Keep Calm and Let the Business Analyst Handle it

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A Day in the Life of a Business Analyst

Business Analytics has emerged as a much sought after skill set. Professionals with business analytics expertise can work in different analytical profiles in companies to help them grow – but what exactly do they do? This article breaks down the essentials of a BA profile by looking into a typical day in the life of a business analyst. 

Equipped with strong analytical skills and a sound knowledge of the market, business analysts take care of a range of tasks to help companies meet their business goals. While collecting and interpreting data is core to a business analytics profile, stakeholder communication, meeting management and report collating are equally important. Aspiring business analytics professionals can refer to this detailed account of a day in an analyst’s life to understand the requirements and set their expectations. 

For a business analyst, a typical day starts by pinning up tasks on a storyboard to plan and prioritise them. As with most other roles, business analysts also have team meetings to discuss pain-points, pending tasks, obstacles and priorities. After having the tasks planned out, the workflow looks somewhat like this:

Prioritization & Business Context: Analysts typically like to plan their day and week meticulously in advance. Iteration planning meetings (IPM) are an excellent way to interact with the whole team and stay updated on all the ongoing projects. This iterative method ensures that objectives and plans are clearly explained. IPM also helps the team to understand the business context of any particular project and prioritize accordingly.  

Investigate Goals and Issues: An important part of an analysts job is to identify the problem. Research, interviews, analytical observations are few of the ways in which analysts investigate the situation to recognise the issues. Analysts look at past data, and try to make projections based on inferences.

Analysing Information:  It is after collecting data points concerning the issue at hand, that analysts finally get down to the analysing part. Data sets are thoroughly examined for recurring patterns and anomalies. Analytic reports are then shared internally for teams to understand the problem areas. These reports break down series of data sets into comprehensible explanations so that they are easily interpreted by the leadership team to help them arrive at business decisions unanimously.

Documenting Information: It is important to record all the analytical findings since they can act as future reference points. Analysts spend a considerable part of their day collecting and documenting all the analytical results, inferences and new developments. Considering documentation techniques are specific for each report, analysts also spend time looking into different documentation methods to choose the best option for any given report. 

Backlog Grooming:  This is an ongoing task for analysts- analysing and distributing the backlog. Resource optimization is crucial for any business and analysts aid that by efficient backlog management. Analysts go through the task lists and plan resource allocation according to priority.

Meetings and Communication: A major part of an analyst’s day is spent in active communication- internally with the team or externally with stakeholders. Business communication is not limited to just speaking, but it also means non-verbal communication in the form of emails and presentations to make sure that information is properly relayed, agreed to and acted upon.

Client Interaction: Client feedback is an integral part of any business plan. The best way to ensure that you are proceeding in the right direct and your business goals are met is by getting direct feedback from the clients. Feedback sessions can be used to evaluate the progress of the projects and analyse its success. Incorporating feedback in the project proceedings will lead to more satisfactory results and improve project success rates.

Business analysts act as a bridge between problems and solutions, trying to understand the former and planing the latter. However, a business analyst needs to work closely with the development teams, operations teams and the service teams to make any business project successful. A typical day in a business analyst’s life involves different kinds of tasks like extensive communication, reporting and documentation. While knowledge of analytical tools is an absolute necessity for an analyst, interpersonal communication skills coupled with strong business acumen is also required to deliver results.

Top 5 Examples of How Supply Chain is Using Analytics to Solve Its Problems

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Supply Chain is a tricky business. One missing entity or a lack of synchronisation can break the entire chain and mean losses in millions for a company. However, the use of analytics in this domain is resolving several pain points in supply chain management at the strategic, operational, and tactical levels. The analytics reports help businesses to scale up through performance monitoring and enhancement. According to Capgemini Analytics, “Supply Chain Analytics brings data-driven intelligence to your business, reducing the overall cost to serve and improving service levels.” For supply chain professionals, it can only mean one thing – to upskill to be able to use advanced analytics to improve operational efficiency and make data-driven decisions. Here are 5 supply chain analytics case studies about the use of analytics in the supply chain that will motivate professionals in this domain to upskill:

