A question about IT change management: does the DNA of the company fit your IT vendor?


Company_Vendor_DNAs

When delivering my final dissertation of the MBA program (here the link of a short presentation), along the research I’ve encountered the topic of IT Change Management.

As a matter of fact, whenever a company decides to implement IT innovations most likely new collaborations or partnerships with IT Vendors, consultants or third parties are needed. Usually, within a selection process, IT suppliers are evaluated accordingly to theirs know how and proven expertise. However, what about other aspects such as the agility to change, the ability to innovate and corporates’ cultures? Is there a potential fit or a misfit between the company and the selected IT vendor?

The company’s DNA

In order to avoid failures, it’s fundamental to set a pace for IT innovations that is affordable to the company according to its DNA. According to R. Ray Wang (@rwang0) there are two kind of attitudes when defining a DNA of a company: proactive vs. reactive and incremental vs transformational attitudes.

Cautious Adopters: proactive & incremental (about 30%). Such companies are looking for new technologies without waiting what other competitors do. However, they are willing to implement only the technologies that might play a key role in the future as well as they are not keen to consider the opportunity to change their business model even if the new technology enable a breakthrough.

Market Leaders proactive & transformational (about 5%). A market leader has the ability to sustain high paces of IT innovations as well as an organizational flexibility to change also its business model.

Laggards: reactive & incremental (30%). Such a company avoid any kind of risk of a self-disruptive innovation and integrates new technology only when other competitor succeed. In any case, without transforming its business model.

Fast Followers: reactive & transformational (15%). This of kind of DNA is able to mitigate the risk of adopting new technology by relying on the ability to change quickly the business model and the organization as a way to survive against disruptive innovation threats.

(More: “The Building Blocks of Successful Corporate IT“, HBR Blog)

IT Vendor’s DNA

What about the DNA of an IT Vendor? Gartner is well-known for providing a “magic” quadrant for everything and also for evaluating an IT vendor: completeness of vision and ability to change are the two main attitudes to consider.

Leaders: high completeness of vision & high ability to execute. As IT vendors, they are able not only to provide innovative services that works today but also to influence the market that theirs innovations are the best for the future. For these reason, such IT vendors might fit best a company with a leadership that wants to invest in new infrastructures\technology early and avoiding any risk due to technology (obsolescence, maintenance, etc.). However, also a cautious adopter (DNA) company that wants to develop a leader DNA should prefer IT leaders by relying on their ability to execute and play a key role as an influencer within a change management process.

Niche Players: low completeness of vision & low ability to execute. Is the case of IT vendors specialized in few functionalities and with low ability to execute due, for example, to a lack of resources (financial, operating) and power (network). However, such IT vendors might be useful for companies that need small technology changes without stringent delivery deadlines. For these reason IT niche players might be extremely useful for Laggard (DNA) companies.

Visionaries: high completeness of vision & low ability to execute. Is the kind of IT vendor that fit best a Cautious Adopter company’s DNA. Anyhow,  a Fast Follower (DNA) company that wants to innovate proactively rather than reactively, might get some useful insights from Visionaries third parties.

Challengers: low completeness of vision & high ability to execute. Is what Fast Follower companies usually need. However, a Cautious Adopter company that wants to improve its change management process should look for Challengers as IT vendors.

(More: “How Gartner Evaluates Vendors and Markets in Magic Quadrants and MarketScopes“, Gartner)

So, which IT Vendor to chose? Thinking about possible threats due to cultural and organizational divergences between the company and th IT vendor DNAs will ensure the implementation of the strategy as well as it will avoid market\operational risks and a waste of resources: why to invest on IT Vendor Leaders? Does the company really need it?

As a moral of this story, selecting the IT Vendors that fit best the company DNA is not so different as chosing relationships and friends in our every day life. Trusted and better relationships are guaranteed only by knowing ourselves as well as the others.

Feelink – Feel & Think approach for doing life!

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X and S band radars: a great metaphor for logistic professionals… and not only, also for every day life!


This time I want to tell a story of mine. Recently I was struggling with figures regarding a new kind of analysis in the field of procurement, supply chain and inventory management. Something that I’ve never done before.

