Advanced analytics builds on the capabilities of business intelligence, providing additional insight and clarification on the resulting data. It identifies the “something more” and shows how to capitalize on it.

In order to discuss business intelligence intelligently, it is important to identify the key components that make up its DNA. Any technical dictionary will tell you that the term business intelligence represents a set of tools and systems that play a key role in planning. The technology can access, gather, compile and analyze data surrounding company operations, all of which are helpful tools for companies looking to make better business decisions.

Now that we’ve considered what BI entails, we must now delve into a less familiar term and address the question of what advanced analytics is. According to a 2008 IDC report, advanced analytics software includes data mining and statistical software. “It uses technologies such as neural networks, rule induction and clustering among others to discover relationships in data and to make predictions that are hidden, not apparent or too complex to be extracted using query, reporting and multidimensional analysis software.” 

Advanced analytics can be used to address complex planning problems and solve difficult business challenges - many of which would otherwise be considered impossible using spreadsheets and similar solutions - which bring true intelligence into the equation.

In other words, advanced analytics is about applying techniques for analyzing data to identify an opportunity, solve a problem or predict a future outcome.
These high-end analytical techniques extend the capabilities of business intelligence, allowing us to tap into rich data sources to spot trends about customers, products, markets or suppliers, manage risk or formulate strategic initiatives in order to forecast and model outcomes. These predictive insights can, in turn, provide companies with the direction needed to make profit-maximizing, cost-saving decisions.

What does this mean for businesses? Advanced analytics lets you leverage your investment in people, contracts, equipment and facilities. It also lets you identify strategies that ensure profitability by looking beyond basic knowledge for actual intelligence.  It means exploring the “how, why and when,” not just the “what” of collected data and committing to sophisticated modeling that generates new insights, rather than using data to support a pre-existing assumption.

Focused “Niche” Analytics are Even More Important in Today’s Economy

These tools can be especially valuable in times of economic downturn when advanced analytics’ predictive capabilities can help businesses foresee risks and determine best products, spot the best customers and best cross-marketing opportunities or avoid missing opportunities by being the first out of the blocks.
In fact, in a recent article, InfoWorld consulted a range of analysts and CIOs to arrive at a consensus on five technology areas where companies should continue to invest in despite the recession.1  Included in these five was niche analytics. 

Ensuring Profitability

Once you have invested in the best people and tools to accomplish your goals, identify the strategies - or best practices - to ensure profitability. And keep in mind that your relative success in using advanced analytics is determined by your ability to act on the recommendations provided. 

Start with the end game. “Here’s what I want. How do I accomplish it?” Rather than identifying what you do currently and then playing with known strategies until you reach an acceptable outcome, turn the problem around. Define the outcome you are looking for, and ask the software to give you the best strategy to accomplish it. For example, use advanced analytics to explore, “What is the best strategy to maximize the net present value (NPV) of my asset?” It may give you a different answer than you expected, but you will get the best answer.

Incorporate business intelligence data. Make the most of your IT investment by gathering and leveraging all the data and technology in which you already have invested. It can be on a variety of platforms and from multiple sources, including Teradata, Oracle, DB2 and SQL Server-based data warehousing environments.

Open your mind to the possible. Identifying only strategies that you already have in mind based on your BI and experience is limiting. Use advanced analytics technology to explore completely off-the-chart what-if scenarios. Examples might be: What if I didn’t repair equipment in the worst condition first? How can we ensure that the total value of our civil infrastructure is not decreasing over time? How do compliance requirements impact our planning?

Put it all in the mix and break some barriers. Consider all options and explore multiple what-if scenarios. Expand the scope of your analysis to include all data and related factors that may be of relevance. It takes sophisticated tools, algorithms and complex modeling capabilities that are not found in less advanced BI software to accomplish this, but you’ll get a deeper, more insightful analysis.

Consider constraints. Take steps to understand and identify all the constraints (budget, timing, regulations and so on) under which you are operating. Constraints may eliminate some options and reduce your overall results, but including them will ensure you get the most realistic scope. Additionally, a proper analysis can help you see how each of the constraints affects the bottom line, allowing you to relax or tighten them if appropriate.

Collaborate. Use collaborative technology to ensure that key people - even those without analytical knowledge - have opportunities to offer their expertise and feedback. 

Leverage Your Resources

You have spent thousands even millions on information technology - data warehousing, data collection and BI software, including graphs, reports and charts - but what are you getting for it and how much more could you get if you add advanced analytics to your toolkit?  Business intelligence is limited to the realm of what we know; advanced analytics ventures into what could be.

The opportunity to maximize profitability and improve efficiencies through the use of advanced analytics are virtually limitless and are applied to any industry or resource, from tracts of land, roads and bridges, and carbon emissions credits to manufactured items.

A good example comes from the province of New Brunswick and the recent overhaul of its entire asset management program for civil infrastructure.  Through advanced analytics, the New Brunswick Department of Transportation (NBDoT) found that the most cost-effective way to manage its assets was to use a least-lifecycle cost approach where previously, the accepted way to manage its 18,000 kilometers of roads, 2,900 bridges and various ferry crossings was to fix the worst first. The result had been a slowly deteriorating infrastructure and steadily increasing maintenance costs. The NBDoT applied advanced analytics software to spot efficiency trends and showed the most profitable alternative through its trade-off analyses and scenario modeling capabilities.

In the end, the system offered an objective and strategic approach to long-term investment planning and program development. It identified the right time and the right way to make improvements to the province's highway infrastructure at the lowest cost to taxpayers.

The more information you can include in your analysis, the more you can mitigate risk and ensure a defendable result. 

This is perhaps best illustrated in a recent land valuation case in which the battle to decide the final outcome of Pacific Lumber Co.’s (PALCO) bankruptcy confirmation proceedings was determined by Judge Richard Schmidt who confirmed the reorganization plan for PALCO by Mendocino Redwood Co. and PALCO creditor Marathon Structured Finance Fund. The opinion that won Schmidt’s approval was an advanced analytics approach that applied LP techniques to consider a wider range of alternatives for a more defendable result.

It all boils down to this: advanced analytics take users to levels beyond those accessible through BI alone.

Whether aimed at strategic or operational issues, advanced analytic software can dramatically improve the consistency and quality of decision-making throughout an organization because it facilitates decisions that are based on quantified costs, benefits and risks, rather than on pure instinct. At the same time, it weighs the opinions of experts against established priorities to allow for the genius of experience, and it accelerates the decision-making process, allowing managers to focus their time and attention on more pressing issues. Depending on the actions taken, organizations either save money or make more money.

Advanced analytics builds on BI, causing some users to say, “Wow, I didn’t see that before,” and to take actions they might never have considered for the highest possible profitability.

Reference:

  1. Tom Sullivan. "Five top spending priorities for hard times," InfoWorld. November 19, 2008.

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