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  • An Age Of Truckload Information


    SUHANI POPLI
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    Once when asked what he does, if the data does not support his decision,

    John Maynard Keynes replied – “I change my opinion. What do you do?â€

    In a haystack of information today, that one thing which helps organizations take sound decisions is the ‘analysis of data’. Often, companies find themselves in situations where from a variety of choices, they need to pick one. In such cases, data-driven decision making enables following a systematic procedure. A successful completion of any process begins from a decision well made. It forms the first step of any execution process, and is thereafter followed by modification, as and when changes in information arise.

     

    The question that one would ask then is – ‘If it is data that is needed, then exactly how much of it?’. Authors like James Taylor and Stephen Covey, in their writings explain keeping ‘the end in mind' before undertaking a course of action. They say that the goal is never to build on the data; rather it is to use the facts to make work easier. Thus, the perfect quantity would be one which helps an organization make ‘timely’ as well as ‘correct’ choices.

     

    But even a manager’s power to predict can do this job, isn’t it? On digging deeper we realize that the ‘intuition' we are referring to is nothing but the gut feeling that arises based on a manager’s experiences of the past, and thus its own roots lie in data as well. What people actually follow is ‘informed intuition' – that uses previous occurrences as its basis. This is justified, since not only is complete information necessary, but also alongside is corporate alignment and clarity.

     

    Decision-making-cartoon-300x247.jpg

     

    These days, a term that managers often hear is ‘big data’ – which refers not only to the volume of data available, but also to the variety of it and the rapid pace at which it alters. Big data brings with itself the complexities of processing and interpretation, causing confusion and delays. It is here that just-the-right-kind of filtration is needed, to separate what is relevant and what is not.Infact sometimes, even lesser amounts of data can lead to better decisions being taken. As they say, the ‘first impression’ can indeed be beneficial if taken as the ‘last impression’. This is exactly where the use of instinct comes into picture. Whether it be studying a consumer insight or predicting the future, it is a blend of analysis and a manager’s intuition that leads to the apt solution. In a post in Forbes, Robert Carraway, a professor at the Darden School of Business said that big data and the increasing use of frameworks require not less, but a higher amount of managerial insight to accompany them.

     

    There have been faults based on judgment (remember Google claiming to overtake Firefox when launching Chrome?) ; and so exist popular crisis due to over-reliance on data. The idea hence is to strike a balance between these two seemingly different ways that managers use to reach a conclusion. The more an association can accommodate diversity in terms of style, emotions and experiences, the higher is the probability of improved performance.

     

    In a nutshell, if a corporation can make sure that it has as members both left-brain and right-brain thinkers – it can strike the nail on its head!

     

    (*source for the cartoon : Google images)

     

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    If I have been successful in the past by virtue of my intuition, why not continue with it? Do consider the fact that I have much exposure in the industry now.

    Thankyou for the question.

    In any sector, I believe, intuition has a major role to play, since no one can predict the future accurately. However, relying solely on it could prove to be dangerous in the long run, since the industry today is highly dynamic. What I am trying to express in this article is the fact that a combination of one's skills of data analysis and his/her power of prediction can help one take better decisions.

    Infact, if you'd ponder on what the source of your intuition is, you'd realize that it actually stems from how your thinking has proven to be correct in the past, which again boils down to how in reality, the 'figures' have aligned to your thoughts. Thus, the data aspect of decision making would add a feather in the intuition cap that you already wear. :)

    Hope I answered your query.

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    Can you explain how to apply Data Driven Decision Making in a particular sector? I do understand the general explanation your post gives, however its application, I feel, might be tough.

    Hi Praveen

    Thank you for your interest in the post. Using data as the basis for analysis is like a 'necessary evil' - 'necessary' because it enhances the accuracy of decisions, and 'evil' because as you rightly put it, its application is difficult. This is probably where the use of statistical tools could come in. Even for large quantities of data, softwares like SPSS, MS Excel, etc. to use graphics and forecast, instead of trying to work with a huge amount of data.

