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      ● There were also drivers that lead to poor service levels that should have been monitored. Those measurements include forecast accuracy, inventory accuracy, and capacity utilization.

      ● Another issue that negatively affected the company was cash flow. The cash flow was negative even without significant investment in the assets or resources of the company. It prevented the company from investing in the right inventory, which would have helped timely fulfillment.

      ● Profitability issues drove the negative cash flow with existing customers. The ability to assess the direct contribution to profitability by product or customer would have been invaluable in avoiding non-profitable product lines and/or customers. It’s important that your organization stop doing things it doesn’t get paid for. This is very difficult when the company doesn’t know which activities it’s not getting paid for. Profitability reporting at its most basic level involves using data to calculate the margin.

      A new management team implemented a number of these measurements and used analytics to make better business decisions, which began to turn around the business. Service-level measurements allowed the business to understand what was required to reach mass channel customers and retain them, and to identify and implement corrective actions to meet those requirements. They implemented forecasting processes and began to measure forecasting accuracy in order to better forecast demand. These efforts, combined with a focus on inventory management, in turn led to an organized production effort. That in turn led to customer orders being fulfilled completely and in a timely manner. Service levels were improved from below 40 % to over 98 % in a relatively short period of time, resulting in significant organic growth of the business.

      This example is important because it demonstrates that data – combined with the right business intelligence tools and analytical techniques – can be used to help answer the ever-present business questions, why did something happen (good or bad) and what should we do about it.

      What Companies Gain from Implementing BI

      When companies consider implementing BI for the first time, they always spend a significant amount of time and energy on comparing costs between different tools, calculating the total cost of ownership, and deciding whether the company can afford such a significant investment. Companies often don’t realize what it costs not to implement BI. The cost of continuing to act in the dark can often be much higher than the most expensive BI tool.

      With the help of BI, your management team can:

      In order to accomplish this nirvana of analysis, there should not be different versions of the same data in the enterprise. For example, unit cost broken down into its components of labor, material, and overhead that reside in one area of your database cannot add up to something different than the total cost that resides in another “table” or database in the organization. Using business intelligence tools ensures that you can access the correct version of the data even if it resides in a variety of places in your information technology architecture.

      Inevitably, different versions of the same data get created in any system. This is particularly true for smaller companies that do not always have the resources to install a new integrated ERP system. You don’t need to wait until you have the “perfect” ERP. With BI tools you can begin to build your analysis around the parts of your data that are correct and ignore the incorrect versions in the short term, in order to move forward with a better understanding of your business. If you wait for traffic to clear in each direction for a mile before crossing the road, you will likely never cross!

      When BI technology is implemented throughout your company, beyond the top executive level, you can enable your associates to:

      The Business Scenario Used in the Book

      The business problems and the QlikView techniques introduced in this book are universal and can be applied to a variety of companies and industry segments. We used a fictional company called Q-Tee Brands for the examples in the book.

      Q-Tee Brands focuses on manufacturing and distributing high-quality shirts, including dressy shirts, polos, and T-shirts, and it maintains a number of well known brands such as Q-Tee Baby, Q-Tee Mommy, Q-Tee Daddy, and Q-Tee Golf.

      The company needs our help in analyzing sales, profitability, and inventory, in order to support their strategic goals of growing revenues and profits.

      As with any textile company, Q-Tee Brands is managing their products using the attributes of style, size, and color, and it’s essential for them to understand the dynamics of sales, profitability, and inventory based on those key attributes.

      Now, let’s step back and admit that this book can’t possibly represent all the complexities of a real-life business environment and a real-life business system. For the purposes of this educational environment, we built a “straw man” of a company, with a simplified straw man of the data set. This is the classroom version of business analytics. Real life is infinitely more complex and demanding.

      The methods and techniques described here, however, are very much real. Understanding and applying these techniques to your real-life environment will enable you and your team to develop powerful analytic solutions to your real-life business challenges.

      Chapter 2

      Why Use Qlik for Data Discovery and Analytics?

      This chapter gives a short version of the evolution of business intelligence, and how Qlik’s disruptive entry into the market has impacted not only the technology that businesses use, but how they actually use data and analytics.

      You’ll look at how Qlik’s products facilitate data discovery– a more realistic and natural approach to data analysis than the somewhat outdated notion of business intelligence. And finally, you’ll learn about both of Qlik’s products, QlikView and Qlik Sense.

      The Evolution of BI

      Software providing business intelligence (BI for short) has been around for several decades, but was affordable only to very large enterprises. And while the technology was expensive and labor-intensive, BI systems mostly delivered an underwhelming product: static reports. However, in recent years, fluid changes in economic conditions require that businesses adapt quickly to stay competitive. No longer satisfied with static reports and analysis, businesses increasingly demand more flexibility and insight from BI systems. The success of products like QlikView highlights the fading value of the static reporting system. Why? To fully appreciate the revolutionary change brought by QlikView to the BI market, it’s helpful to review where things started.

      This story begins with a description of traditional business intelligence.

      Traditional Business Intelligence (OLAP)

      The term BI describes a system of tools and processes that transform transactional data into meaningful or actionable information for the business. Traditional BI systems are typically proprietary stacks consisting of specialized databases, scripting languages, and report writers – all for the

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