Since I was too focus on the jungle of numbers and details what happen is that I’ve completely missed the path…I felt myself completely lost in the middle of the forest of figures!

So, my mentor helped me to find the path again in order to complete the analysis with an inspirational metaphor, well-known among logistic and operation professional: the X-band and S-band radars.

The S-band radar

S-band_ASR-9_Radar_AntennaIt means be able to patrol what’s going on in the medium-long range in order to anticipate risks proactively. This means, for a logistic professional, taking all the countermeasure in order to properly asses the forecast of the demand in the future as an example. Having a good term vision is essential when planning the procurement of the materials, especially with high lead times, as well as develop a strategic thinking and a wider perspective by monitoring competitors, suppliers and new technology innovations. Demand Driven Supply Chain (DDSC) is possible only thanks to a good S-band radar surveillance.

The X-band radar

kingston_sband_ant_closeup

It is aimed to work for short-range surveillance, usually below 2-3 thousands Kilometers. For a logistic professional this means beeing able to address the ongoing issues of every day work and thus promptly take the counteractions against the encounter menace: delay of the delivery or a call from the quality control about the noncompliance of the material received with the consequence to stop all the production within a couple of hour. Usually a X-radar is small and it doesn’t weigh too much. Very useful characteristic when dealing with tactical moves.

So, a good professional in logistic has to handle both of the S-band and the X-radar. This is the easiest part. The hardest one is  to manage them simultaneously and is what I’ve realized when I was struggling with the figures for the analysis because I’ve temporally switched off my S-band radar. Once I’ve switched it on again, all the numbers for the analysis become suddenly much more clear since it was as well clear the long term purpose and meaning behind the figures.

Anyhow, is this metaphor useful only for logistic professional? According to an interpretation of a famous quote from Hemingway, I would say no:

Today is only one day in all the days that will ever be. But what will happen in all the other days that ever come can depend on what you do today.

Using the X-band radar might also help ourselves in everyday life. Meanwhile, the S-band will clear the fog in front of our perceptions and aspirations in the future.

Feelink – Feel & Think approach for doing life!

Firm Infrastructure Vs Catalyst to Change Business Models (part 2): New IT Innovation Development (NITID)


Value chain

Acknowledged the role of IT and technology as a catalyst to change business model (see the previous post “Firm Infrastructure Vs Catalyst to Change Business Models:  the Double Side of IT“), how to implement new IT innovations in practice?

Each innovation implies a changing process and each changing process implies commitment and investments…so, which IT innovations to choose in order to avoid a waste of resources? Are the IT innovations under development in line with the customer needs (actual or potential)? Which are the key competences needed for developing a new IT innovation?

Whatever the industry of the company is about, since the focus is customers’ needs, why not thinking how to adapt the NPD (New Product Development) process to IT innovation? The NPD is a structured creativity process focused on introducing new kind of products\services that effectively produces innovations.

In particular, the NPD process combines lateral (generations of ideas) and vertical thinking (selections of ideas) together and it is divided into four stages: ideas brainstorming, ideas classifications, ideas evaluation and ideas selection.

NPD stage 1: ideas brainstorming (lateral thinking)

In this stage all the team members engaged simply write down new ideas without any kind of filter or criticism (lateral thinking). Taking as an example the case of TripAdvisor (see “Tripadvisor: a case study to think why bigdata variety matters“) where a validation process of the reviews is in place by recording on a database the receipts of the end-user at the restaurant: which might be the new innovations available by using the data of the receipts?

NPD stage 2: ideas classification (vertical thinking) – KJ Method

Now, since usually a brainstorming session generate chaos, how to figure out which IT innovations to implement?

Like navigating in the middle of a storm, just stay focus on the ongoing  issues, do not think to a final solution and keep clam. So a first step is to organized ideas in a structure way in order to figure out a big picture. An approach for classifying the brainstormed ideas is the KJ method, where all the initiatives are split into groups by using a criteria. For example, criteria for classifying IT innovations could be: which are the departments\functions involved by the IT innovation? Or\And, which are the stakeholders (customer, suppliers, third parties,…) involved?

Then, for each group of ideas, assign a tag that identifies it. For example, suppliers IT innovation, marketing & sales IT innovations, and so on.

