Business Analytics

Business Analytics- The Next Big Thing

Business Analytics- The Next Big Thing

Business Analytics is one sector which has been growing rapidly with organizations such as Flipkart, Amazon, Walmart, Facebook recruiting various talents across B-Schools offering specialized Business Analytics course. Most organizations used to outsource major analytics work to pure analytics firm but today, in-house analytics teams are preferred. B-Schools such as School of Inspired Leadership(SOIL) have realized the growing awareness about business analytics and buzz words like Data Mining, Big Data, Text analysis are captured by courses offered in SOIL.

Why Business Analytics?

Business Analytics helps to decode the Why, What and How questions from any organization. Huge amount of data available to organizations help to decode why part. The what part is ability to work huge amount of data, analyze and break it down into critical insights.

Business Analytics requires to define current state, desired state, identify gap between desired and current state, generate and evaluate hypothesis and last but not least, story boarding and visualization. Above processes are carried out for which different form of analytics are used such as Descriptive, Diagnostic/ Inquisitive, Predictive and Prescriptive analytics.

  • Descriptive gives an overview of what has occurred in business and is presented in form of old data and takes form of reports, flowcharts etc.
  • Diagnostic/Inquisitive helps in understanding why something has happened till a particular time which involves drilling into the data through traditional methods such as regression, factor analysis etc.
  • Predictive Analytics part deals with what can happen in the future and involves a high analytics bent of mind which is used to predict the future of using data modelling and forecasting methods.
  • Prescriptive Analytics part deals with what to do which is meant to tackle the predictions made and take the business to the top.
  • Tools

    Proprietary software such asSAS and IBM SPSS. But most widely used software is R due to ease of availability. R and SAS are mostly used for Predictive Analysis, SQL and Teradata is suitable for smaller data pulls.

6 Reasons Why You Should Choose SOIL PGPBA

6 Reasons why you should choose SOIL PGPBA

India’s Most Comprehensive Analytics Program

The program is designed to make the entire Analytics learning curve an experience.  Our in-depth course curriculum and modules provide students with a comprehensive deep dive into the world of analytics.  Descriptive, Predictive Prescriptive Analytic modules are all covered as part of the course curriculum.  With over 380 Hours of Class room teaching, 30 Hours on capstone project and 350 hours of work for home assignments the PGPBA is truly India’s most comprehensive analytics program for working professionals.

Functional Business Domain Knowledge

PGPBA students get an opportunity to learn not only about Analytics but also get an overview of other business domains including Marketing, Finance, Economics and Human Resources. This makes them capable of solving real-life business problems using Data Analytics for different functional areas.

Innovative Pedagogy and Leading Industry Tools

The program courses and project work are designed around the real-world integration of business disciplines. Industry leading tools that are taught and used in the program include SAS, Tableau, R, Python, Hadoop, Hive, Pig and Google Analytics.

Industry Relevant Curriculum & Corporate Partnership

Interactions with leading industry experts and live action projects with organisations in Delhi – NCR provide a framework through which participants learn to enhance their management skills, expand their knowledge of business analytics and gain a strategic perspective of business application of analytics. Located in the hub of the services capital of India – Gurgaon, SOIL provides a multitude of networking opportunities with Organisations and corporates using cutting edge analytical insights to make better business decisions.

Leadership Networking with the Analytics Industry

The curriculum will provide multiple opportunities for our students to interact with Industry experts. The sessions with these experts will provide important insights on how Business Analytics can be instrumental in transforming students careers and how other organisations are using analytics to make a difference to their competitive advantage.

Social Cause Exposure

The Social Innovation project aims to foster social responsibility in future PGPBA Leaders. Students are paired with a not for profit organisations on projects that will help them apply analytical skills to community development and enable them to work on grass root level social welfare analytical projects.

Career in Business Analytics

Career in Business Analytics

People are unclear and bit lost in the terms of understanding Business Analytics .In today’s world a business analysts needs to be multifaceted. A successful business analytics needs to be clear communicators, facilitators, analysers and team players. Also you need to get the exposure of different backgrounds to be an ideal analyst and to understand the industry well, be it operations, finance, technology, architecture or anything.

What Does a Business Analyst Do?

As you explore the role of business analysts, you will about all the different roles they have to perform. From being a good communicator and data analyser to possessing project management and technical skills, business analysts regularly use a variety of techniques. They are the bridge that fills in the gap between each department throughout every step of development. Modern Analyst identifies several characteristics that make up the role of a business analyst. Business Analysts have to work very closely with the business so that they can identify the different opportunities where any scope of improvement is available in the business operations and processes. Analysts are always involved in designing or min modifying the business systems or IT systems. They have to talk to different stakeholders to understand the basic needs and problems related to business. They bring structure to all the unstructured designs. They ease the flow of business.

