Sunday, 18 June 2017

Top 10 tips for Digital Transformation

Digital Transformation is changing the way customers think & demand new products or services. There is so much discussed in various forums as to how to go digital. No business will undergo digital transformation without making any mistakes. 


Here are my top 10 tips to make it successful.

Evangelize Digital internally, externally and celebrate even the small successes!!
It is extremely important to evangelize the digital within the organization and to the external stakeholders – employees, partners, suppliers, customers.

Celebrate each and every small success to make it visible at all levels to increase the moral of the team and show the value to leadership.

First assess your organization digital maturity, then identify digital trends impacting your industry and act!!
Getting to know where you stand on the digital maturity is extremely important so that you can create a roadmap as to where you want to go. Identify important trends in your industry and plug the gaps.

Deal first with Organization's internal resistance to change, for Digital Transformation!!
There are various organizational politics which will hold you back or stall your digital transformation efforts. Resolve all the internal politics and resistance to change before embarking on bigger journey. Culture change is absolutely essential.

Identify what Customer need from your service, not what your organization thinks they need. Transform accordingly.
Find out what your customer wants in real sense than assuming what they want. Once you know that, prioritize the unmet needs of the customer and take them head on.




Work with each senior stakeholder, to quantify the extent to which their business function will benefit from the digitization
If you work in silos, then you will miss the rigor and advantage of digitization. Get each and every senior stakeholder by your side by explaining them the benefit to their function. Some companies have hired Chief Digital Officer to get organizational alignment.


Recruit right people with right technology for success!!
It all depends on how expert your team is. If you don’t have right people on the job, then hire them from outside. Technical expertise plays a significant role in digital transformation.


Avoid the cost of trying to do it internally and then learning, bring in the expert to do the job!!
Ensure you have time on your side. If you keep on learning by own mistakes you will miss the tide and cost a business. Get an expert from outside if he/she is not available internally.


Treat Digital as a new born baby who takes over a year to walk on its own. Have patience to see the results!!
Never expect the returns immediately. Digital Transformation requires proper nurturing like a baby hence set the expectations of senior management of RoI.





Establish and communicate a clear vision of digital transformation for the business, and individual stakeholders.


Have a proper vision defined for organization and communicate it to all the levels of hierarchy to ensure everyone is on same page.




Fail Fast, Be flexible and prepare to change your pace/direction if needed.
Finally be flexible and be happy to fail fast but learn quickly and move on to new ideas to try out.

Sunday, 11 June 2017

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 applying analytics 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.     WellnessIoT 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 drones will 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.


Sunday, 4 June 2017

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.

Saturday, 27 May 2017

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.

Sunday, 21 May 2017

Top 7 Virtual Reality Industry use cases

Today Digital Transformation has entered our life and we have been subconsciously using it in our day to day life. e.g. Smartphones, Smart cars, internet connected devices etc.

Virtual Reality technology has evolved dramatically in the past few years the costs of VR devices has gone down so it is all set to hit mainstream markets soon. While gaming applications like Pokemon Go have attracted most of the attention, there are many other use cases that could have a much larger impact on our lives.

Google Cardboard is a super low-cost headset ($15) to which a compatible, VR enabled mobile phone is attached to deliver the VR experience.

Other commercial product is Oculus Rift gear which has become extremely popular in gaming & business equally.

Here are some great VR use cases:

1.     VR for Tourism: do you want to sit on your couch and climb up the Eiffel tower? Or walk on the glass horse shoe at grand canyon? Wild Within is VR app available for experience of travel through rain forest in Canada. Travelers around the world are able to experience a helicopter flight around New York City or a boat ride around the Statue of Liberty.

2.     VR for Education: Over last decade eLearning had picked up very much. But it could not deliver hands on experience which is now possible with VR technology. Technicians can actually learn the real life examples and do their bit to solve the problems on the shop floor. Medical students can actually perform surgeries allowing them to make mistakes without any impact on actual patients.

3.     VR for Sales: Traditionally automakers have the showroom to show the cars to the customers and explain their features and sometimes a test drive is also possible. But customization of how the interior will look as per their choice was not possible which now can be done via VR.  Audi is experimenting this in London, where customer can configure their Audi with accessories as they want and drive virtually in real time.

4.     VR in Gaming: who does not know the excitement Pokemon Go had created and reached 50 million users in record time of 22 days.  Using AR/VR technology games have changed the life of seniors as well as teens. Game of Thrones has capitalized on VR and gone viral in various countries.