NPD stage 3: ideas evaluation (vertical thinking) – QFD Matrix

Once ideas are grouped and tagged, the next step is to identify the key performances that are needed in order to implement new IT initiatives. Typically, regarding IT stuff, they are about DataBase (storage, number of transactions,…), architectures, maintenance costs, usability, interoperability,…

By putting IT initiatives into rows and the key IT characteristics into columns, the finial result is a matrix called QFD (Quality Function Development). Briefly, the QFD matrix connects the IT initiative with the needed performances. For these reasons, the QFD matrix applied to IT innovations might be useful also for procurement: which are the key competences? Make or Buy? If buy, which IT vendor to choose?

NPD stage 4: ideas selection (vertical thinking) – Pugh Matrix

Just for a recap. We have organized the ideas, we have identified the key characteristics for each IT initiative… and so? Which IT initiative to implement? The answer is provided by the so called Pugh Matrix where, for the development of a new product or service, evaluates ideas and solutions according to a gap analysis. In particular, how much the new idea will be valuable for the customer? Will the new idea provide a competitive advantage against competitors?

A similar evaluation should be adopted also for IT innovation. Why? Just think about the risks correlated when IT becomes so complex to be maintained and thus a nightmare for customers, employees and suppliers as well.

Too much enthusiasm on IT initiatives has a side effect to much IT complexity. How to innovate without adding superfluous IT complexity? What about using NITID (New IT Initiative Development), a revised NPD method widely use for product innovations?

Feelink – Feel & Think approach for doing life!

The D.A.I. model to better understand different mindests and cultural values: why social responsibility means higher prices?


Few weeks ago, from a new Twitter follower, I’ve received a direct message with the following question: “Do you spend more money with a brand that you think is socially responsible?”. I felt immediately that it could be either a marketing research or a way to create awareness on something, nothing bad on it whatever it is.

Anyhow, the aim of a question is to gather an information. So which is the information that the question above wants to address? Suddenly came into my mind a principle from information theory: information is an interpretation of data based on assumptions (see figure). Usually assumption are due to culture, mindset and context in general. Think, as an example, how the same gesture of moving the head up and down (data) means yes for Europeans and Westerns but for Indians means exactly the opposite.

information_assumption

So, why not applying such a principle from information theory also for every day life in order to better understand ourselves as well as others? Let’s analyze deeper the question “Do you spend more money with a brand that you think is socially responsible?”

First of all, the question is a close one since the answer must be yes or not. When I’ve realized that I felt myself uncomfortable… why? I thought and I realized that is due to the value of “social responsibility” that in the question is forced to be against “price” (money).

Acknowledge that, I inferred unconsciously that if the answer of the question would have been YES it means that social responsibility is priceless thus more important that money. Vice versa, if the answer would have been NO.

…however, why inferring such considerations? which is the assumption behind? That was my doubt and my hypothesis was that the assumption behind the tricky question “Do you spend more money with a brand that you think is socially responsible?” is: beeing social responsible costs!

…wow, eureka! So, why not creating such conditions so that pursuing social responsibility implies intrinsically cheaper products?

That was my question that I’ve delivered to the owner of the research…and, as an incredible surprise, I’ve receive the following answer: “The impression is socially responsible = higher product cost to the consumer.”

Bingo! The assumption that I’ve inferred is right. There is a kind of cultural impression, suggestion and mindset that unconsciously let us to think (me included) that if you want social responsible products there are no other ways: you have to pay more! Why?

Paradoxically, since people behave according to incentives, if socially responsibility implies intrinsically cheaper prices instead, a virtuous circle will be established!

How to create a context where the assumption “socially responsible = higher product” is replaced with “socially responsible = cheaper product”?

…I don’t know, any idea?

Meanwhile, why not applying the DAI (Data, Assumption, Information) model whenever we inferred quick answers?

Behind each information there is an unknown world of undisclosed assumptions.

Feelink – Feel & Think approach for doing life!

Semantic search algorithm, behaviorism and fairy-tale Snowwhite with the seven dwarfs. Would SEO behave like Grumpy?


How does semantic search work? Which are the implications regarding SEO tactics and users/customers’ behaviors?