The beginner phase of Business Analysts

Beginning business analysts need to have either a strong business background or extensive IT knowledge. With that, you can start to work as a business analyst with job responsibilities that include collecting, analysing, communicating and documenting requirements, user-testing and so on. Entry-level jobs may include industry/domain expert, developer, and/or quality assurance. Within a few years you could choose to become a Subject Matter Expert (SME). This is the time to delve into the areas that interest you most and develop those areas that can help you progress into higher management positions.

The learner phase of Business Analysts

Once you have several years of experience in the industry, you will reach a pivotal turning point where you can choose the next step in your business analyst career. After three to five years, you can be positioned to move up into roles such as IT business analyst, senior/lead business analyst or product manager. The more experience you have as a business analyst, the more likely you are to be assigned larger and/or more complex projects. After eight to 10 years in various business analysis positions, you can advance to chief technology officer or work as a consultant. You can take the business analyst career path as far as you would like, progressing through management levels as far as your expertise, talents and desires take you.

How Much Do Business Analysts Make?

What you will earn depend upon what and how you work. As per a survey, this is what different job titles are being paid.:

Job TitleAverage Annual Salary
Information Security Analyst $88,890
Computer Systems Analyst $82,710
Management Analyst $80,880
Financial Analyst $78,620
Budget Analyst $71,220

Certification: Your Fastest Route to a Higher Salary and Increased Opportunities

Business analysts who want to enhance their expertise and expand their career options achieve industry-recognized certification.

But apart from everything, it depend upon how you work. It is you who can drive yourself to the heights.

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How to start your career in Business Analytics

It is difficult for someone new to find out the best way to start a career in Analytics. As this industry is in its new phase, hence it gets difficult to find proper guidance. Also there is a buzz created about Business Analytics but very actually understand these terms. There are limited well designed path which one could follow to enter the field. To build a career in Business Analytics you can follow two approaches-

Like any other employment skill, there are 2 approaches to enter an analytics career:

  • Approach 1 – Get in touch, hired or trained by a company on the required skills be it on job or internal training.

These would be companies which have Analytics in their system and use it for their day to day decisions. This approach is better from long term perspective but yes it takes time and investment. Some of the companies known for using cutting edge Analytics (in India) are:

  • Technology leaders:Google, Facebook, Linkedin
  • Banking, Financial Services and Insurance (BFSI):Capital One, American Express, ICICI, HDFC
  • Telecom companies:Idea, Vodafone, Airtel
  • Analytics Consultancies:Fractal, Mu-Sigma, Absolutdata, ZS Associates

Else you can also go for internship. It will give you altogether  2 months to extract as much knowledge as you want to know this industry closely..

  • Approach 2 – Get Business Analytics related certification: These certifications will provide you with in depth knowledge of all the technical knowledge and skills required for this industry but will not be able to give you the real life experience of the job or the industry which on job trainings provide.
    • For people with work experience, various leading academic institutes run certification courses.
    • For beginners, there are many certification courses available. Getting these certification courses can increase your chances of getting hired in some of the best companies.

While these are two ways to gain knowledge  for starting a career in Analytics, there are smaller tips which  you can follow to increase your awareness. You should keep on reading about this subject. Nothing is going to be enough. As much as you read, you are likely to be more expert. Keep reading blogs and books. There are any workshops and conferences on this particular topic, you can always go have an idea about the industry. Go through the training materials which are available on the internet. Talk to people related to this industry. And try to get an internship. You just need to have faith and work hard.

 

Myths about Business Analytics

Myths about Business Analytics

When terms like Business Analytics pops up, lot of us takes our step back. Many of us have a notion that such areas are not for us, better to be away with such technical areas. But for all those who are scared of exploring this venture, let me clarify you few things so that you take a better decision.

When one talks about Business analyst, you don’t need to an engineer necessarily. Business analytics is not a subject where only engineers have their role to play rather it can be taken up by anyone. The truth is that you don’t. All you need is a structured thinking process and a comfort with numbers. If you could provide structure to an unstructured data and also come forward with the calculations, you can be a business analyst. This is all what is needed. But yes companies will prefer people from quantitative background as they are expected to be better with numbers. By quantitative background, I mean people from any of these disciplines: Engineering, Economics, Maths, Statistics, Physics or MBAs with graduation in these fields.

You need to earn programming for the tools you are going to use for your analysis, you don’t need to be a programmer beforehand. Also business analytics is not just about using tools because a business analyst should have that intellectual mind which can think how to put situations coded into the tools.

Also Business analytics is not at all about large datasets. It may or may not be the case. Most of the time analytics team work on specific problems, which may or may not involve large datasets. The requirement of the role is to be able to put structure across unstructured problems and be able to use numbers to understand business and the changes required in strategy.

