Is Your Business Analytics Driving Profitability?

By Bill Cabiró

It should be no surprise that data-driven decision making works better than relying on managers’ intuition.

Research clearly shows that analytics oriented organizations outperform their peers but making sense of the data becomes an increasingly challenging task as corporate data continues to grow at a 40% yearly rate as a result of the rapidly declining cost of computer memory.

An IBM CFO study shows that analytics-driven organizations had 33% more revenue growth, 12 times the earnings (before interest, tax, depreciation, and amortization) and 32 percent more return on capital invested.

This is where Business Analytics (BA) becomes crucial in providing data management, integration, multi-dimensional analysis, visual discovery, data mining and statistical methods to improve productivity in nearly every business function.

Business Analytics is an all-encompassing name for a new discipline resulting from the integration of Business Intelligence and Predictive Analytics.  BA not only includes the classic Business Intelligence functions of reporting what happened, drill-down to how it happened, find out the cause of why it happened and alert management as soon key metrics move in the wrong direction.

In addition, BA includes a highly sophisticated subject called Predictive Analytics that can be defined as Advanced Computational Statistics.  It uses large cleansed historical data sets to look forward.  Specifically, Predictive Analytics finds patterns in the data to forecast what has a high probability to happen in the future.

BA application includes operational intelligence, strategic and competitive analytics, customer acquisition and retention, risk management, fraud detection and demand driven forecasting among others.

According to Tom Davenport, “Companies that invest heavily in advanced analytical capabilities outperform the S&P 500 on average by 64%”.

Having a clear view of the profitable customers, products, regions and market segments is fundamental to understand the causes and expand upon the successes.  Equally important is to find those customers, brands, markets, segments and competitors responsible for draining cash and quickly stop the bleeding.

 

In their book, “Competing on Analytics – The Science of Winning”, Thomas Davenport and Jeanne Harris define decision support, business intelligence, data mining and predictive analytics and put all these concepts well in perspective.

The book shows the five stages of analytical competency and gives plenty of examples of companies that are successful in both the internal and external implementation.

Stage 1: Analytically Impaired – Lack of analytical skill or executive interest.

Stage 2: Localized Analytics – Uncoordinated activities or silos.

Stage 3: Analytical Aspirations – Good intentions with slow progress.

Stage 4: Analytical Companies – Widely use analytics internally.

Stage 5: Analytical Competitors – Use analytics as a competitive advantage.

Business Analytics is a fundamental discipline to find the root cause of issues and probable outcomes.  Taking prompt corrective actions tends to satisfy customers’ needs faster and better than the competition providing the company a competitive advantage regardless of how small the business is.

Up until now, BA has been the exclusive domain of large companies that were able to afford the investment.  Companies like Bank of America, Progressive Insurance, Amazon, Google, Walmart, Capital One and Google were pioneers in this area.

This is no longer the case.  Today, there are many choices of analytic applications, either on premise or in the cloud, that are powerful, user friendly and very inexpensive.  Mainly designed for business users, they include interactive data discovery, self-serve visual analytics  and open source statistical tools that require minimal IT involvement, making them ideal to transform small companies into analytic competitors.

Regardless of the company size, the strategic use of Business Intelligence and Predictive Analytics can have major impact on the growth and profitability of the company.

Unfortunately, today many small companies are still unclear about the value analytics can bring to their business. Others, while aware of the value may not be fully prepared to effectively utilize it.  So what steps can a small business take to begin effectively using analytics?

A starting point would be to determine where your business stands regarding the capability to use data and analytics. This can be done in less than10 minutes using our free assessment tool for small businesses.

Based on your responses to several questions this tool will grade your company’s capability level in the analytical landscape.  After you finish the grader, you may want to download the Suggested Action Plan Report to help you take the next step in your company’s Business Analytics journey.

  

Can Small Companies Justify Investing in Business Analytics?

By Bill Cabiró

Even in the case of very small businesses, a strategically deployed Business Intelligence solution can have a major impact on the growth and profitability of the company.