Google search is not unlike the “Mirror, mirror on the wall, who’s the fairest of them all?” where the question asked, reveals (in the fairy tale) the Evil Queen’s narcissistic obsession

, what a great metaphor to explain how semantic search works! (see Google Search and the Racial Bias).

I will take the assist from David Amerland to help me to better understand how the SEO world (something still unknown from me) as well as remembering childhood times with the fair tale “Snow White and the seven dwarfs“.

So, let’s have a look at the characters of the famous fairy-tale:

The mirror is the result of the search engine. According to what I’ve understood about semantic search, the mirror reflects back a result that is contextualize accordingly to the user and his/her relationships among the social networks as well as thorough the analysis of past behaviours.

Snow White is the most beautiful creature in the WEB forest. She publishes smart content as well as she establishes such trusted relationships in the social medias so that the mirror (the semantic search engine) reflects back a beautiful princess… accordingly to the algorithm I would say.

The evil queen is the bad guy, attempting to be viewed as the most beautiful in the WEB forest while it is not. The evil queen struggles and suffers a lot for that, since the mirror suggest always Snow White as the best result… the life in the digital jungle is not so easy for the evil queen!

The poisoned apple represents a trick, a negative SEO attack where the objective either is to game the search engine (the mirror) or to compromise the reputation of Snow White. Fake reviews, negative or positive SEO tactics, are just an example of how an apple could be poisoned in order to kill digitally a competitor and game the search engine algorithm (see the case of Tripdavisor).

The seven dwarfs are data scientists and SEO experts that are mining the WEB forest in order to get some valuable and reliable information from the WEB. Usually they are well-intentioned and thus willing to protect the beauty of Snow White from negative SEO (the poisoned apple and the evil princess).

The charming Prince represents all the users, companies and individuals, that go deeper and deeper into the WEB forest in order to discover the truth. Mirror’s result apart: Who is really the fairest in the WEB forest?Encountering few smart dwarf might be useful for the charming Prince, both in the forest to discover the beauty of Snow White and in the WEB to find out great contents and reputations accordingly to personal impressions rather than only relying on algorithms.

…so, which is the moral of the fairy-tail “Snow White and the seven dwarfs” applied to the modern semantic search and SEO?

An interesting point has been pointed out by D. Amerland in his article “How semantic search is changing end-user behaviour“. In particular:

The fact remains that the web is changing, search has changed and the way we operate as individuals, as well as marketers, has changed with it.

Since the semantic search is so powerful to influence the behaviour of the end-user (individuals, companies,…), the point is: what kind of algorithm there is behind the mirror on the wall? Which are the criteria behind the result that identify the fairest princess in the WEB?

More interesting doubt: what happen if the criteria behind the search algorithm (the mirror) change so that the fairest in the WEB would be Grumpy, one of the seven dwarfs? Would all the end-user and SEO really want to become and behave like Grumpy?

seo_mirror_on_the_wall

Barriers to change… Should I stay or should I go? A ripped up speech


Ferdinandeo (Triest), Saturday 21st September 2013 around 12:00 a.m.: what to say as a final speech after attending an MBA program in behalf of all the class?

Here below an idea, a story about barriers to change… delivered here, in a comfortable “context”, with 10 day of delay: should I stay or should I go?

Should I stay or should I go? A story about barriers to change

Should I stay or Should I go? That was the question that each MBA participant has faced when applying for the master program in business administration here at MIB School of Management.

Should I get an MBA in my country or abroad?

The MBA class of the 23rd edition was almost equally distributed: 60% foreigners and 40% Italians. Who made the right decision?

Nobody knows… now!

Anyhow, what all the participants of the 23rd edition have in common, both foreigners and Italians, is that they have started a changing process in a way:

someone changed country, some other quit a job and somebody did both.

Was that easy? Of course it was not!

Why? Because each change requires a transformation process, and each transformation process requires resources:

physically, mentally and emotionally.

So… which are the barriers to change? I would say mainly three:

unawareness, laziness and conservation of the status quo.

The first one, unawareness, means that since I don’t know there is a problem, why to invest resources for a change? How to start a changing process in such a situation? Simply by creating awareness: “Houston, we have a problem!”

The second one, laziness, I know there is a problem but it requires too much resources: physically, mentally and emotionally. In this case the therapy is defining an objective that is attractive enough in order to justify the effort.