5.     VR in Designing: product designing is tedious task and changes to products based on the competition or customization is time consuming. This is where VR helps designers. They can now create the products easily, configure all the features and test them out. It is more popular in construction of buildings to see how the interior will look like.

6.     VR in Marketing: With Digital Marketing ads are becoming more intrusive. The best marketing campaigns use VR to create successful campaigns as users get completely immersed into the content, and create memorable experiences. Coca Cola created a virtual reality sleigh ride. New York times releases multiple immersive documentaries in their app. Finnair is showing their Airbus 350 via VR to attract more customers.

7.     VR in Sports coaching: The potential for VR in sports in endless. You get all the benefits of real-world interaction, but in a controlled environment. Showing is so much more effective than explaining, and experiencing something first-hand is that much more powerful again. Football, Cricket.


Virtual reality technology holds enormous potential to change the future for a number of fields, from medicine, business, and architecture to manufacturing. We are on the roller coaster ride !!

Saturday, 13 May 2017

Internet of (Medical) things in Healthcare

Over the past few decades, we’ve gotten used to the Internet and cannot imagine our lives without it. Millennials and new age kids don’t even know what is life without being online.

With the disruption of Digital Transformation, Internet of Things have added lots of opportunities to business and consumers like us, equally.

IOT means connecting things, extracting data, storing, processing and analyzing in big data platforms and making decisions based on analytics. It helps in predicting certain outcomes thereby helping with taking preventive actions

The popularity of wearables, such as fitness trackers, blood glucose monitors and other connected medical devices, has taken healthcare by storm. Connected devices have become a prevalent phenomenon in the consumer space and have made their way into healthcare

Healthcare is fast adopting IoT & changing rapidly, as it reduces costs, boosts productivity, and improves quality. IoT can also boost patient engagement and satisfaction by allowing patients to spend more time interacting with their doctors.

There are a number of opportunities for the internet of things to make a difference in patients' lives. IoT-enabled devices capture and monitor relevant patient data and allow providers to gain insights without having to bring patients in for visits. Adding sensors to medicines or delivery mechanisms allows doctors to keep accurate track of whether patients are sticking to their treatment plan and avoid patient's readmission.

Patients are using these connected medical products to capture ECG readings, record medication levels, sense fall detection and act as telehealth units.

Diabetes self-management includes all sorts of gadgets and devices, which control glucose levels and remind patients to take their insulin dose. The newest wearables are even capable of delivering insulin on their own, according to health condition indicators. 

Remote patient monitoring is one of the most significant cost-reduction features of IoT in healthcare. Hospitals don’t have to worry about bed availability, and doctors or nurses can keep an eye on their patients remotely. At the same time, patients usually feel more relaxed at home and recover faster.

Smart beds are a convenient solution for patients who have trouble adjusting bed positions on their own. This kind of IoT tool can sense when the patient is trying to move on their own and it reacts by correcting the bed angle or adjusting pressure to make the person more comfortable. Additionally, this frees up nurses, who don’t have to be available all the time and can dedicate extra time to other duties. Many hospitals have already introduced smart beds in their rooms.

At Boston Medical Center, IoT is everyday life:
·       Newborn babies are given wristbands, allowing a wireless network to locate them at any time.
·       They have installed wireless sensors in refrigerators, freezers and laboratories to ensure that blood samples, medications and other materials are kept at the proper temperatures.
·       Hospital has more than 600 infusion pumps which are IoT enabled. BMC staff members can now dispense and change medications automatically through the wireless network, rather than having to physically touch each pump to load it up or make changes.

At Florida Hospital, when patients go in for surgery, they're tagged with real-time location system (RTLS) badges that track their progress through from the pre-op room to the surgical suite to the recovery unit so relatives can track the patients from outside.

Philips GoSafe can be worn as a pendant and it helps to detect and alert falls in elderly people

There are few challenges as well in implementing IoT:
·       Data security & lack of standard security policy
·       Hospital’s internal system integration with IoT data
·       Further changes and improvements in IoT hardware

The Internet of these Medical Things is a game-changer as future will be connected, integrated & secure healthcare industry 

Sunday, 7 May 2017

Terminator or Iron Man – What will AI bring in future?

In the age of Digital Transformation, Artificial Intelligence has come a long way from Siri to driverless cars.

If you have used a GPS on Google Maps to navigate in your car, purchased a book recommended to you by  Amazon or watched a movie suggested to you by Netflix, then you have interacted with artificial intelligence.

Artificial Intelligence is the capability of a machine to imitate intelligent human behavior which relies on the processing and comparison of vast amounts of data in volumes with help of big data analytics, no human being could ever absorb.