  1. Identify the most efficient shipping carriers through advanced analytics – One of the issues that a Fortune 100 CPG company faced was assessing each carrier and choosing the right carrier for shipment across the globe. Since there were various metrics available, the challenge was ranking carrier performance and choosing the right one for shipping. Understanding the carrier selection framework, the solution by Fractal Analysis followed a step-wise approach by identifying correlated attributes, ranking of carriers, and assessing alternate carriers via what-if analysis. Read the complete case study here.pgp business analytics (pgp-babi) great learning
  2. Pierian Digital delivered interface, forecasting, and visibility solution to oil & gas major – A Global EPC Service Provider was facing issues without a common user interface across applications to provide end-to-end visibility, visibility of global supply chain and logistics processes, and forecasting for cost and schedule. Pierian Digital’s solution provided Proactive Supply Chain Performance Management Analytics insights positively impacting the top and bottom-line business growth specifically through improvements across the whole supply chain. Read the full details here.
  3. Gartner Analyzes Market for Supply Chain Management Solution – A Fortune 500 company knew its innovative solution for supply chain management had huge potential, however, management needed the validation of the market, the competitive landscape, and opportunities to secure funding. A Gartner engagement answered all their questions by conducting a full product assessment, sizing the market, and analysing competitive alternatives. Once they were able to use these supply chain advanced analytics report, they could market their solution successfully. Read more.
  4. Improved forecasting and inventory planning for a large retailer – Mu Sigma helped one of UK’s leading fashion retailer to build a customised demand forecasting and inventory planning solution for its online channel involving apparel and home furnishing products. They developed an analytical process to forecast demand and estimate launch quantities for new products during seasonal sales leading to an increase in product availability by 8%. Read the case study here.
  5. Use predictive modelling to control critical process parameters – A Fortune 100 fertiliser manufacturing company produces fertilisers that must meet quality criteria for key natural elements like potassium, nitrogen, and phosphorus to be within a defined range of specification. The results of thorough data understanding and brainstorming determined that for water soluble fertilizers, in 98.4% of instances the prediction accuracy was greater than 95%. For other nutrient products, in 99.9% of instances, the prediction accuracy was greater than 95%. The client saw multi-million-dollar savings through these tools in fine-tuning the manufacturing process. Read fractal analytics’ 4-step approach to know the full solution.

Click here to explore a career in Business Analytics.

Sources: Mu-Sigma, Fractal Analysis, NASSCOM, Gartner.

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What is Upskilling and why you need to pay more attention to it than ever?

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As per the latest NASSCOM report, up to 40 percent of the estimated 4 million workforce in India would undergo re-skilling over the next 5 years. 

You must have come across articles blaring data points like the one above in the past few months and would’ve brushed them aside conveniently, but if you are planning to make 2018 a milestone year in terms of Career Growth it’s time you took the latest corporate buzzword seriously. ‘Upskilling’ has arrived and it is here to stay.

In light of the layoffs witnessed by the IT industry last year Reskilling/Upskilling has become the new mantra to success, and for the all the right reasons. But before we get into why it is super important to upskill yourself more than ever now let’s understand what upskilling really entails.

What is Upskilling?

Upskilling refers to improving the skillset of professionals, usually through training to enable them to perform better in their jobs and help them progress through the company into various job roles and opportunities. Upskilling opportunities can be provided using a number of formats, ranging from short courses to getting higher qualifications or gaining certifications through part-time or full-time programs.