The third one, conservation of the status quo, is the toughest: I do know there is a problem and I do not want to change since I feel myself comfortable in the current situation. I am not sure… in this case uncertainties about the current situation and status quo will establish a changing process.

Why uncertainties? According to a passage taken from a speech held here in this hall few months ago: “Since the economy is not growing in Europe and in the Western counties, the only alternative for getting good jobs is to go abroad where the economy is booming”

So… should I stay or should I go? According to this story, I would say: it depends!

It depends on how much uncertain and uncomfortable you are with your current situation and status quo… unless new innovative opportunities and unconventional alternatives will be created from scratch.

All the best for the MBA23 and MBA24 classes!

Thank you!

The story was slightly different and this speech has not been delivered because the “context”, the final ceremony for the MBA23 class, was not comfortable for the speaker.

How to break such a uncomfortable situation? …well, you already know the moral of the story: by creating uncertainties through innovative and unconventional alternatives!

Feelink – Feel & Think approach for doing life!

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Saving IT Expenditures and sourcing Business Intelligence and Analytics tools: which are the KPIs for BigData?


The IT expenditures are forecasted to growth due to the business speculation behind the buzz word BigData. Therefore, in order to avoid biased insights, How to measure the quality of the information extracted? How is it possible to get more value from BigData and saving useless expenditures?  Are the insights provided by business intelligence, analytics, and prediction tools really reliable?

A meaningful example about the speculation behind BigData, is the case of sentimenters that analyze tweets and posts: are they a BigData bubble? (see also My Issue with BigData Sentiment Bubble: Sorry, Which Is the Variance of the Noise?)

Bigdata_process

As a matter of fact, insights and predictions are final results of a transformation process (see figure) where the data in input is elaborated by an algorithm. A fantastic and exhaustive explanation about the process behind any business intelligence tool is the pyramid of data science where five stages are identified: 1) data gathering/selection, 2) data cleaning/integration/storage, 3) feature extraction, 4) knowledge extraction and 5) visualization (see The Pyramid of Data Science).

Anyhow, as for the production of products such as cars, clothes and a good meal in a restaurant, high quality results are ensured by the quality of the raw materials and the quality of the transformation process as well.

Thus, if the raw material for an analytic is the Data, how to assess the quality of the supply, the data? ACID compliance and pessimistic looking already define best practices in order to guarantee the quality of data in terms of data management and thus reduce maintenance cost and improve efficiency.

However, from a procurement point of view, how evaluate the quality of the supply within a procurement process for sourcing data? Similarly, how to evaluate the quality of the process that transform the supply (data) into insights and valuable information?

Like for the production of products a well-defined procurement process is ensured through well written specifications documents where requirements and key parameters/characteristics are clearly stated. Superfluous to say that a well-defined procurement process will ensure the quality of the supply, and the quality of the supply will ensure the quality of the final product/service. In this case, it will ensure the quality of the insights.

Undoubtedly, the huge amount of data available nowadays and new technologic improvements are generating more business opportunities than in the past both to improve process efficiency and to define new business models (see Firm Infrastructure Vs Catalyst to Change Business Models: the Double Side of IT (Change Management).

Thus, clearly define which KPIs to look for and negotiating the aspects that really matters will ensure best IT analytics services in terms of opportunities to exploit, thanks to the insights provided, as well as saving costs.

As an example, if are not yet available parameters for evaluating the quality of data and of the analytics as well, I would go to a restaurant where I know the quality of the suppliers instead of looking to reviews and advertisements based on questionable data suppliers: fake TripAdvisor’s users (see Tripadvisor: a case study to think why bigdata variety matters).

Beeing aware that ignoring bigdata opportunities means also ignoring a better restaurants, with delicious meal and low prices, Companies that define best a procurement process for data sourcing will enjoy the best meal in a bigdata restaurant.

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My Issue with BigData Sentiment Bubble: Sorry, Which Is the Variance of the Noise? (NON Verbal Communication)


Why sentiment analysis is so hard? How to interpret the word “Crush” in a tweet? Crush as in “being in love” or Crush as in “I will crush you”? According to Albert Mehrabian communication model and statistics, I would say that on average a tweet for a sentimenter has an accuracy of 7%. No such a big deal, isn’t it?