    Coming to a particular sector, say pick up sales. Sales in the future can be forecasted with respect to data. Incase of FMCG especially, what is selling the most can be found by consumer (offline as well as online) surveys. Thus, from this data and figures over time, sales for the future can be predicted to a reasonable extent. This could help a firm decide on a correct time to launch a new product, or probably make an effort to increase their current sales. Coupled with an intuition, infact, this could even bring about innovations (if one can foresee the latent demands of consumers in the market might be).

    Hope this answered your question. Do let me know if you would want an example for any other sector.

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    An analysis of everyday issues (such as the stock market numbers, etc.) can be done simply by analyzing data over the periods. How would you use your intuitive logic in such a situation?

    Hi Mandar,

    Thankyou for this question. Being inclined towards Finance myself, I follow stock markets to a reasonable extent, and hence feel that intuition has a great role to play in this field. In most investment situations, especially the complex ones, taking all the factors affecting it into account is nearly impossible. This is where the 'gut feeling' can play a significant role. Other cases could be those when information is classified or unavailable.

    As a matter of fact, there exists a subject called 'Behavioral Finance' which explains how emotions and thinking affects the investing decisions of individuals.

    As you metioned, on following the market closely and gathering information about the performance of a stock, one can 'analyze' its movement. But the purpose of an investment is usually to make profit, for which one would want to forecast what the market, and the stock would look like in future. Truly,one can develop 'correct' intuitive feelings only when s/he has information enough, but it is solely this intuition that can provide orientation in uncertain areas. Infact, financial markets in which instruments like futures, forwards and options are traded thrive on the ability to forecast of the major players, i.e. their intuition of whether they think an investment is worthwhile or not.

    Putting it succinctly, I would buy a particular share only when on looking at its price over time, I 'feel' that it would do well in the time to come. It is only then that when I sell it tomorrow, I would be able to earn a profit.

    Hope I answered your query.

    If you have some more time, do read :

    http://www.fool.com/investing/general/2006/05/22/the-role-of-intuition-in-trading.aspx

    It is the story of a person by the name 'Larry Livingston', Edwin Lefevre's protagonist in his book 'Reminiscences of a Stock Operator', and describes how he makes a killing in the stock market by sheer virtue of intuition.

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    Congratulations on the article, Suhani, it is explained quite well.

    But it explains only the supply side of a sector - how data is important for the 'managers'. Don't you think pondering over data is essential for those who demand as well? If Yes, could you elaborate on that?

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    Congratulations on the article, Suhani, it is explained quite well.But it explains only the supply side of a sector - how data is important for the 'managers'. Don't you think pondering over data is essential for those who demand as well? If Yes, could you elaborate on that?

    Hey Sucharita, thanks a lot!! :)

    I completely agree with you. Not only the supply, but also the demand side is dependent on data to a great extent.Probably the best example would be that of the stock market, where an investor always looks at the data to find out which stock is doing well, and hence buys it. Further, any firm in an industry demands inputs (raw material, electricity) and employs labor, depending on what its records of the past show (in terms of its output, efficiency, etc.) and what can be predicted for the future, given the current and past peformance.

    In a nutshell, be it any step - whether towards growth or innovation, or any other kind of expansion, reliance on data is an absolute necessity, coupled though with the gut feeling that tells you that you're going in the right direction.

    Hope I answered your query.

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    Hi Suhani, very good article and good responses so far. Referring to your examples of stock markets, why is it that mostly those with deep pockets survive in markets? Why is it that most of the stock advisers/ experts like to spend their time making recommendations for others while the money at stake is not theirs? Don't you think that the data crunching experts should ideally be busy in higher value activity of multiplying their own existing money?    