Here are the top reasons Why Upskilling is important for you now more than ever:

  1. It helps you keep up with latest Industry Demand & trends– Learning new skills or improving existing skillsets ensures that you are up to pace with the shift in trends your domain is witnessing. As an example take The Union Budget 2018 and its clear focus on AI, Big Data and Robotics and their application in the Digital Economy. We can clearly see career opportunities are set to rise exponentially in these domains within the next 2-3 years. So if you were to acquire a new skill or develop expertise in a new domain, Analytics, Big Data, AI or IOT could be a great option.
  2. You can increase your pay-check in no-time- According to a staffing solutions company, TeamLease Services, India will face a demand-supply gap of 2 lakh data analytics professionals by 2020. This lag between demand and supply exists not only in India but is a global phenomenon. As per the estimates of McKinsey, the gap between supply and requisite demand for analytics skills in the US will reach 50-60% by 2018. With the industry all set to witness such a huge demand gap you can utilize the opportunity to get a lucrative pay package in the respective domain. A sure shot way to develop a new competency in it would be to take up an industry-oriented program focusing on a new-age skill. You might have to invest a year or 6 months with such a course but the gains in terms of better employment opportunities and rise in pay scale will all be worth it.
  3. You can future-proof your career– More technological advancements sometimes translate to more and more people being replaced at their jobs. A recent threat to millions of jobs is posed by Automation and Artifical Intelligence, although the number of jobs that will be automated due to AI is debatable it is always better to future-proof your career by developing new competencies. It is hence beneficial to become an irreplaceable asset to your organization by constantly proving that you have the grit and enthusiasm to learn new things and stay updated.
  4. Enable a successful career transition– In case you are planning to transition into a new role or enter a new domain altogether, Upskilling will help you facilitate the shift with much more ease. A program or course that enables you to build a body of work through industry-based projects will surely be helpful in tackling interviews with prospective employers with confidence and will display domain knowledge. Look for a program which has a good mix of industry participation which will allow you to network with industry experts and thought leaders and give you opportunities for referrals and endorsements.

The bottom line

With newer employment avenues opening up in the IT industry, the emphasis is slowly shifting from Scale to Skill. Technical competencies aligned with the Digital Economy are therefore in high demand. The time to explore new waters and ride the new wave is now. Re-skill or perish is the only way forward.

The only resolution you should be making in 2017

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Every New Year brings with it the hope of a new beginning in our lives and along with it, come the myriad of resolutions we make to ourselves. Research indicates that most of the resolutions made by people are towards fitness and weight loss. As a result, January becomes a windfall month for most gymnasiums and fitness studios while most of us don’t become any leaner or fitter with passing years the one thing that we can definitely achieve is being a better version of ourselves. To achieve that you don’t have to make tall promises to yourself just Make Learning a Habit.

Learning new things is simple, achievable and one of the most profitable investments you can make each year.

 

1. Learning is like weight-loss

train

Let me make an uncanny analogy here: Aspiring to becoming leaner is very similar to wanting to learn something new. Ultimately, you have to change something that’s core in your behaviour to have the desired results. Both these goals need focus, determination and lots of discipline. And lastly, just as in weight loss as in education, there are no low-hanging fruits or express results. Both take time to fructify, but once you go the distance, there is no looking back.

 

2. Why ‘Learning’ in 2017?

Why we need to learn in 2017

The right question here should be ‘Why Not’. There has never been a better time to learn and frankly speaking, with the changing dynamics of businesses and technology disruption impacting us, if we don’t make learning a habit in 2017 and onwards, our professional credentials would be questionable at best and irrelevant at worst. Learning new skills and upgrading one’s professional capabilities is no longer a matter of choice but a necessity to have a fruitful career. In today’s time and age, the half-life of knowledgehalf-life of knowledge is forever decreasing which means that one needs to keep learning always to stay professionally relevant. The new reality is that what you learn at 25, will not take you till 35.

 

3. What should I learn?

What should you learn

This is like standing by an ocean and trying to find the perfect starting point for your swim. What you can learn is limited only by your intellectual bandwidth and interest. For the sake of brevity, let us focus on what the professional in you needs to learn. Depending upon the industry you are in or aspire to be in, you need to understand the trends that are driving growth. If you are unclear about it, you should talk to your seniors from the industry and pick their brains. Pick an area that is affecting most companies in your space and eventually will impact everyone and build your skill sets in that. Professional competencies such as analytics, big data engineering, product management, information security, intellectual property, digital marketing etc. are high growth areas where most companies are struggling for ‘good’ talent. Finding a sweet spot like this and making yourself competent in it will ensure your career benefits from this talent shortage.