Also, don’t have a conception that you won’t find a job. In fact, this is one area where there is shortage and lot of attrition. So these firms are in need of you. And if you are really good at something, then finding a jb can be a problem. Success will search for you.

 

Name your price: The power of analytics

Name your price: The power of analytics

 A new generation of pricing and revenue management practices can lead to meaningful results quickly.

In the travel industry, pricing has always been a tough job. Overprice an airline seat, hotel room, cruise cabin, or rental car today, and you won’t get a second chance to move that unsold unit tomorrow. Set the price too low, and you destroy value by selling out limited inventory too soon. No wonder, then, that the industry boasts some of the most sophisticated pricing capabilities anywhere. But in the era of analytics, those capabilities are looking increasingly outdated and inadequate. To meet the demands of large data sets and respond rapidly to fluctuations, targeted automation is a must have. Blame the Internet. An explosion of new sales channels, with price-comparison sites such as Expedia and Kayak, has ratcheted up competition and ever more frequent price changes. Digital technology and social media have also greatly raised the scope for one-to-one marketing — and made it possible to track the behaviors of millions of individual customers. As a result, pricing managers are faced with an overwhelming amount of information stored in a variety of places. For example, one travel company we know has three terabytes of pricing data in eight systems — including inventory data, current booking levels, historic demand patterns, and competitor information across thousands of categories. How can companies make sense of all this data — and use it to drive value? The answer lies in a new generation of pricing and revenue management practices that can yield meaningful results quickly. These have helped travel companies improve revenue per unit by 3-8 percent, and market share by 1-2 percentage points. But it is not just a matter of a software tool or a single new analysis. It requires a sharp prioritization, iterative building of tools, and hands-on engagement of many functions across the organization.

What, then, are the practical steps that pricing managers can take to master analytics using big data? Companies must recruit a new generation of pricing talent with more of a “trader” profile than an “analyst” one.

  1. Pinpoint the most promising opportunities. In the travel industry, those opportunities include determining exactly what each customer is willing to pay (through customer segmentation, targeted promotions and micro-marketing, sell-up, and cross-selling), and maximizing the use of available inventory (through, competitive pricing, overbooking, substitutions and upgrades, and so on). Effective pricing and revenue management organizations must have the talent and know-how to identify such opportunities consistently and systematically.
  2. Move quickly to automate key analyses. To meet the demands of large data sets and respond rapidly to fluctuations, targeted automation is a must have. To maximize use of inventory, for example, companies can develop automated utilization forecasts based on past booking patterns, current advance reservations, competitor information, and so on. Just as importantly, the output needs to be in easy-to-use, flexible formats, such as Excel-based tables or web interfaces. One tool we worked with automated the combination of revenue forecasts and inventory utilization data that was previously stored in separate systems; this allowed managers to track progress in real time and make pricing decisions that were much faster and better-informed. To analyze and simplify large volumes of sales data across locations, you’ll generally need customized IT solutions and applications. The best performers can get advanced systems in place in weeks then test and adjust, rather than waiting for months or even years to implement new applications.
  3. Align the organization around pricing performance. Companies often spend most of their energies and resources on building advanced analytics tools. But in our experience, they need to spend as much or more time making necessary changes to organizations and processes. At one travel company, pricing team interactions with supporting business units were originally ad-hoc and unstructured. So they developed a systematic process that allocated responsibilities for pricing and revenue management amongst the relevant departments, including pricing, marketing, inventory management, and distribution — and described when and how they should work together to create alignment on pricing decisions. As one output of this process, inventory managers developed a new appreciation for revenue metrics, and understood that these should take precedence over the utilization metrics that had previously been their focus. It’s also important to develop clear incentives that reward managers for pricing performance; and to recruit a new generation of pricing talent with more of a “trader” profile than an “analyst” one, ie. results-driven, comfortable with risk and experimentation, and able to make quick decisions.
  4. Train to sustain : Gains from improved pricing performance are hard to sustain unless companies commit to extensive and intensive training. Training should focus on the most critical elements of pricing that drive revenues, best practices for pricing and inventory management, and how to use new tools. Rather than using traditional classroom instruction, training needs to be emphasize the simulation involving real data and decision that Affects Company’s pricing in the market.

Putting advanced analytics to work

Putting advanced analytics to work

Putting Big Data and advanced analytics to work promise to transform the way many companies do business, delivering performance improvements not seen since the redesign of core processes in the 1990s. As such, these tools and techniques will open new avenues of competitive advantage. Many executives, however, remain unsure about how to proceed. They’re not certain their organizations are prepared for the required changes, and a lot of companies have yet to fully exploit the data or analytics capabilities they currently possess. Getting leaders’ attention Big data and analytics actually have been receiving attention for a few years, but the reason is changing. A few years ago the question was “We have all this data. Surely there’s something we can do with it.” Now the question is “I see my competitors exploiting this and I feel I’m getting behind.” And in fact, the people who say this are right. If you look at the advantages people get from using data and analytics—in terms of what they can do in pricing, what they can do in customer care, what they can do in segmentation, what they can do in inventory management—it’s not a little bit of a difference anymore. It’s a significant difference. And for that reason, the question being asked is “I’m behind. I don’t like it. Catch me up.” I get asked, “Who’s big data for?”

