hive, to process any data elements without needing to know physically where in the cluster the data is stored.
 
Impala: provides fast, interactive SQL queries directly on your Apache Hadoop data stored in HDFS or HBase using the same metadata, SQL syntax (Hive SQL), ODBC driver and user interface (Hue Beeswax) as Apache Hive. This provides a familiar and unified platform for batch-oriented or real-time queries.
 
JSON: Many of today’s NoSQL databases store data in the JSON (JavaScript Object Notation) format that’s become popular with Web developers
 
Kafka: is a distributed publish-subscribe messaging system that offers a solution capable of handling all data flow activity and processing these data on a consumer website. This type of data (page views, searches, and other user actions) are a key ingredient in the current social web.
 
MongoDB: is a NoSQL database oriented to documents, developed under the open source concept. This comes with full index support and the flexibility to index any attribute and scale horizontally without affecting functionality.
 
Neo4j: is a graph database & boasts performance improvements of up to 1000x or more when in comparison with relational databases.
Oozie: is a workflow processing system that lets users define a series of jobs written in multiple languages – such as Map Reduce, Pig and Hive. It further intelligently links them to one another. Oozie allows users to specify dependancies.
 
Pig: is a Hadoop-based language developed by Yahoo. It is relatively easy to learn and is adept at very deep, very long data pipelines.
 
Storm: is a system of real-time distributed computing, open source and free.  Storm makes it easy to reliably process unstructured data flows in the field of real-time processing. Storm is fault-tolerant and works with nearly all programming languages, though typically Java is used. Descending from the Apache family, Storm is now owned by Twitter.
 
Tableau: is a data visualization tool with a primary focus on business intelligence. You can create maps, bar charts, scatter plots and more without the need for programming. They recently released a web connector that allows you to connect to a database or API thus giving you the ability to get live data in a visualization.
 
ZooKeeper: is a service that provides centralized configuration and open code name registration for large distributed systems. 
 
Everyday many more tools are getting added the big data technology stack and its extremely difficult to cope up with each and every tool. Select few which you can master and continue upgrading your knowledge.
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