Before I move forward to explain the challenges of the blockchain let me just give you a quick idea about what Blockchain is and what the fuss is about it? I wont go in detail.
WHAT IS IT?
- A blockchain is a distributed database, meaning that the storage devices for the database are not all connected to a common processor. It is decentralized. It maintains a growing list of ordered records, called blocks. Each block has a timestamp and a link to a previous block. It uses a P2P protocol meaning the two person involved in the transaction are directly dealing without any 3rd party interference(ofcourse at the backend lot of computations are there but it doesn’t bother us). A chain of block becomes blockchain.
- So the question is since it is a database so what can it store? Well it can be used to store anything that we think is of value. One implementation is BITCOINS. In China, IBM has partnered with Walmart to put pork on blockchains in order to keep a check on its movement and quality.
- A database that can store anything? Whats big deal about it? Well What if I say that hacking it, wont be easy. Now that you are reading this with even more concentration now, let me tell you that when a new block is added to the existing blockchain, before it is added, the system make sure that it conforms to blockchain by passing it through a series of mathematical checks. So that consistency is maintained and the problem of double spending is also solved. Since it is a decentralized method. So a hacker cant just intrude one site and play around with it, because that would make the entire blockchain invalid and that tampering with the record will be immediately visible.
- Cryptography ensures that users can only edit the parts of the blockchain that they “own” by possessing the private keys necessary to write to the file. It also ensures that everyone’s copy of the distributed blockchain is kept in synch.
Imagine a digital medical record: each entry is a block. It has a timestamp, the date and time when the record was created. And by design, that entry cannot be changed retroactively, because we want the record of diagnosis, treatment, etc. to be clear and unmodified. Only the doctor, who has one private key, and the patient, who has the other, can access the information, and then information is only shared when one of those users shares his or her private key with a third party — say, a hospital or specialist. This describes a blockchain for that medical database.
APPLICATIONS IN REAL WORLD
- Healthcare – The blockchain can be used to create a type of universal record with a timestamp, a library that enables data retrieval across diverse databases. This will become exceedingly valuable as precision medicine and the explosion of sensors, wearables and mHealth apps proceeds. The current health systems and the legacy health IT players quite simply are not well designed to manage the volume and types of data that are being generated today.
- Finance – The most mature plans for using blockchains aim to cut costs for financial institutions in tasks such as settling transactions involving bonds or other financial instruments. All the back office stuff can be simpler and more reliable, and they can save a tremendous amount of money.
- Security – With the help of concept of distributed contracts, transactions can be made more secure for users by removing the concept of middlemen and making it P2P. A distributed contract is a method of using Bitcoin to form agreements with people via the block chain. Contracts don’t make anything possible that was previously impossible, but rather, they allow you to solve common problems in a way that minimizes trust. Minimal trust often makes things more convenient by allowing human judgements to be taken out of the loop, thus allowing complete automation.
CHALLENGES FOR BLOCKCHAIN
Bitcoin is a digital currency implementation of Blockchains. So I will be using the words bitcoins and blockchains interchangeably as per the usage.
- User anonymity
- Although every blockchain consultant out their says bitcoin is anonymous, they either don’t know what they are talking about or are misleading us. Bitcoin has a public ledger that indicates how much money everyone has. Anyone can look at this ledger and see what the balance of a specific address is. These addresses are pseudononymous — but once I transact with someone, I can reasonably guess which address is theirs — and then reasonably guess how much money they have! This is bad! If the size of blockchain is less, then it will be easy to crack that person and not a lot of computation will be required but if the size of blockchains is very large, then a lot of computation will be required. So logically it is possible to crack the anonymity of the person.
- We need to encrypt the amounts in a transaction to make Bitcoin much more private. In an ideal world, a third party should be able to see a transaction on the network and look at a mathematical proof that the encrypted amounts are valid on the network — that is the proof tells us the user didn’t create money out of thin air —without seeing the original amounts themselves.
- Customer protection
- A transaction on blockchain cannot be reversed. The only way to reverse the transaction is the receiver party to actually do the oppsosite. Think of it like a cash dealing with a person. Once you have handed over the cash to person, then its theirs. But while doing transaction with cash, we have a moderator like a bank or a person. But there is no such concept in blockchains(Bitcoin).
- So what do you do if the transaction becomes sour? You cant do anything in blockchain
- We need a moderator like a bank in a cash transaction or a third person which will be the part of that transaction block. A multisignature.
- Blockchain size
- We know that the size of the block chain is only going to increase and it will increase in exponential manner since each new block will record the history of blockchain as well. So are we going to run out of memory or feasibility in terms of hardware cost.