Finding better answers

So where have we been seeing data analytics recently? Well, the answer is in many places. An airline optimizing what price it charges on each flight for any day of the week. A bank figuring out how to best do its customer care across the four or five channels that it has. Allowing customers to be able to ask questions and get better answers and to direct them. All of that is on the customer side of things. And then in operations, think of an airline or a railway scheduling its crews. Think of a retailer optimizing its supply chain for how much inventory to hold versus “What do I pay for my transportation costs?” All of that lends itself to big data—the need to model—but frontline managers have to be able to use it.

Changing the organization

So what’s the formula or what’s the key success factor for exploiting analytics?

It always comes down to three things: data, models, transformation. Data is the creative use of internal and external data to give you a broader view on what is happening to your operations or your customer. Modelling is all about using that data to get workable models that can either help you predict better or allow you to optimize better in terms of your business. And the third success factor is about transforming the company you’ve developed a new model that predicts or optimizes, how do you get your frontline managers to use it? That’s always a combination of simple tools and training and things like that. Then there’s a medium-term challenge, which is “How do I upscale my and things like that.

Executing big data

There are several things you just have to do. The first is you need to focus. And what we mean by focus is, let’s take a pricing manager in a consumer services company or a buyer in a retailer. They have 22 things they do. Don’t try and change 22 things; try and change 2 or 3 things. Focus on part of the decision and focus, therefore, where the greatest economic leverage is in the business. The second is that you’ve got to make a decision support tool the frontline user understands and has confidence in.  The moment you make it simple, understandable, then people start using it and you get better decisions. For a company, if you have 100,000 employees and you’ve got only 14 that actually know this stuff and how to use it, you’re not going to get sustainable change. You don’t have to have 100,000. But you might have to have 10,000, five years from now, that are comfortable with analytics. So, again, link it to the processes, get the metrics right, and make sure you build the capabilities across the company.

 

Success Stories

Big Data & Advanced Analytics: Success stories from the front lines

Big data and advanced analytics can transform business .Even though sometimes company have not able to capture true potential of analytics, some companies are already seeing significant values. These companies which incorporated data and analytics into their operation show productivity raised by 6% compared to the peers. Following are the three stories that show how companies have used advanced analytics to their advantage and had an impactful delivery.

  1. Asking the right questions

As business grows, more data-rich the business becomes and hence this increases the importance of asking right questions. These questions are encouraged at the start of any analytical process because the scale of data makes it easy to lose the way and get trap in the endless round of analysis. Good questions identify specific decision that data and analytics will support so as to drive positive business impact. For example, two simple questions helped one insurer find a way to grow its sales without increasing the marketing budget. First, how much investment should be in marketing. Second was to which channels, vehicles and messages should the investment allocated. This helped in developing a proprietary model to optimize spending across channels by guiding the company as it is triangulated between three sources of data.

  1. Be creative

More data can hone models of consumer behaviour. This allows for accurate views of opportunities and risks. One telecom company recognized the data could solve a longstanding quandary which was faced by financial service companies. How to meet the need of millions of low income earning individuals for revolving credit which is similar to credit card but without credit risk model. Telecom executives realised this that payment histories of their mobile network could be used to solve the problem. So company created an innovative risk model to asses potential customer’s ability to repay loans. After this, companies are now exploring an entirely new line in emerging market consumer finance which uses this analytics as a core asset.

  1. Optimizing spend and impact across channel

Business is all about trade-offs between price and volume, between cost of inventory and chance of a stock out. In the past, such trade-offs were more of gut instinct and less of data. In the age of cookies and click through, it is not easy to optimize spending allocations. Big data and advanced analytics eliminate much of the guesswork. One transnational communications company had spent heavily on traditional media to improve brand recognition and invest in social media. Traditional marketing does not measure the sales impact created due to social buzz. Combining data from traditional media, sales and customer use of key social-media sites yielded a model that demonstrated that social media had a much higher impact than company strategists had assumed. More critically, company analysts found that the primary driver of social-media sentiment was not its television commercials but customer interaction with the company’s call centers—and in fact, that poor call-handling was subtracting almost as much value as the TV spots were adding. By reallocating some media spending to improve call-center satisfaction, the company increased its customer base significantly and gained several million dollars in revenues.

 

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