Plenty has been written on empowering users with self-service business intelligence, but the topic is rarely viewed through the lens of small to midsized businesses grappling with limited IT resources and small budgets. Paradoxically, small and midsized businesses often have more to gain in terms of bottom-line impact of BI than larger Fortune 500 companies do.

The rapid growth of visual analysis and data discovery BI tools is just the latest chapter in the evolution of business intelligence software from IT-centric platforms to self-service products, and it is a trend that has the potential to make a great impact on smaller organizations. While many small and midsized businesses scoff at the idea of implementing a BI solution, BI does not have to be big and scary. Many solutions today require no IT footprint and can be easily piloted in just one area of your organization. It just takes careful planning to introduce and implement BI properly.

Let’s explore five ways you can bring self-service BI into your organization in an easy, cost-effective fashion.

1. Spreadsheets Can Show You Where BI will Be Most Successful

Why is the humble spreadsheet still – by far – the most-used self-service BI tool on the planet? It’s because spreadsheets give users an extraordinary amount of control over the design and construction of reports, all from a convenient point-and-click interface. Once users gain “advanced” skills, they can use macros to automate routine processing. Pivot tables, filters, what-if analysis and a rich collection of statistical functions provide advanced users with a non-trivial amount of analytical fire power. What’s not to like?

But the problems with spreadsheets are well-documented. Spreadsheets containing confidential data are often emailed around among employees, representing a potential data security breach. Spreadsheet formula syntax is not intuitive, making it difficult to find and debug errors. Macros, pivot tables and links to other spreadsheets are fragile and easily broken. Spreadsheet data can be typed over and changed so it is subject to errors. In the end, basing important business decisions on spreadsheet analysis can be risky. Many BI practitioners consider spreadsheets to be “the enemy.”

But if you are looking for a good place within your organization to start with BI, look for the people and departments that exhibit heavy use of spreadsheets. These are your “data champions”: employees and departments who are hungry for data analysis and visualization solutions and who are already using spreadsheets as a proxy for self-service reporting. They probably already know the source systems where the raw data exists, the schedule by which it gets updated and the format of the reports or dashboards they need to do their jobs better. They are the ideal first users of a BI solution.

Business intelligence is useful for these data champions because it provides more secure and reliable business decision support. The trick is that the BI solution must be intuitive and simple to use, like a spreadsheet. If more self-service BI products were as easy to learn and use as spreadsheets, BI adoption rates would be far higher, especially in smaller organizations that lack in-house training and support staff.

2. Demystify BI with Purpose-Built Applications

In any organization, there are departments with cultural and practical barriers to adopting new tools. For example, finance takes great pride in its spreadsheet ninja skills and will naturally fall back to this tool rather than deploy a new one. And financial software systems are so entrenched in the daily operation of a business that introducing new systems or replacing old ones can seem as difficult as performing open-heart surgery on a marathoner in the middle of a race.

For organizations in which BI implementation seems especially daunting, deploying a purpose-built BI application can provide an easier entry into the technology because it can provide immediate benefits to one area of the business without disrupting existing systems. Once departmental users view the new tool as a productivity enhancer – rather than a threat or disruption – adoption rates tend to rise dramatically.

It is wise to look for a well-thought-out interface and focused functional scope. Noted social psychologist Roy Baumeister coined the term “decision fatigue,” which humans experience when challenged to make too many decisions in a fast-paced environment. Interestingly, people experience this condition regardless of the magnitude of a particular decision. Whether or not to drill down into a particular dashboard metric can, surprisingly, raise the same level of mental stress as making a major personal financial decision. Bottom line: The fewer decisions our overtaxed brains have to make to complete a task, the more likely we are to successfully complete our assigned task.

Successful, purpose-built applications can bring the benefits of self-service BI to the end user by presenting fewer menu options, a more problem/resolution-focused interface and a familiarity of the subject matter for users. Effective self-service BI is not guaranteed from any particular tool, application or platform. When BI providers pay attention to the details of application design, it pays dividends in terms of users’ productivity increases and clearer decision-making.

3. Just Say “No” to the Data Warehouse

This is an admittedly provocative topic, and I expect plenty of readers to express opinions to the contrary. But too many small and midsized organizations have denied themselves the benefits of BI because conventional wisdom says that building a data warehouse is a mandatory first step. That premise has been, and will continue to be, demonstrably false.

Many excellent BI tools have flexible ETL capabilities that offer an alternative to building a data warehouse. Foregoing the data warehouse can shave time, cost and complexity off the implementation, while still delivering BI results.

With exponentially growing volumes of unstructured and streaming data making the data warehouse value proposition increasingly questionable, it’s time to move beyond this sacred cow. A truly versatile BI platform should be able to create BI-optimized data structures regardless of whether a data warehouse exists or not.

4. Broaden Your BI Mind

Beyond BI lies information delivery. Traditional BI delivers numbers, dashboards and reports, but does not tell users what to do with this data. Information delivery expands BI’s utility by including not just data, but other content needed to convert insight into action. These can include context-relevant documents, presentations, videos and alerts.

Mobile BI is an excellent example that demonstrates this new paradigm. A BI-based sales enablement tool can provide a field rep with metrics on inventory, stock-outs, promotions and incentives as well as sales scripts, sell sheets, product videos and other collateral that specifically target a particular class of customers. According to the “Wisdom of Crowds Mobile Computing/Mobile Business Intelligence Market Study,” published by Dresner Advisory Services LLC, three times as many small organizations indicated that mobile BI is a critically important function to the business compared to large organizations. Howard Dresner, lead researcher, president and founder of the Nashua, N.H.-based analyst firm, said, “When you’re a small organization, you have to garner as many competitive advantages as you can.”

5. Cloud and SaaS Keep BI Easy to Support and Affordable

Cloud and SaaS-based deployment options have arguably made self-service BI an affordable reality for more small and midsized organizations than any other innovation. A monthly subscription and reduced demand on internal IT resources can lower entry barriers for decision-makers who realize they need BI to remain competitive yet balk at the price of implementation. As the BI user base grows, cloud or SaaS deployments scale up, with all of the heavy lifting left to the BI vendor and its designated SaaS infrastructure provider.

With a SaaS-based BI deployment, customers can access the functionality found in a vendor’s on-premise solution. The co-location facility hosting the vendor’s physical servers will employ  security, backup and failover practices and allow high availability and 24x7x365 access. The servers at the co-location facility can be configured to optimize each customer’s performance and storage needs. For customers concerned about sensitive data, a SaaS-based vendor should be able to guarantee the physical location of their data. Customer requirements such as availability, throughput, concurrent users and anticipated data volumes should be explicitly addressed in the vendor’s SLA.

Conclusion

While challenges remain, they are continually being addressed by BI vendors. Self-service BI can quickly be implemented in small and midsized business environments, and it provides an easy entry point without the time or financial commitments required for a large-scale BI implementation.

The confluence of information delivery, convenient cloud and SaaS-based deployment options and purpose-built applications have overcome significant obstacles that seemed daunting only a few years ago. Best practices are equally important, though small and midsized companies use a slightly different playbook than their much larger corporate brethren that deploy enterprise BI solutions. The trends outlined here demonstrate that self-service BI is a reality for all who want the benefits it offers throughout their organizations, regardless of the organization’s size