Having a clear view of the profitable customers, products, regions and market segments is fundamental to understand the causes and expand upon the successes.

Equally important is to find those customers, brands, markets, segments and competitors responsible for draining cash to quickly stop the bleeding.

Should we treat all customers equally? 

If you say yes, I’d suggest reading “Angel Customers & Demon Customers” by Larry Selden & Geoffrey Colvin.

This is because in a company that has more than thirty customers, the Pareto Principle will be evident.  Looking inside the Pareto’s famous 80/20 rule not only one can find that the top 20% of products contributes 80% of total sales.  

We can also find that the top five percent of the customers generates close to 50% of the profits while the bottom 50% of the customers generates only 5% of the total profit.  Even worse, the bottom 40% usually does not generate any profit at all!

Many companies have a hard time identifying which customers belong to each group.  The good news is that the strategic use of Business Analytics provides these seemingly difficult answers instantly.

Regardless of the business situation management should be able to ask critical performance questions and find -first hand- clear answers at the speed of thought without interruptions or the involvement of analysts:

• Is revenue growing profitably? Where? How and Why?
• Are we paying sales reps commissions for bringing in unprofitable tonnage?
• Can we quickly tell whether the growth trend is just over last month, last quarter, same quarter last year or this year to date?
• How about the profit growth of the last 52 weeks compared to the previous 52 weeks?  Is it really growing?
• Is our growth accelerating or decelerating?  How much?
• How is our profit growth versus budget or business plan? Where are we failing to meet our objectives?  Why?
• Which competitors are threatening our business?
• In what regions and market segments can we maximize our growth?

A modern Business Intelligence solution is fundamental to find answers to the seven layers of WHY's in order to get to the root cause of issues.  Being able to understand and correct these issues faster than the competition provides the company a competitive advantage regardless of how small the business is.

In the past deploying a Business Intelligence solution was not affordable by small companies, not only due to the high licensing cost of the software but also because of both the internal and external resources necessary to set it-up and provide maintenance.

This is no longer the case.  Today, there are many choices of analytic applications, either on premise or in the cloud, that are powerful, user friendly and very inexpensive.  

Designed for business users, they include interactive data discovery and self-serve visual analytics that require minimal IT involvement, making them ideal to bring small companies to the forefront of the 21st century technology to become true analytic competitors.

References:

1)    Angel Customer & Demon Customers by Larry Selden & Geoffrey Colvin
2)    The 80/20 Principle by Richard Koch
3)    Competing on Analytics y by Thomas H. Davenport, Jeanne G. Harris
4)    Strategic Knowledge IQ Test

Image: GraphicStock

What Is Business Intelligence 3.0?

Interactive Visual Analytics represents what Gartner Research calls the consumerization of Business Intelligence.  It’s a good example of a disruptive innovation or, as Qlik’s Donald Farmer calls it, a market changer.

According to Tableau Software “visual analysis is not a graphical depiction of data. Virtually any software application can produce a chart, gauge or dashboard. Visual analytics offers something much more profound. Visual analytics is the process of analytical reasoning facilitated by interactive visual interfaces”

This new generation of BI tools is so intuitive to the regular user that little or no training is necessary to explore data. This is a great feature since, according to Gartner, BI users do not want to read manuals. They demand intuitive BI interfaces, in line with the internet experience they are accustomed to, like Google searches or smart phone apps.

The current low BI utilization rate of about 5% does not provide many companies an acceptable return on their Business Intelligence investment.  The new user-friendly and intuitive visual analytic tools are helping companies exploit the treasure of business trends, patterns and opportunities hidden in their oceans of data by increasing the number of employees that participate in the data discovery process. The technology enables casual users to transition into power-users and power-users into app developers in a matter of weeks.