- One more thing to note that if too many small value transactions start taking place then the size of blockchain will increase three fold and we might see unprecedented increase in the cost of the whole blockchain setup against the monetory value that the entire blockchain can provide to the company.
- We can only hope that with advancement in technology, the hardware cost for storing is going to decrease and the size of the chip will also decrease. Both of them must be decreased in a faster rate as compared to the increasing rate of blockchain size in order for the overall thing to be feasible.(Several other factors I have overlooked here.)
- We can set a minimum transaction value but that will be against the idea of blockchains. So other solution could be giving precedence to higher value transaction and lower value transaction could be grouped together and added. If every 10 minutes a block is added on the blockchain then for the lower value transaction, we could increase the time to lets say 20 minutes. But this is not a good fix. Is it?
- Transaction time
- Lets say we have a very large blockchain size, now if a new transaction is going to happen and join the blockchain, it has to satisfy the already available blockchain, so verifying whether the transaction is valid or not against the billions of blocks already there, might be slow depending on the backend computing algorithm and the hardware capabilities.
- Again we can say that with the advancement in technology, the hardware cost will be cheaper and higher end processor will be available for cheaper rates.
- Illegal data
- If a blockchain can store any kind of data, then anybody can post anything in it and that illegal data will be propagated. Not sure who will be responsible for regulating it. Entire blockchain will become illegal. And since every transaction is irreversible, then whole transaction has to become invalid.
- Some internal method must be there to keep a check on that or if the illegal data is added to the blockchain then the concerned person must be punished, but wait a second! How do we do that? We know the whole concept is all about anonymity.
I still remember Tata saying what inspired him to think about a car suitable for India. He said when he was passing on a road, he saw a family of 3 or 4 riding a bike and the same inspired him to …
Source: People’s car- what went wrong?
I still remember Tata saying what inspired him to think about a car suitable for India. He said when he was passing on a road, he saw a family of 3 or 4 riding a bike and the same inspired him to conceptualize a car which will give comfort to families risking their lives on bikes to switch to the safety of a 4 wheeler. When Tata launched Nano, it was not just a business opportunity, but also a tool to improve quality of lives of millions of Indian who were facing the dangers of fast paced roads and everyday were being exposed to accidents due to non-affordable four wheelers. When media wrote about Nano being cheap, Tata allowed the frenzy as it allowed free promotion. When media started comparing Nano to other cars to show how economical, Tata allowed the frenzy. So the question is what went wrong?
- Buying a car in India is associated with social status and prestige; if a person owns a car, he is assumed to be successful and settled. Indian car buyers are not utilitarian but aspirational. It differs hugely from the Western market, where cars are more of a necessity rather than luxury. If a person buys a car in US, no one gives a damn unless it’s a Ferrari or Lamborghini. Indian market is different, and a different marketing strategy was required for selling Nano, which is arguably world’s cheapest car. But the word ‘cheap’ in its marketing campaigns spoiled everything. It had to be subtle yet hidden from the promotional messages.
- From the start they should have stressed that it is not competing with cars but giving alternate to two wheeler. They should have allowed or directed media to compare a bike to Nano. For a few rupees more a lower middle class man can take his family out in the comfort of a car. Instead they got carried away and deviated from initial inspiration. The media frenzy was such that the whole nation saw the few Nanos on fire which suggested that in order to minimize cost, Tata compromised on safety which is against the initial inspiration. Tata wanted to give a safe ride to bike riding families but it turned out that it is a “cheap car” without safety.
- There were various psychographic factors involved in the failure of Tata Nano as well. The Models of Consumer Behaviour clearly indicate the importance of psychographic Factors affecting Consumer Buying behaviour. Especially a product like car is a matter of Social exhibit and prestige. The needs behind buying a car follow a different category. As per Product Levels recommended by Philip Kotler (2006), for creating Customer-Value Hierarchy, the marketer needs to address five product levels out of which each level adds more customer value.
- The fundamental level is the core benefit: the service or benefit the customer is really buying.
- At the second level, the marketer must turn the core benefit into a basic product.
- At the third level, the marketer prepares an expected product, a set of attributes and conditions buyers normally expect when they purchase this product.
- At the fourth level, the marketer prepares an augmented product that exceeds customer expectations.
- At the fifth level stands the potential product, which encompasses all the possible augmentations.
In case of Tata Nano, Tata group emphasized more on the core benefit of the product which is to provide a safe and secure mode of transportation at low affordable prices but it could not reach up to the expectations of customers and failed to be an augmented or potential products.
- The launch price came in two variants ranging between 1.2 lacs to 1.5lacs. It was 20 – 50% higher then the proposed rates which was a major setback to customers. Within a few months of initial sales, technical problems were found in the product and there were a few reports of Nano catching fire, which further weakened the trust for the brand ‘Nano’ as a whole. Tata also faced political problems and had to shift the plant location which led to production delays. And now due to inflation, Nano’s prices had further increased due to increase in the prices of raw material such as steel, rubber and others.