Let’s think about it by considering, as an example, the case of the sentiment analysis described in My issues with Big Data: Sentiment: crush as in “being in love” (positive) or crush as in “I will crush you” (negative)?

What is a sentimenter? As a process, is a tool that from an input (tweets) produce an outupt like “the sentiment is positive” or “the sentiment is negative“. Many sentimenters are even supposed to estimate how much the mood is positive or negative: cool!

Paraverbal and non-verbal communication

Anyhow, according to Albert Mehrabian the information transmitted in a communication process is 7% verbal, 38% paraverbal (tone of the voice) and the remaining 55% is non-verbal communication (facial expressions, gestures, posture,..).

In a Tweet, as well in a SMS or e-mail, neither paraverbal nor non-verbal communication are transmitted. Therefore, from a single tweet is possible to extract only the 7% of the information available: the text (verbal communication).

So, what about the paraverbal and non verbal communication? During a real life conversation, they play a key role since they count for 93% of all the message. Moreover, since paraverbal and non verbal messages are strictly connected with emotions, they are exactly what we need: sentiments!

Emotions are also transmitted and expressed though words such as “crush” in the example mentioned. However, within a communication process, not always the verbal and non-verbal are consistent. That’s the case when we talk with a friend, he\she saiys that everything is ok while we perceive, more or less consciously, something different from his\her tone or expressions. Thus we might ask: are you really sure that everything is ok? As a golden role, also for every day life, I would recommend to use non-verlbal signals as an opportunity to make questions rather than inferring mislead answers (see also: A good picture for Acceptance: feel the divergences & think how to deal with).

For these reason, the non-verbal messages are a kind of noise that interferes with verbal communication. In a tweet, it is a noise that interferes with the text. Such a noise can be as much disturbing as much the transmitter and the receiver are sensitive to the non-verbal communication. It might be so much disturbing to change completely the meaning of the message received.

Statistic and Information Theory

From a statistic point of view the noise might be significantly reduced by collecting more samples. In Twitter, a tweet is one sample and each tweet have 7% of available information (text) and 93% of noise (non verbal communication) that is the unknown information.

From a prediction\estimation point of view no noise means no errors.

Thus, thanks to BigData, if the sentimenter analyzes all the tweets theoretically it’s possible to reduce the noise to zero and thus having no prediction error about sentiments…...WRONG!!!

Even if the sentimenter is able to provide a result by analyzing all the BigData tweets (see Statistical Truisms in the Age of Big Data Features):

the final error in our predictive models is likely to be irreducible beyond a certain threshold: this is the intrinsic sample variance“.

The variance is an estimation of how much samples are different each others. In the case of a communication process, that means how much emotions are changeable through time. Just for fun, next time, try to talk to a friend by changing randomly your mood happy, sad, angry,..and see what happen with him\her (just in case, before fighting tell him\her that is part of an experiment that you’ve read in this post).

In Twitter, the variance of the samples is an estimation about how much differently emotions are impacting the use of certain words in a tweet, from person to person at a specific time. Or, similarly, by considering one person, how much emotions are impacting the use of words differently through time.

Like in a funnel (see picture), the sentimenter can eliminate the noise and thus reduce the size of the tweet bubbles (the higher the bubble the higher the noise) till a fixed limit that depends on the quality of the sample: its variance.

Sentimenter_Twitter_Funnel

So, I have a question for bigdata sentimenters: which is the sample variance of tweets due to non-verbal communication? Acknowledge the sample variance, the error of prediction of the best sentimenter ever is also given:

error of prediction (size of the bubble sentiment) = sample variance of tweets…

…with the assumption that both samples and algorithm used by the sentimenter are not slanted\biased. If this is not the case, the sentiment bigdata bubble might be even larger and the prediction less reliable. Anyhow, that is another story, another issue for BigData sentimenters (coming soon, here in this blog. Stay tuned!).

Feelink – Feel & Think approach for doing life!

Tripadvisor: a case study to think why bigdata variety matters


tripaadvisor

The recent scandals about fake reviews has put the reliability of TripAdvisor under discussion (see The Guardian).

