Are you drowning in Data Lake?

Today more than ever, 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 an entry of Hadoop, everyone wants to dump their silos 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 on the 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?ilo

·        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.

Beyond SMAC – Digital twister of disruption!!

Have your seen the 1996 movie Twister, based on tornadoes disrupting the neighborhoods? A group of people were shown trying to perfect the devices called Dorothy which has hundreds of sensors to be released in the center of twister so proper data can be collected to create a more advanced warning system and save people.

Today if we apply the same analogy – digital is disrupting every business, if you stand still and don’t adapt you will become digital dinosaur. Everyone wants to get that advance warning of what is coming ahead.

Even if your business is doing strong right now, you will never know who will disrupt you tomorrow.

We have seen these disruption waves and innovations in technologies – mainframe era, mini computers era, personal computers & client-server era and internet era. Then came the 5^th wave of SMAC era comprising Social, 

Mobile, Analytics and Cloud technologies.

Gone are the days when we used to wait for vacations to meet our families and friends by travelling to native place or abroad. Today all of us are interacting with each other on social media rather than in person on Facebook, Whastapp, Instagram, Snapchat and so on.

Mobile enablement has helped us anytime, anywhere, any device interaction with consumers. We stare at smarphone screen more than 200 times a day.

Analytics came in to power the hyper-personalization in each interaction and send relevant offers, communications to customers. The descriptive analytics gave the power to know what is happening to the business right now, while predictive analytics gave the insight of what may happen. Going further prescriptive analytics gave the foresight of what actions to be taken to make things happens.

Cloud gave organizations the ability to quickly scale up at lower cost as the computing requirements grow with secure private clouds.

Today we are in the 6^th wave of disruption beyond SMAC era - into Digital Transformation, bringing Big Data, Internet of things, APIs, Microservices, Robotics, 3d printing, augmented reality/virtual reality, wearables, drones, beacons and blockchain.

Big Data allows to store all the tons of data generated in the universe to be used further for competitive edge.

Internet of Things allows machines, computers, smart devices communicate with each other and help us carry out various tasks remotely.

APIs are getting lot of attention as they are easy, lightweight, can be plugged into virtually any system and highly customizable to ensure data flows between disparate systems.

Microservices are independently developed & deployable, small, modular services. 

Robotics is bringing the wave of intelligent automation with help of cognitive computing.

3D printing or additive manufacturing is taking the several industries like medical, military, engineering & manufacturing by storm.

Augmented reality / virtual reality is changing the travel, real estate and education.

Wearables such as smart watches, health trackers, Google Glass can help real time updates,  ensure better health & enable hands-free process optimization in areas like item picking in a warehouse.

Drones have come out of military zone and available for common use. Amazon, Dominos are using it for delivery while Insurance & Agriculture are using it for aerial surveys.

Beacons are revolutionizing the customer experience with in-store analytics, proximity marketing, indoor navigation and contact less payments.

The new kid on the block is blockchain where finance industry is all set to take advantage of this technology.

As products and services are getting more digitized, traditional business processes, business models and even business are getting disrupted.

The only way to survive this twister is to get closer to your customers by offering a radically different way of doing business that’s faster, simpler and cheaper.

What is the difference between Consumer IoT and Industrial IoT (IIoT)?

Internet of Things (IoT) began as an emerging trend and has now become one of the key element of Digital Transformation that is driving the world in many respects.

If your thermostat or refrigerator is connected to the Internet, then it is part of the consumer IoT.  If your factory equipment have sensors connected to internet, then it is part of Industrial IoT (IIoT).

IoT has an impact on end consumers, while IIoT has an impact on industries like Manufacturing, Aviation, Utility, Agriculture, Oil & Gas, Transportation, Energy and Healthcare.

IoT refers to the use of "smart" objects, which are everyday things from cars and home appliances to athletic shoes and light switches that can connect to the Internet, transmitting and receiving data and connecting the physical world to the digital world.