 

4. Where should I learn?

e-learning

Learning in 2017 will be easier than ever before. From blogs to YouTube or TED, from companies offering online learning to mobile apps, ‘lack of access’ cannot be your excuse to not learning. But having said that, having a plethora of options makes it overwhelming and confusing.

I come across some candidates who know what the skills they need to acquire but are not sure if they will be able to learn. I usually advise them to first test the waters by accessing some free content online. YouTube is usually a good source for this. See if you like what you are learning and are able to grasp it.

 

5. Why do we fail to learn online?

why we fail to learn

If you are the kind that does not suffer from such starting troubles, you will usually find your learning options to be either completely online courses or blended courses (online + occasional weekend classroom sessions). Given this spread, how do you decide which format to go for?

Completely online courses provide convenience since you don’t need to attend any classroom sessions. But, online learning has been plagued by abysmally low rates of completion. The main reason for this is that for most of us, we learn better when we learn in a classroom setting with peers and faculty, who we can talk to in person.

The flexibility of attending class room sessions over few weekends in a month gives you the advantage of mixing the best of two worlds – the flexibility of online learning and the learning effectiveness of classroom learning. In our blended analytics program, we have seen hundreds of candidates do our program after having done one or multiple online courses. When asked, the most common response we get is because they feel that their learning in the online programs was incomplete. Also, when it comes to acquiring hard skills such as analytics, big data or machine learning, it is important to focus on programs that are more exhaustive and immersive and don’t take a superficial approach by promising to teach something in a matter of some hours.

 

6. What will it take?

learning in 2017

Learning is for everyone. Amongst the thousands of candidates who take our programs every year, we see about 30% of them to be with in the 15-30 year experience bracket. While there is no age to imbibe the habit of learning, just like with all good habits, the sooner you do it, the better you are. Having said that, learning is hard work. Depending upon when was the last time you were in a class, you would need discipline, focus and perseverance to go the whole distance. Usually, we have seen that the first two months are the hardest but once you settle into a routine within the first sixty days, you will go one to achieve the results you desire. The advice that we give to all our learners is to start small. Begin by dedicating an hour every day for the first 2 weeks, then about 8-10 hours a week for the next thirty days. Small changes in your habit will ultimately lead to big gains in your learning and professional success.

On that note, in 2017, make a promise to yourself. To learn something new and to challenge your professional status quo. Make Learning a habit and build the career you’ve always wanted. Oh and as for fitness, try playing a sport – 5 days a week. It is fun and just as effective (or ineffective) 🙂

RIP Degree, Hello Competency?

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The inevitable transition of value from Degrees to Competencies in the knowledge economy

I had a conversation in Bangalore recently with a senior technology professional, one with over 20 years of experience in both large and small technology companies and currently in a VP role at one of the posterchildren of India’s Internet businesses. He said that when he interviews people these days, very rarely does he look at what degree they possessed. He is more interested in what they can do and what the most recent course they had done on Coursera.

Shift in Hiring Manager’s mindsets

Conversations with dozens of senior industry professions over the past couple of years indicate that most of them, in their hiring decisions, look more at what the candidates know (knowledge) and can do (competence) rather than what degree they have.

This is a phenomenon, increasingly common, that acknowledges the fact that our undergraduate and post graduate degrees are no longer good enough. The rapid pace of change being driven by technology has meant that we have to be constantly learning to keep up with the latest and best practices.