The failure of Tata Nano present with a great lesson for all the marketers the car was positioned as a symbol of social liberty and equality. It was positioned as dream car of common man of India. It was targeting the laymen who want to have a car and it got successful to some extent but only till a functional level. The Nano made sense in terms of a social mission, on a purely functional level. Good quality engineering focused on the task of making something reliable and safe as cheap as possible. Sell it to people with not much money. But it has been criticized all around as the one to the greatest positioning blunder as even the most cost effective producers do not label their products as cheap. Here the cheap has a great social connotation and the social tag because nobody aspires to buy the cheapest thing on the market, and driving around in a car is as big a statement as you get to make. Human psychology is that the motivation behind buying isn’t to have a car, or a shampoo, or whatever the product is. If a product is positioned as poor‘s product then poor people will definitely avoid it because they don‘t want to be viewed as poor yet. The marketer just need to place their product right in the minds of customer and the brands like Giorgio Armani, Raymond‘s, Toyota and even other brands of Tata are examples of that. So positioning remains the main mantra behind the success of any product.
Big data is a source of new economic value and innovation. Big data’s ascendancy represents shifts in the way we analyze information that transform how we understand and organize society. Now with so much data already generated, big decisions in many firms are taken after analyzing the past trend.
We have several areas where big data has improved the overall performance. Some of them are-
- Understanding and Targeting Customers Companies are keen to expand their traditional data sets with social media data, browser logs as well as text analytics and sensor data to get a more complete picture.
When the sales of XUV500, one of Mahindra and Mahindra Ltd’s best-selling sport utility vehicles, started dropping after a strong run for a-year-and-a-half, the company turned to social media and traditional feedback channels to work on a turnaround strategy. The sales and marketing team began monitoring Facebook posts, YouTube videos and tweets that involved the XUV500, and used the feedback and analysis to eventually launch a variant of the vehicle that was stripped of certain features to make it more affordable. The launch of the cheaper variant helped the company boost sales.
US retailer Target was able to identify that one of their customers was expecting a baby by just studying her shopping pattern. Target identified 25 products that when purchased together indicate a women is likely pregnant. The value of this information was that Target could send coupons to the pregnant woman at an expensive and habit-forming period of her life.
- Personal Quantification and Performance Optimization For many years economists and scientist believed that happiness and income were directly correlated: increase the income and a person on average will get happier. Looking at the data on a chart, however revealed that a more complex dynamic is at play. For income levels below a certain threshold every rise in income translates into a substantial rise in happiness, but above that level increase in income barely improved a person’s happiness. If we were to plot this on a graph, the line would appear as a curve rather than a straight line.
- Improving Healthcare and Public Health Big data techniques are already being used to monitor babies in a specialist premature and sick baby unit. By recording and analyzing every heart beat and breathing pattern of every baby, the unit was able to develop algorithms that can now predict infections 24 hours before any physical symptoms appear. That way, the team can intervene early and save fragile babies in an environment where every hour counts. Personalized medicine is another hot topic in the healthcare field. It involves tailoring medicines to a person’s unique genetic makeup – and is developed by integrating a person’s genetic blueprint and data on their lifestyle and environment, then comparing it alongside thousands of others to predict
4. Improving Sports Performance Adidas has a system called miCoach that 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.That kind of real-time data could help trainers and physicians plan for better training and conditioning.
5. Optimizing Machine and Device Performance Google’s fleet of robotic Toyota Priuses has now logged more than 190,000 miles (about 300,000 kilometers), driving in city traffic, busy highways, and mountainous roads with only occasional human intervention. The project is still far from becoming commercially viable, but Google has set up a demonstration system on its campus, using driverless golf carts, which points to how the technology could change transportation even in the near future.
6. Improving and Optimizing Cities and Countries Big data is used to improve many aspects of our cities and countries. For example, it allows cities to optimize traffic flows based on real time traffic information as well as social media and weather data. A number of cities are currently piloting big data analytics with the aim of turning themselves into Smart Cities, where the transport infrastructure and utility processes are all joined up. Where a bus would wait for a delayed train and where traffic signals predict traffic volumes and operate to minimize jams.
7. Improving Security and Law Enforcement. Big data is applied heavily in improving security and enabling law enforcement. The National Security Agency (NSA) in the U.S. uses big data analytics to foil terrorist plots (and maybe spy on us). Others use big data techniques to detect and prevent cyber attacks. Police forces use big data tools to catch criminals and even predict criminal activity(eg. movie ‘Minority report’ ) and credit card companies use big data use it to detect fraudulent transactions.