IoT is mostly about human interaction with objects. Devices can alert users when certain events or situations occur or monitor activities:

·       Google Nest sends an alert when temperature in the house dropped below 68 degrees

·       Garage door sensors alert when open

·       Turn up the heat and turn on the driveway lights a half hour before you arrive at your home

·       Meeting room that turns off lights when no one is using it

·       A/C switch off when windows are open

IIoT on the other hand, focus more workers safety, productivity & monitors activities and conditions with remote control functions ability:

·       Drones to monitor oil pipelines

·       Sensors to monitor Chemical factories, drilling equipment, excavators, earth movers

·       Tractors and sprayers in agriculture

·       Smart cities might be a mix of commercial and IIoT.

IoT is important but not critical while IIoT failure often results in life-threatening or other emergency situations.

IIoT provides an unprecedented level of visibility throughout the supply chain. Individual items, cases, pallets, containers and vehicles can be equipped with auto identification tags and tied to GPS-enabled connections to continuously update location and movement.

IoT generates medium or high volume of data while IIoT generates very huge amounts of data (A single turbine compressor blade can generate more than 500GB of data per day) so includes Big Data, Cloud computing, machine learning as necessary computing requirements.

In future, IoT will continue to enhance our lives as consumers while IIoT will enable efficient management of entire supply chain.

All You Need To Know About Business Models in Digital Transformation

In very simple terms, the Business model is how you plan to make money from your business. 

A refined version is how you create and deliver value to customers. Your strategy tells you where you want to go and the business model tells you how you are going to do it.

In this time of industry 4.0 with Digital Transformation, businesses are getting disrupted faster than they get established. We all know what Apple did for music, Uber did for taxis and Airbnb did for hotels.

Digital is helping them to enhance their existing products and services and helping to launch new products and services.

Companies are using various business models to be successful:

• Freemium model: Basic products/services are provided free but users are charged for advanced features. E.g. Coursera, LinkedIn, Spotify, Dropbox, Skype
• Pay as you go or Subscription Model: Pay only for services which are used. E.g. Netflix, Kindle, New York Times, Safari Books online
• Customer experience model: provide the customer experience never before e.g. Tesla, Disney Land, Apple
• On-Demand model: provide customer service on demand with speed. E.g. Uber, cloud services from Amazon, Microsoft
• Marketplace model: provide a platform for buyer and seller interact with each other directly e.g. eBay, Alibaba
• Free model: provide the typical services to users free and sell their behavior data to different businesses e.g. Google, Facebook, PatientsLikeMe
• Crowd-sourcing model: receive money for an engaging crowd for a common goal, innovation, problem-solving. E.g. Kaggle, CrowdAnalytix
• Bundling model: selling similar products or services together. E.g. Microsoft Office        
• Gamification model: use of game like feature to simplify the interaction. E.g Mint.com, Khan Academy, Nike +

 

Some of the big companies moved on from their core business model and adapted to the change embracing digital to get closer to customers in real time and grow exponentially.

Nike had moved on from a sports apparel company to fitness driven personalized wearables like FuelBand manufacturer.

Amazon started in 1995 as an online bookstore but went on to become a leader in technologies like Cloud, Drones, web services. 

Philips started as Light Bulb Company and moved on to become the leader in healthcare equipment’s touching millions of people lives.

GE has moved forward from its core industrial products – from jet engines and gas turbines to CT/PET scanners, locomotives with sensors that monitor various parts of the machinery. They developed their own Predix IoT platform with advanced analytics to provide real-time information to improve efficiency, increase productivity, and schedule more effective preventive maintenance.

Apple adopted multiple models from PC manufacturer to selling online music, to subscription model of iCloud.

Changing the business model drastically may not work. Don’t try to boil the ocean but start with how you can deliver greater value to customers through digital technology.

Success in choosing one business model over another will depend on how well companies understand their customers’ needs. 

This is how Analytics is changing the game of Sports!!

Analytics and Big Data have disrupted many industries, and now they are on the edge of scoring major points in sports. Over the past few years, the world of sports has experienced an explosion in the use of analytics

Till few years back experience, gut feelings, and superstition have traditionally shaped the decision making process in sports.

It is first started with Oakland Athletics' General Manager, Billy Beane, who applied analytics for selecting right players. This was the first known use of statistics and data to make decisions in professional sports.