Such a bad quality of service is not useful for consumers, entrpeneurs as well as in the long run for the reputation of TripAdvisor. So, where is the problem?

Clearly it’s a question of reliability of the sources of information and specifically for TripAdvisor is a question of assessing the reliability of the user that post a new review. Nice and easy…like discovering the hot water. However, thinking also at the practice of the so-called Negative SEO, that is not only an issue of web sites like TripAdvisor but also for all the companies that have to promote theirs brands in the social networks (who think doesn’t need it, raise up the hand).

In order to fix the issue, Tripadvisor developed the service Report Blackmail that tracks and eventually bans the users that are using Negative SEO tactics. For example, 100 user managed by a restaurateur that are reporting cases of colitis and runs in the reviews of the competitor near the corner. Such a solution try to catch fake users when they’ve already done the “attack” as well as, if not properly working, it might ban by mistake honest users. It sound reactive rather proactive, isn’t it?

So, are there other approaches that can fix the problem of malicious reviews proactively? An idea could be use new IT bigdata technologies and re-think the business model. How? (see also MIT Sloan Management Review: technology as a catalyst for change).

An approach could be associating the Tripadvisor user with a unique ID, for example a TripAdvisor idetity card, while to restaurateurs and hotel managers have an ID card reader (RFID, infrared,etc.). Thus, once the consumer eat the meal and goes to pay the restaurateur track the consumer ID that univocally identify the user, plus time and position. Finally, the user have just to fill the form for his\her review that now can be fully validated. Potentially, once the users sign in the TripAdvisor website, a list of pending reviews not already filled might be also provided in order to facilitate the process and thus creating the so-called “customer experience”. Moreover, by tracking precisely the date, it is also possible to provide evaluations that are more meaningful for the customer by giving less importance to aged reviews.

With the technology currently available actually even a smart phone could be a card reader since it might equipped with a RFID or a magnetic stripe reader and, by developing a specific app, the restaurateur could easily and quickly transmit a transaction with the TripAdvisor ID of the customer.

tipadvisor_new_business_model

Apart from the solution proposed, that is an example that stresses the importance, when defining a bigdata strategy, to identify first the information that is really meaningful (user, time, position) as well as having a Variety of sources in order to validate the reliability of the data. In the case of Tripadvisor is crucial to correlate the data coming from the restaurateurs with the reviews of the couple customer\user (together!!!).

Thinking about the definition of BigData by Gartner:

Bigdata is high-volume, -velocity and -variety information assets that demand
cost-effective, innovative forms of information processing for enhanced insight and decision making

So, Variety is one of the “Vs (Volume, Velocity and Variety) and the Volume of data is only what is up to the sea level of the iceberg called BigData.

Do you think that variety matter? I think yes, it matters!

If you think so as well and you have the opportunity to visit Italy I would you recommend (personal advice) to enjoy meals in restaurants where are shown logos such as the following and relying on the word of mouth, an evergreen.

Recensioni

They are not implementing Variety like TripAdvisor as well but reviews are made by professionals and they do not have social media and WEB2.0 visibility risks. Of course, I would recommend to find other sources (use variety!).

Have a nice journey and enjoy the meal!

Feelink – Feel & Think approach for doing life!

The 2nd Law: a MUSE for a Sustainable Economy


What does it mean sustainable? After the last financial crisis in 2007 as well as the issues of global warming, pollution and deforestation the word “sustainable” has become very popular.

That is the question that many people have. That’s why there are many best sellers about economic crisis. That’s why nowadays economists are so popular… that’s why I’ve just bought the last book by @TimHarford “The Undercover Economist Strikes Back”.

In their latest album, “The 2nd Law“, the rock band @muse spreads out to the all the fans the concept of entropy and the second principle of thermodynamics. Paraphrasing Rockonomics by Tim Harford (see Undercover Economist: the law of rockonomics), that’s an example of Rockphysic…cool, check it out!