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    Hi Suhani, very good article and good responses so far. Referring to your examples of stock markets, why is it that mostly those with deep pockets survive in markets? Why is it that most of the stock advisers/ experts like to spend their time making recommendations for others while the money at stake is not theirs? Don't you think that the data crunching experts should ideally be busy in higher value activity of multiplying their own existing money?

    Hi Vishwadeep Sir

    Thankyou for your interest in the article.

    As I see it, there could be two possible reasons for why it is those with 'big pockets' who actually play well in the stock market -

    (i) It is these people who actually have enough funds to hedge their risk by investing in a variety of instruments (a commonly known phenomenon is that nearly 30-50 stocks across different sectors can bring down one's portfolio risk considerably).

    (ii) Even if they aren't 'financially literate' themselves, they possess the resources to seek help before making an investment.

    Putting it differently, if one doesn't have 'big pockets', one might tend to be more risk averse in nature. Such people would want a sure-shot return on their money, and might not prefer the stock market, per se. In cases when they do, there always exists a chance of the investment turning into a loss. This is where having 'big pockets' helps, since a reasonable amount of losses can be tolerated by this category of individuals.

    Coming to the second part of the question, this has been in my own mind for quite a while now, probably from the time I had begun to develop an interest in markets. I always wondered that if there do exist experts who know 'everything' about the market, why don't they leverage the opportunity and become rich themselves?

    Thus the answer to this question of yours is simply from what I have read, observed and learnt while myself trying to solve this query. A majority of those who are willing and able to invest in the stock market neither understand the meaning, nor the complexity of the different instruments that exist. Their objective is straight and simple - 'to get the maximum return'. This is where the role of 'advisers' or 'experts' comes in. Infact with people increasingly becoming tech-savvy these days, there are even online consultants available for this purpose. Truly, the idea for an expert should be to maximize his own wealth, rather than somebody else's. However, this again takes us back to where I started from - the 'availability of funds'. Most experts, have clients with a heavy bank balance, whereas at their own level, all they earn is a commission from the services they provide to their clients. This might be directly proportional as well, i.e. higher the client earns, higher the advisor's commission would be. Apart from this, another prominent reason is that the market to a reasonable extent is 'sentiment driven'. Hence, though the knowledge of experts is highly respected, it may not always be a hundred percent correct. due to this, there remains a risk of losing funds as well. Infact, it is different expectations which lead to people either choosing to be 'buyers' or 'sellers' in the market. If all experts had the same opinion, a market would not have existed in the first place, since everyone would behave in the same manner.

    Hope I answered your query. :)

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    Hey Suhani :)A very nice post. But tell me, what about new entrants in an industry, or first movers say. They have no past-performance data to review. Doesn't intuition become the only path to success in that case?

    Hey Jeny,

    Thanks for the appreciation. :)

    Coming to your question, not really. Rather to think of it, it is probably these players who need the maximum information or data about the industry they are going to enter. Truly, intuition would play a part when trying to predict their own trajectory of growth, but it is facts and figures that would essentially help any firm picture how it can carve an opportunity for itself. Based on this background information then, the firm can take necessary steps to establish itself, and grow further.

    Hope I answered your question.

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    Your article is quite informative, it gave me some food for thought.I do have a question - what are the different problems one must deal with when collecting huge amounts of data?

    Hi Roy

    I am glad you like the article.

    The major issues with a huge amount of data, as I see it, are -

    - Duplication or missing data

    - Availability of forged or incorrect data

    - Time and Cost associated with the search and collection of data

    - Obsolete figures are used for analysis in cases where data is unavailable

    - Reliability of the data obtained- Difficult interpretation of Big Data

    Though this list is not exhaustive, these are the most commonly observed sources of error when firms extensively deal with data. Firms employ various techniques to reduce, if not completely eliminate these errors. Common methods are to employ a group of people to solely deal with information and numbers pertaining to the company, collect data from varied sources, update it regularly, and check for its correctness. A combination of these, and some more steps taken, can help the firm deal with inconsistencies.

    Hope I answered your question!

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