Depending on the vendor, the new software class is known by different names: Data Discovery, Advanced Visualization, Visual Analytics, Business Discovery, Self-Serve Business Intelligence or Business Intelligence 3.0

Advanced data visualization is based on the fact that 70% of the human sensory receptors are dedicated to vision while the other four senses share the remaining 30%.  In addition, our brains are much more effective recognizing shapes trends, patterns and colors than analyzing spreadsheets or tables full of numbers. Visual data analysis principles are based on the work of Edward Tufte and Stephen Few.

The data visualization market begun to grow during the last decade as business users started purchasing these applications for departmental use, mainly without IT consent.  The reason was simple: business analysts needed the capability to analyze all sorts of data rapidly, beyond the scope of the data-warehouse.  A request that most IT organizations were not prepared to fulfill. Today as data discovery tools have become more popular and scalable IT organizations are more involved in the purchasing process. 

Today more than two dozen applications fall into this category from companies around the globe. The leading ones –Tableau and QlikView- have grown their acceptance at a very fast rate.  Ten visual applications have made it to Gartner Research's 2015Magic Quadrant for Business Intelligence and Analytics and this number will grow in the future as more BI solutions continue to add visual analysis functionality.  Gartner estimates that more than half of net new purchasing is data-discovery-driven.

"For years, data discovery vendors — such as QlikTech, Salient Management Company, Tableau Software and Tibco Spotfire — received more positive feedback than vendors offering OLAP cube and semantic-layer-based architectures.  In 2012, the market responded:

·        MicroStrategy significantly improved Visual Insight.

·        SAP launched Visual Intelligence.

·        SAS launched Visual Analytics.

·        Microsoft bolstered PowerPivot with Power View.

·        IBM launched Cognos Insight.

·        Oracle acquired Endeca.

·        Actuate acquired Quiterian".

To be clear, Self-serve BI does not mean “IT Free” as a strong IT-Business partnership is always helpful to ensure data quality through proper governance and also to maintain the proverbial single version of the truth.  Self-serve refers to the user’s ability to perform data exploration and discovery simply by clicking or tapping into interactive dashboards and reports.  All this without having to request IT to create specific data marts, build OLAP cubes or predefined reports as this would delay the data analysis process.

Also, it’s important to highlight that there are two kinds of self-serve BI user: 

1. Analytics Power Users who create visual apps from multiple data sources –both internal and external.
2. Regular Users that can fully explore the visual apps created by power users or IT.

In addition to the typical functionality of multidimensional analysis (drill-down, drill-through, roll-up, sort, group, filter and calculations) some visual tools offer “what-if” scenario analysis, data animation, integration with the statistical ”R” program and mobile capability. 

A great feature of this new generation of BI software is its data blending functionality. These applications allow connecting simultaneously to disparate types of data bases or tables, whether in a data warehouse, data-marts, spreadsheets, text files, Microsoft Access, websites and in the case of Tableau OLAP cubes.

The analytic results are instantaneous since the process takes place in-memory (RAM).  Additionally the visual interface, when used proficiently, permits to digest huge amounts of information and visualize trends and patterns in seconds.  This process enables what many call “analysis at the speed of thought”; Meaning that the answers to business questions can be found fast enough without  interrupting the “train of thought” that leads to the next layer of questions, seeking to find the root cause of issues or opportunities.

Visual Analytics packages are not replacing traditional BI in large organizations but complementing them. They provide fast analytical capabilities to more people that need to gain a competitive edge in the current fast changing market dynamics.

For small and medium size companies that haven’t yet invested in BI, Self-serve, Visual Data Discovery is a cost effective solution that can be deployed very fast.

This new generation of BI software takes descriptive analytics to a whole new level. That's the reason for the fast growth rate this $4.5 Billion market segment has experienced during last few years.

It only takes a few minutes to download the free versions most vendors offer for testing purposes.

Below: Dr. Hans Rosling’s video is a few years old but still illustrates the power of data visualization techniques that make 120,000 data-points tell a compelling story in a way that’s very easy to understand. 

Note: The original version of this article was published here by Bill Cabiró in 2011.

Image: GraphicStock