MUSE – The 2nd Law: Unsustainable

All natural and technological processes proceed in such a way that the availability of the remaining energy decreases. In all energy exchanges, if no energy enters or leaves an isolated system, the entropy of that system increases. Energy continuously flows from being concentrated, to becoming dispersed, spread out, wasted and useless. New energy cannot be created and high grade energy is being destroyed. An economy based on endless growth is Unsustainable

The fundamental laws of thermodynamics will place fixed limits on technological innovation and human advancement. In an isolated system the entropy can only increase. A species set on endless growth is Unsustainable

So, according to the second law of thermodynamics each transformation requires energy (see also Does the price for inequalities exist because of the second law of thermodynamics?). If the system is isolated there is no way to recover such energy in a state that can be used. An example, think about a car as a system that transforms the chemical energy of the gasoline in mechanical energy and heat (…mainly heat actually). If the car is an isolated system, once the tank is empty the car can not work anymore. Fortunately the car is not isolated, since it’s sill possible to go to the patrol station and fill again the tank with additional energy: gasoline.

What about the planet earth: is it an isolated system? Is the world economy as is defined nowadays sustainable accordingly to the second law of thermodynamics? For @MattBellamy, @CaptMorganized, @CTWolstenholme and their friend Charles no way: it’s unsustainable.

Anyhow, since the planet is not isolated there is a chance to create a sustainable economy and thus to avoid extinction. How? Every second, every minute every day for billions of years the planet Earth has received energy from the Sun. It’s thanks to the solar energy that there is life in our planet and all the human activities are possible (even blogging!). Both, life and world economy need energy. In order to be sustainable, the sum of the energy needed for life and human activities must be lower that the solar energy received from the Sun (see Life on Earth). In this way the stock of energy available in the biosphere (number of species, forests, oil,…) will increase or, if the energy consumed equals the energy received, at least remains constant (see Figure below).

charles

On the contrary, if the energy consumed by life and human activities is higher than the energy coming from the Sun, the energy balance is negative and the stock of energy in the biosphere will decrease (extinctions of species, deforestation, oil, gas,…). That condition can not be sustained for a long period since the stock of energy available in the planet is finite. It’s like a bank account: expenditures higher than the incomes can be sustained till the bank account is positive!

That’s way Entropy likes the song “Time is on my side” by Rolling Stone. Soon or later the 2nd Law will impose its energy dictatorship to all the humankind.

Rolling Stones – Time is on my Side

According to Tim Harford  there is an Optimistic View about a self-regulation of the world economy that, thanks to the supply-demand’s law, will guarantee an endless growth and energy efficiency as well (see Energy Use and Growth: an Optimistic View).  In particular, for Tim Harford the key fact is that:

Economic growth and energy growth are not the same thing, and there are good reasons to believe they’re already in the process of decoupling from each other

Believe!?! Despite there are good reasons, why the sustainability of an endless economic growth is not certain and still a Belief? Is really knowledge what is missing?

What about replacing “believe” with more certain words such as “assert”, “confirm” or “state”? Few simple questions should be answered:

  1. How much energy the planet Earth receives from the Sun [S]?
  2. How much energy is needed for supporting life (carbon cycle,  photosynthesis, climate,…) in the Earth [L]?
  3. How much energy is consumed by the world economy [E]?

Are the life and the human activities together in the planet Earth sustainable?

If

Energy from the Sun [S] < Energy for sustaining Life [L] + Energy consumed by the economy [E]

Mr. Charles, after few calculations, will give the answer: UN-UN-UNSUSTAINABLE!

So, conscious about the uncertain sustainability of the world economy as it is defined nowadays, let’s move our bodies following the irresistible funky rif of “Panic Station” from “The 2nd Law” album by Muse while since entropy is inattentive (it’s still singing “Time is on my side”).

MUSE – Panic Station

You won’t get much closer
Until you sacrifice it all (all the energy available)
You won’t get to taste it
With your face against the wall (the truth of The 2nd Law)

…actually, the humankind has already “tasted” the unavoidable rule of the 2nd law. In the 18th century, the population of Easter Island has dropped from 15.000 to 2.000-3.000 because an ecology disaster due to an unsustainable use of the natural resources (see Easter Island, they harvest all the woods in the island). If the inhabitants of Easter Island had had the chance to see a concert of “The 2nd Law” tour in Rapa Nui probably they would have decided not to hack up so many trees. Is the humankind smart enough to learn from his mistakes and make the optimistic view of growth really sustainable? Who knows!

Feelink – Feel & Think approach for doing life!