When we were growing up, people were introduced to each other an engineer, a doctor, a CA, a lawyer, a commerce graduate, an arts graduate, etc., – essentially tying our identity to our formal education. Job requirements were specified in these terms. The most essential requirement for a job would be the undergraduate or post graduate degree. Today, if you look at the job descriptions on Naukri or Linkedin for knowledge workers/roles, the degree would be the last or the second last thing that is mentioned with most of the other requirements specified in terms of competencies: x years of digital marketing experience, y years of data analysis experience, z years of design experience, etc. Unless it is from a very reputed top institution, the degree seem to hardly contribute to the interview evaluation. Even the value being added by the reputed institution seems to be attributed more to the filtering and motivation/drive of the candidates that it signals than the specific degree that is pursued there.

This transition is already manifesting in the recruitment practices of several of the most reputed companies in the world. A few weeks back, Ernst and Young, one of the most reputed consulting firms and a large recruiter of young talent globally, declared in its UK division that it would scrap the UG degree as a recruitment filter and instead rely on its internal competence assessment. Several technology companies like Google, Uber, Facebook, and closer to home, Flipkart, Snapdeal, etc., have started accepting candidates based on informal credentials like the “nanodegrees” from Udacity or the “specializations” and certificates from Coursera, which are merely signals of verified competencies and not accredited degrees or diplomas.

This phenomenon hit home for me recently from the most unlikely of sources. I was attending a talk at one of the TIE conferences on education in Delhi and the keynote speaker was an ex Pro Vice Chancellor of IGNOU. IGNOU is the world’s largest grantor of degrees in the world, having over 1 million enrolees and distributing hundreds of thousands of degrees and diplomas each year. I am sure these degrees are meaningful to a large number of people who were not fortunate enough to go through a full time college experience and are qualifying them for a large number of government and public sector jobs thus serving a valuable purpose for them. However, it is widely acknowledged that they hold little value in the knowledge economy due to the poor learning outcomes associated with them.

Given this background, I went into this talk expecting to hear a very traditional perspective on education from this septuagenarian gentleman. However, what I heard blew my mind. He had some of the most progressive and creative ideas I had ever heard on the transformation that is happening and will happen in the world of education and in the global talent markets. One of the points he made really stuck. He said, “Today, what KRA stands for has changed. It stands for ‘Kyun Rakhe Aapko (Why should I keep you)’”. I thought that this captured most succinctly the massive change in focus in the talent market from degree to competency.

Dawn of the Portfolio

If competencies are becoming all important, how does one showcase them or communicate about them? This is being done through creating a “Portfolio” or “body of work” that demonstrates the competence. This approach is not new. It has been widely used in other fields that require creativity and innovation, qualities that are increasingly more important in the knowledge economy. A photographer, an architect, an artist, a designer, a writer, a journalist, a film director, a PR executive – all of these professionals are judged by reviewing a portfolio of their prior work. This is now being applied to knowledge professionals as well. Good programmers are being judged by the code libraries they have shared on Github, the hackathon they have participated in and their topcoder rank. Good Data Analytics professionals are being judged the analytics problems they have solved on platforms like Kaggle. Marketing professionals are being judged by the blog posts and social media presence they have created for their brands.

I believe that this trend will accelerate further as it is in keeping with the general shift in decision making becoming more and more data driven. When recruiters can make decisions based on data that is directly relevant to them, like the directly relevant portfolios of candidates they are considering, they have a little reason to depend on a stamp applied by a third party education institution using methodology that may or may not be relevant to them.

So, it’s high time all knowledge professionals, particularly those at the early stages or their career, start creating their personal portfolios. That will be their currency in the competence-driven world of the future.

People Analytics for Employee Engagement

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The last few years have seen the emergence of analytics as a potential force for driving data-based decision making in HR. Traditionally, Human Resource Management forms the policies and practices that define the workplace culture of the company. It deals with identifying, hiring, training, motivating, and retrenchment of workforce. Human Capital Management, on the other hand, is the strategic issue that systematically seeks to analyze, measure and evaluate how these policies and practices create value. HR Analytics is one such practice under HCM. It is a combination of software and methodology that applies statistical models to worker-related data, allowing enterprise leaders to optimize human resource management. Genpact has been using people analytics successfully to drive employee engagement over the last 2 years.