Today, every major professional sports team either has an analytics department or an analytics expert on staff.  From coaches and players to front offices and businesses, analytics can make a difference in scoring touchdowns, signing contracts or preventing injuries.

Big name organizations such as the Chicago Cubs, and Golden State Warriors are realizing that this is the future of sports and it is in their best interest to ride the wave while everyone else is trying to learn how to surf.

Golden State Warriors, have similarly used big data sets to help owners and coaches recruit players and execute game plans.

SportVu has six cameras installed in the NBA arenas to track the movements of every player on the court and the basketball 25 times per second. The data collected provides a plethora of innovative statistics based on speed, distance, player separation and ball possession to improve next games.

Adidas miCoach app works by having players attach a wearable device to their jerseys. Data from the device shows the coach who the top performers are and who needs rest. It also provides real-time stats on each player, such as speed, heart rate and acceleration.

Patriots developed a mobile app called Patriots Game Day Live, available to anyone attending a game at Gillette Stadium. With this app, they are trying to predict the wants and needs of fans, special content to be delivered, in-seat concession ordering and bathroom wait times.

FiveThirtyEight.com, provides details into more than just baseball coverage. It has over 20 journalists crunching numbers for fans to gain a better understanding of an upcoming game, series or season.

Motus’ new sleeves for tracking a pitcher’s throwing motion, measuring arm stress, speed and shoulder rotation. The advanced data generated from this increases a player’s health, performance and career. Experts can now predict with greater confidence if and when a pitcher with a certain throwing style will get injured.

In the recent Cricket world cup, every team had its own team of Data Analysts. They used various technologies like Cloud Platform and visualizations to predict scores, player performance, player profiles and more. Around 40 years’ worth of Cricket World Cup data is being mined to produce insights that enhances the viewer's experience. 

Analytics can advance the sports fans' experience as teams and ticket vendors compete with the at-home experience -- the better they know their fans, the better they can cater to them.

This collection of data is also used for internet ads, which can help with the expansion and growth of your organization through social media platforms or websites. 

• What would be the most profitable food served at the concession stand?
• What would be the best prices to sell game day tickets?
• Determine which player on the team is the most productive?
• Which players in the draft will become all-stars, and which ones will be considered role players?
• Understand the fans behavior at the stadium via their app and push relevant information accordingly.

In this Digital age, Analytics are the present and future of professional sports. Any team that does not apply them to the fullest is at a competitive disadvantage.

Fail fast approach to Digital Transformation

Digital Transformation is changing the way customers think & demand new products or services.

Today Bank accounts are opened online, Insurance claims are filed online, patient’s health is monitored online while buying things online is the thing of past. Everything is here and now in real time.

Till a few years back any failure of decision making in business was scary & not acceptable. It had cost companies to go out of the fortune 100 lists. Blockbuster, Nokia, Kodak, Blackberry are well-known examples of not trying new experiments quickly.

But with the digital era, failure is accepted & it is seen as part and parcel of a successful digital business. Failure must be fast, and the lessons of failure learned should be even faster. It allows businesses to take a shotgun approach to digital transformation.

Fail fast is all about deploying quick pilots and check the outcome. If it does not work then drop the concept/idea and move on to the new one. Be prepared to change the pace or direction as necessary.

No business will undergo the digital transformation without making any mistakes. Even if an organization has the best possible culture & strategy in place, there will be stumbling blocks on the road to success. With the digital technologies like Cloud, Big Data, Analytics, Mobility, Internet of Things, at the disposal, organizations can test innovative ideas quickly before even reaching out to the customer for feedback.

Speed is of the essence here. Testing all the ideas without making huge investments, then delivering the applications in weeks and not months or years to remain competitive. This change has helped organizations to reduce the time-to-market of enhancement on customer experience.

Apple is an example of a company which failed but didn’t give up. It moved on, refined its approach, improved its R&D and eventually launched the product its customers deserved.

Domino's bounced back from customers comments like “your pizza tastes like a cardboard”. With the reboot of the menu in 2009 & digital technology, they experimented online ordering, created a tracker, which allowed customers to follow their pizza from the oven to their doorstep.

