The Usual

When we talk about Business analytics, most people think about the MIS reports generated by IT department. In reality it goes much beyond that.

The Smart

Smart companies and managements have realized that Business Analytics can change their future in terms of competitive advantage, operational efficiency, revenue and profitability. Not just that, it could even help in new product launches and understanding what the market is looking for. Hence it has been made a CXO level initiative where the CMO and the CFO take active interest.

How to

Just having a business initiative does not help, and due to the firefighting that is the norm in companies, most initiatives stay in the cold storage until the presentation deadline. Part of the reason why few people act on it is also because its venturing into the unknown. We articulate the need of the CXOs in a short timeframe and enable a roadmap which can be acted upon. With our understanding of tools, experience in managing data, deriving actionable insights out of it and above all training people in selling those insights to senior management, we make this happen.

Data Cleansing

We address data cleansing not just as a technological problem but as an organizational and business initiative to enter the right data and validations. Drawing out the right process taking the business compulsions into consideration is the basis of any data cleansing effort. This along with assigning ownership of data works wonders better than any pure technological solution.

Data warehousing or storage

Access to clean data in a fast manner is pre requisite for most business analytics. Hence having a data warehouse separate from the transactional database enables analytics without disturbing the day to day operations. However, building a data warehouse and Extract-Transform-Load (ETL) is a long (often couple of years) and high cost process. To overcome this hurdle, QlikView provides an internal ETL and highly compressed data storage which can be loaded at night just like the data warehouse and then be used for delivering the analytics.

Historical Analytics

Reporting, Dashboarding and Query/Analysis tools offer Historical analytics to the executives. MIS reports are often the first step in understanding business using the key performance indicators (KPIs) prevalent in the industry and done with the help of domain experts in that industry. We believe that by just putting in a little extra effort with the right architecture, we can deliver much better analytics that can be used by decision makers to change the profitability of the company.

Predictive Analytics

Predictive Analytics or Data mining is well suited for any business which has a high volume of low or mid value transactions. For example, a bank or insurance company with lot of retail customers might be interested in knowing who their best customers are and what they should do, not just to retain them but to keep them profitable. This is a good prospect for data mining solutions.
On the other hand, a business such as high net worth private banking would have lot of relationship nuances involved which may not be captured perfectly by data. Also the value per contact in this case would be so high that there would be individuals looking at it and hence the value of mining this data would be limited. We bring several years of hands on expertise to help you define a roadmap for predictive analytics.

Tool Training for Analysts

The analysts have to be well versed with the tool such as QlikView or R so that they are comfortable doing what they are asked. Substantial effort is in understanding, formulating and getting sign off on the requirements from the relevant stakeholders. In addition, analysts have to learn to transform the requirement into a usable model in the tool and communicate this back to stakeholders.

Facilitated workshops for ‘Data to Decision’

Building a business analytics framework is just one of the things. Transforming the business needs handholding the key decision makers to be comfortable with the unexpected learnings from it and enabling them to take action based on it. Workshops with the senior management work best for this.

Building Strategies using Predictive Analytics

Making decisions with Predictive Analytics needs a good understanding of the underlying methods and their comparison. Often we find that people pay a lot of attention to get the last bit of accuracy in a predictive analytics methodology such as logistic regression and its statistical rigor without paying equal amount of attention to how the model is going to be used and tracking its performance. As a result, several modeling exercises end up with excellent results in development but do not replicate the same in real world.

Keeping this background in mind, this is a course focused on aspects to consider while building strategies with Predictive Analytics. Although we would look into probability, statistics and modeling techniques, it would be kept limited to application areas. It is not a statistical or modeling treatise but focused more on getting reliable results using predictive analytics for the purpose of driving business impact.
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