Gallup, a research-based global performance management consulting company, in their recent survey, found that concentrating on employee engagement can help companies withstand, and possibly even thrive, in tough economic times. It advocates that companies with high engagement have a 20% boost in productivity and profitability. They also said that globally, only 13% workers were engaged.

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Engagement reflects upon organization’s operational capabilities from the viewpoint of its employees such as Leadership, Change Advocacy, Work Culture and other important competencies. It can help highlight issues like reasons for attrition and incompetent leadership. It can also predict well in advance the dissatisfied or unhappy employees who might either eventually attrite or their performance suffers due to lack of focus which finally leads to firing. In both the cases, the company ends up exhausting its vital resources like money and workforce in filling up those places again. It is a fact that retention is always cheaper than recruiting. Therefore, if unhappy/dissatisfied/disengagement employees could be predicted it, will help in forming an effective retention policy specific to individual problems or at least help in understanding the problem itself if not able to retain. With HR more and more becoming a strategic partner in helping a company achieve its goals, organizations today are looking at employee engagement to be a driver of business outcomes.

With tools to manage onboarding, performance management, succession planning, workforce analytics and HR Management, Howden, an engineering firm has increased HR process efficiencies and retention of its top talent, while decreasing time-to-productivity for new employees and costs associated with employee turnover.

Genpact has worked extensively in the area of attrition. The basic premise they work on is that dissatisfaction leads to unhappiness at work which causes disengagement and ultimately attrition.

The analysis at Genpact begins with a complete database of employees containing details since the time of their joining. Along with various attributes like age, gender, date of joining, date of birth, date of leaving, days in band etc., they also collect a first line manager survey (FLM Survey), which is designed to get ratings of managers from subordinates based on Six leadership competencies namely: Business Acumen, Change Advocacy, People Leadership, Execution, Effective Communication, Customer Centricity.

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Apart from this, they also have performance ratings of the employees which categorizes them according to their potential. They also undertake a lot of engagement initiatives and keep records of the employees who participate. Training data is also available of the employees who have undertaken trainings and their performance on those as well as their other achievement.

Genpact has found a positive relationship between the performance ratings and their FLM surveys. Using this data, they were able to identify factors which are important for employee retention and which enhance an employees’ sense of engagement. Once this is done, they can better engage the employees by using the analytics data in the following ways:

They are able to prioritize the initiatives out of the basket of engagement activities, which have the maximum impact and are able to redirect investments to the more beneficial ones.

Using analytics they can predict employees who are at the highest risk of leaving the organisation within the next 6 months and can design interventions to rehire them or re-engage them to minimise the risk of attrition.

This becomes very important for them as they invest a lot of resources in training and developing their employees. Therefore, every employee who leaves is a drain on the resources.

Career Break? Add these hot skills to your resume to entice the recruiters!

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A lot of working women take mid-career break of 1 to 5 years to look after their children when they are very young. However, once the kids grow up, when lot of women want to resume their careers; they often hit a wall – as their skills (if in a technical field) are considered to be obsolete as they carry no experience with the latest technology or practices mandatory in their respective industries.

Well, actually there are so many things those women can do in order to prepare themselves for the transition back into the workforce. The most important amongst them is to upskill oneself through short term or long term course in the chosen field, networking with ex-colleagues to find relevant opportunities in their industry, or perhaps start with internships or unpaid voluntary roles to get a foot in the door.

Analytics is a fast growing industry today and data scientist is becoming one of the most sought after professions in the past 2-3 years. Enrolling oneself in an analytics course can be one rewarding opportunity to get back to work life after a sabbatical. Few compelling reasons that make Analytics profession a great career option are:

In demand skills

The field of data mining and analytics is growing rapidly, creating a substantial gap of talent, globally. Businesses today trust data mining and analytics for informed business decision making, and look for talent who can work with data and help them in business decision making.