Stephen Hawking, Elon Musk, Bill Gates have recently expressed concern in the media about the risks posed by AI.

According to them, AI will soon replace all kinds of manual tasks and make humans redundant. This could be true in some sense but still this is a far cry from the current maturity levels of AI, which is still at the stage of figuring out real-world use cases.

Today machines can carry out complex actions but without a mind or thinking for themselves. Smartphones are smart because they are responding to your specific inputs.

The world’s top tech companies are in a race to build the best AI and capture that massive market, which means the technology will get better fast, and come at us at faster speed. IBM is investing billions in its Watson, Apple improving Siri, Amazon is banking on Alexa;  Google, Facebook and Microsoft are devoting their research labs to AI and robotics.

Together, they will swirl into that roaring twister, blowing down the industries and businesses in its path.

Within maybe few years, AI will be better than humans at diagnosing medical images and converting speech to emotions. But it can also be stealing millions of records from a government agency to identify targets vulnerable to extortion.

Soon you’ll be able to contact an AI doctor on your smartphone, talk to it about your symptoms, use your camera to show it anything it wants to see and get a diagnosis that tells you to either take a couple of Tylenols or see a specialist.

In all the fairy tales we have seen so far, good almost always wins over evil.
This is what we have seen in the movies like I, Robot or Avengers: Age of Ultron.  But Will Smith or team of avengers does not know that till end of the story. That’s where we are now: face to face with the demon for the first time, doing everything we can to get through the scary plot alive.

Today many companies are using AI for improving their business:
·         Geico is using Watson based cognitive computing to learn the underwriting guidelines, read the risk submissions, and effectively help underwrite
·         Google Translate applies AI in not only translating words, but in understanding the meaning of sentences to provide a true translation.
·         IBM Watson is the most prominent example of AI based question answering via petabytes of data retrieval that helps in various areas like finance, healthcare & insurance.

As Humans we are programmed from childhood either by nurture or nature to do things the way we do. All the nine emotions we have learned since then are the inseparable part of our lives.

Currently we are in the control of the planet because we are smartest species compared to all the animals.

But when, and if machines learns to love or hate, work in peace or retaliate in anger, then it’s not too far that, with the ability to consume & digest the vast amount of data, they will become more smarter & start taking control of the planet.

Only then we will be able to know that AI is helping us like Iron Man's Jarvis or planning to eradicate us like Terminator!!

Saturday, 29 April 2017

5 ways to improve the model accuracy of Machine Learning!!

Today we are into digital age, every business is using big data and machine learning to effectively target users with messaging in a language they really understand and push offers, deals and ads that appeal to them across a range of channels.

With exponential growth in data from people and & internet of things, a key to survival is to use machine learning & make that data more meaningful, more relevant to enrich customer experience.

Machine Learning can also wreak havoc on a business if improperly implemented. Before embracing this technology, enterprises should be aware of the ways machine learning can fall flat. Data scientists have to take extreme care while developing these machine learning models so that it generate right insights to be consumed by business.

Here are 5 ways to improve the accuracy & predictive ability of machine learning model and ensure it produces better results.

·       Ensure that you have variety of data that covers almost all the scenarios and not biased to any situation. There was a news in early pokemon go days that it was showing only white neighborhoods. It’s because the creators of the algorithms failed to provide a diverse training set, and didn't spend time in these neighborhoods. Instead of working on a limited data, ask for more data. That will improve the accuracy of the model.

·       Several times the data received has missing values. Data scientists have to treat outliers and missing values properly to increase the accuracy. There are multiple methods to do that – impute mean, median or mode values in case of continuous variables and for categorical variables use a class. For outliers either delete them or perform some transformations.

·       Finding the right variables or features which will have maximum impact on the outcome is one of the key aspect. This will come from better domain knowledge, visualizations. It’s imperative to consider as many relevant variables and potential outcomes as possible prior to deploying a machine learning algorithm.

·       Ensemble models is combining multiple models to improve the accuracy using bagging, boosting. This ensembling can improve the predictive performance more than any single model. Random forests are used many times for ensembling.

·       Re-validate the model at proper time frequency. It is necessary to score the model with new data every day, every week or month based on changes in the data. If required rebuild the models periodically with different techniques to challenge the model present in the production.

There are some more ways but the ones mentioned above are foundational steps to ensure model accuracy.

Machine learning gives the super power in the hands of organization but as mentioned in the Spider Man movie – “With great power comes the great responsibility” so use it properly.


LinkWithin

Related Posts Plugin for WordPress, Blogger...