Air New Zeland has gone from posting the largest corporate loss in its country’s history to being one of the world’s most consistently profitable airlines by using Big Data Analytics to enhance the customer experience in many ways including biometric baggage check-in, an electronic “air band” for unaccompanied minors.

There are several individual examples of failures and success over time:

·        Steve Jobs was fired from the Apple but came back as CEO & made history

·        Thomas Edison failed over 10000 times before success of light bulb

·        J K Rowling of Harry Potter had lots of failures

·        Michael Jordan succeeded after his constant failure to win

But organizations don’t have this time at their hand. They can learn a lot from these individuals failures but quickly move on and achieve success in Digital Transformation.

In Digital Transformation, fail fast is not an option but it is a requirement!!

Digital disruption in Customer Experience

In an age of digital disruption, great customer experience has become do or die. 

Digital technologies such as Analytics, Mobile, Cloud, Gamification, Cognitive computing, Artificial Intelligence and Social media have disrupted the customer experience.

Customer satisfaction has never been a higher priority than it is today, where fierce competition for space in the market means loyalties can change for the smallest reason.

Whether a customer is visiting the store, making a purchase through a mobile app, or liking a photo on Instagram, they must be able to engage your brand in a way that is both seamless and effortless, regardless of the device or channel. Match your channels to your customers’ needs and they’ll keep coming back.

Timing is everything in this ever-changing digital world. Every customer is a digital customer.

No matter your industry, every organization must deeply consider and transform the way they handle customer service. 

Understanding customers - their behavior, frustrations and needs - will allow you to identify what unique value you can bring to them. Big data analytics enable marketers to send customer communications that are more relevant, personalized and targeted than ever before

Initially considered a gaming innovation, virtual reality is turning out to be more mainstream, and the applications for organizations and purchasers are abundant.

Here are some of the reasons customers are giving for loving top brands:

• They are easy to do business with
• Hyper personalization that makes me feel great
• They are quick to resolve my queries
• Their product are class apart and their service is super
• Technical knowledge of their customer service staff is excellent
• They know me well when I call 

Today it seems that we’re not far from having drones landing on our lawns! The first time you experience something like this, it feels like a revelation but later it  will feel like it’s the norm.

Today’s customer delights are tomorrow's customer expectations. Apple, Google, Disney, Starbucks, Airbnb, and Amazon are just a few companies delivering these every day. Are you?

9 steps to Successful Digital Transformation

Today nobody is bothered about if you need to go for Digital Transformation but when and how you are doing it.

All new programs or initiatives should now take a ‘Digital First’ approach, with the rapid evolution in social media, mobile, big data analytics and cloud. 

Consumers of all ages are using wide range of digital channels and are increasingly expecting high standards of digitization.

If an organization fails in attempt to digitally transform its business, then there will be multiple predators to eat them out.

Digital Transformation will involve various leading edge technologies like:

• Social media
• Mobile 
• Big Data Analytics
• Cloud computing
• Internet of things
• API management
• User Experience - Responsive web design
• Microservices
• Artificial Intelligence and Machine Learning
• Virtual Reality - Augmented reality
• Wearables
• 3D printing
• Robotics
• Drones
• Beacons
• Blockchain

Here are the steps to be successful in digital transformation:

1. Boardroom/Senior management buy in, decision to go Digital and drive it across organization
2. Cultural alignment & commitment to Digital from board of directors to entry level employees
3. Identify and assess the current state of the organization on Digital
4. Put Customer first - Prepare customer journey maps to identify all the touch points with organization
5. Find out pain areas at each touch point and respective stakeholders involved who can correct them
6. 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.
7. Seek partners to help you in your journey, who take shared risk and shared rewards
8. Deploy agile implementation approach for quick results
9. Market your successes to whole world

Some of the successful Digitally Transformed organizations are:

• Apple – do you need introduction?
• Uber – disrupted taxi industry
• Airbnb – disrupted hotel industry
• Disney – most loved brand in the world
• Tesla – disrupted auto industry
• CVS Health – leader in pharmacy
• Burberry - retail
•  John Deere – manufacturing

Digital Transformation can be achieved only with change of mindset and commitment across the organization. 

There is very little time now for businesses to capitalize on Digital Transformation opportunity to win and serve their customers, to create new products and services that customers want.