Multi-Industry opportunity

Today, there is hardly any industry, established or growing that does not opt for data driven decision making. Be it healthcare, telecom, sports, ecommerce, finance or government, and across functions like HR, management, operations, sales, and marketing, Analytics does play an eminent role. Whatever be person’s past industry or functional experience, analytics skills can be one good addition to existing skills. For example, a person who has worked in the banking sector can learn about financial analytics, while one who carries retail experience can learn how analytics works in marketing and ecommerce, IT professionals can get into Big Data Processing and analytics, where the requirement is usually of strong IT and programming skills in addition to data crunching knowledge.

Management life-skill:

Often at the time of taking a break, most of the women are in entry level – mid management level leadership roles, and prefer resuming the career at a same level. The competence to make better and informed business decisions on the basis of data is becoming an important part of any management role, irrespective of function. Thus, an inclusion of data analytics skills will supplement wholly supplement the past experience and make resume more alluring to potential employers.

Well, there are many barriers to entry for women looking to get back to the workforce after a long break.  Even after extensive prior experience, women do find it difficult to get back into the job market with no experience of current market tools and practices. Hence, to increase their chances of being shortlisted for roles relevant to their experience and skills, they should update their skill set, especially in areas that are in great demand such as analytics. If you are interested, check out  comprehensive courses at Great Learning, one of India’s most premier learning institute.

LIGHTS, CAMERA, ANALYTICS

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Every Friday is one big day for filmmakers when a Bollywood flick with its fair share of romance, comedy, melodrama and action is all geared to release, giving producers a genuine reason to bite the nails for the movies fate. Will the movie pull in abundant profits or will it turn out to be the forgettable flop?

How wonderful it would be if we could call the genie, pull out our crystal balls or get the tarots read on this? Is there any way to save our producers from numerous weekly heart attacks?

FROM THE GUT TO THE GUTTER

Remembering the charisma of Jack Sparrow, all three sequels of Pirates of Caribbean were smashing big hits at the box office. Encouraged by this success, Disney came to a conclusion that John Carter with a similar dose of action and special effects would be again a hit.

Unfortunately, the truth is that John Carter turned out to be the biggest flops of all time.

How could Disney get it so wrong? The culprit lies within – it’s called the gut! For a very long time, our film industry has relied on tried and tested formulae, but lately we have seen movies like Queen, which are made on a shoe-string budget movie to be hits while big budget movies like Roy and Finding Fanny flopping. Hence, times have come to revise and optimize the thinking relevant to audience needs. It is high time when movie makers should do decision making on data rather than relying on gut feeling.

Recently, Bollywood has come up trumps for analytics, giving predictions on which movie will succeed and which will bomb at box office. Data gathered from different social platforms like Facebook, Twitter, You Tube, blogs was able to predict the success of ‘Ramleela with confidence percentage of 73’, which ultimately proved to be correct.

ANALYTICS IS A HERO

Just for example, let’s say Disney want to remake John Carter, keeping in mind ‘predictive analytics’.

To decide on the cast, the studio can initiate by looking at all the action/adventure movies released in the recent years that had one particular star, check on their releasing dates, location wise performance, major events done to promote them, etc. and see how successful each one of them was. Data could also be pulled from social media comments to know whether audience developed fatigue with that actor in recent times.

Movie success prediction also helps companies to plan their resources. A studio that expects its newest movie to be immensely popular will certainly rent more theatre rooms in advance.

The Hollywood star Will Smith is one celebrity who has intelligently applied analytics to pursue a career in cinema. Along with his business manager, they analyzed top 10 highest money grossing movies so as to uncover their patterns. They found each one of them had special effects, with 9 having special effects with aliens/creatures from outer space. And 8 out of 10 had special effects, creatures and a love story. The rest we all know is history. Independence Day, Men in Black, I, Robot, and then I am Legend…..are few of his movies that fall in this patter and needless to say, have been runaway hits.

CURTAINS

In predicting the success of a movie, data alone can play one big role. In times of today, when data influences our everyday decision making, predictive analytics can be a magic wand that can create order out of so much chaos of decision-making and answer the enigmatic question….Are vampires still a hit?