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By Peter Graves, CIO, Independent Bank. Graves has 25 plus years experience on the business side relating to commercial lending administration and on the technology side in his role as chief information officer for Independent Bank, a $2.7 billion community bank with over a 100 locations in the lower peninsula of Michigan.

Banks are getting serious about business intelligence. They have to, in order to cope with market and regulatory demands

Why is business intelligence (BI) gaining more traction these days? As a methodology to identify, extract, and analyze meaningful information from data to improve business decisions, the concept has been around for decades.

The answer is simple: Because managing revenues, expenses, and risks has never been more critical to executing banking strategies than it is today. No longer is it sufficient to wait until the monthly reports come out to see how we’re doing relative to sales, deposit, or revenue goals. Nor is it acceptable to wait for a quarterly report on credit risk to see if we are back on track or to spot emerging risk trends.

I can’t think of a more important or more pertinent topic in banking today, and one that is at the heart of information technology.

Two other factors are driving the push to get BI up and running—or running more effectively—in many organizations today.

First, earnings pressures brought on by asset quality issues over the last four years have forced banks to increase revenue opportunities and decrease expenses to build lost capital. Depending upon the older traditional methods of data mining to populate reports at monthly or quarterly intervals just does not meet the need for immediacy or real-time information.

Second, new devices such as smart-phones and tablets are providing surprisingly useful examples of what is possible combining mobility with meaningful, real-time information. New solution providers are re-engineering their BI methodologies around these mobile devices and they are getting noticed. For the first time, you can get the right information on a truly mobile device, and that is driving renewed interest in BI.


What key BI attributes are needed?
There are three things necessary for an effective BI solution: a data-integration interface, a logical/relational engine, and an interactive output/reporting toolset. Let’s look at each of these.

Integration The data-integration interface is critical to combine databases simply and efficiently. Data itself exists in many different flavors. These range from an Excel file with a few data points, in its simplest form, to complex Oracle or SAP databases with thousands of tables and characteristics that require sophisticated methods to aggregate and rationally assemble. The best BI solutions perform this integration behind the application layer to allow end users to hook into data at different levels. The ease of integration is a cornerstone to finding a solution that encourages and accommodates use by the business units. If it has to be owned and managed by IT, adoption will be limited.

Logical/Relational Data Engine Just bringing the data to one location from multiple sources is not enough. Data is worthless without the ability to align input from multiple sources in a logical way that gets to the art of solving problems and making decisions. An effective BI engine will combine and help analyze data, providing meaningful extractions, concepts, and solutions. Without that, decisions get lost in a vast sea of ambiguity. Further, being able to drill down into data from the top or from the general to the specific is important in order to isolate issues. Likewise, noticing a piece of information at the detail level and determining the extent that it might impact the total is equally important.

Output/Reporting Toolset What most people remember about a BI demonstration is the colorful output or “dashboards.” These are attractive graphic representations of data organized by areas or disciplines such as sales/revenues, risk management, costs, production, and performance metrics. The dashboards often include a unique way of alerting when something is out of norm. For instance, when revenues or expenses exceed an expected range a brightly colored flag or icon appears. The specific measurement can then be clicked on to drill down to more data or levels of data to quickly understand what is causing the anomaly. This ability to move up or down or horizontally within the data is proportional to the benefit attained, arriving at conclusions quickly and adjusting strategies in real time.

Finally, providing historical along with predictive analytics assists with spotting meaningful trends over time. This capability is as much dependent on the tool as it is on the aggregation of the data.


With so many solutions, how do you know which one is best?
There are a several factors to consider when selecting a business intelligence solution.

1. Ease of implementation is often a factor. Most organizations have a pressing need and want a solution up and running as soon as possible. Solutions designed for a particular segment of the business are often easier than those that take the enterprise approach. However, leveraging an enterprise solution spreads the life cycle management and cost of the platform over many business units.

2. The types of data to be aggregated must be considered although most of today’s solutions are capable of handling a wide range of data types on many disparate systems or applications. Data types can vary from Excel files to huge extracts of mainframe databases. Some solutions are better at hooking into the sources of data than others.

3. The skill sets of business units that will engage the solution may drive the complexity of the system. If the intent is to decentralize the usage of the BI tool (which should be the objective), finding an intuitive solution with a user friendly interface will increase adaptability and reduce training requirements.

4. Outputs/dashboards are what help drive the understanding of the information delivered. The ability to choose between multiple formats will allow business units to find the most meaningful way to present the data to those who will consume it. After all, this is what the users experience and if the dashboards are effective, adaptability is maximized.

5. Solution delivery methods are typically either in-house on the bank’s network or hosted by an application service provider. While the first typically offers the most flexibility in terms of integration and support, hosted solutions can speed implementation times and tend to be better suited for less intensive BI requirements.

6. Cost always has to be a consideration. Although new solution providers are tending to drive down the overall cost of these implementations, the old axiom tends to apply, “You get what you pay for.”


Who are the leading providers?
There are many names you might expect that have had an impact on the development of business intelligence as we know it today. Among them: Oracle, IBM, and SAP. But there are some new players as well, according to Gartner’s latest review of the subject. MicroStrategies, Qlik Tech, and Information Builders are all solidly located in the leader’s quadrant. But Microsoft has really made an impact in the last five to six years. While most of us think of MS Excel as a rudimentary business intelligence solution, Microsoft has built powerful integration capabilities into Excel and into many of their collaborative products such as SharePoint.


Beyond business intelligence
Today, problem solving is taking on more of an abstract approach, not the typical top-down, bottom-up, or horizontal methods we typically experience in information systems. This new approach—an extension of BI—is called “business discovery.” The best example of this approach is how the younger generation (millennials) tackles problem solving. They do research using internet search engines and virtual social networks to immerse themselves in data and to track down answers and solutions. The approach is abstract because one researched piece of data may lead to another in random patterns as they devour data in their quests. Collaboration is also key since the social aspect of problem solving takes on any form that brings together the right team.

Applying this same approach within the enterprise requires solutions that offer similar methods of search capabilities and collaboration between employees. Most often, these ad hoc teams evolve based on need but do not follow the traditional, functional organizational lines. The tools and the data need to be adaptive and available.

As security has become more of a challenge, access to information is more restrictive. Once access is granted to those that need it, powerful search tools must be part of the BI solution or platform. This allows those using the solution to move about the sea of data in ways that arrive at the right information.

Although business intelligence solutions have evolved significantly over the years, they have only recently started to model their solutions to embrace business discovery as a methodology. Perhaps business discovery is just around the corner for the enterprise. Until then, BI solutions are receiving renewed focus as banks must understand their business processes in real time and react accordingly. •

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