Practical training, executive buy-in key to BI user Adoption

During any business intelligence (BI) deployment, organizations focus on the technical details – for example, determining the number of servers needed to support the system, choosing the data sources to be integrated, and deciding how often to refresh the data warehouse.

But in a BI deployment aimed at non-power users, addressing cultural barriers to ensure that the system is actually adopted throughout the enterprise is often just as important as mastering the technical specifications. Giving short shrift to these non-technical concerns could result in a BI manager's worst nightmare – a successfully installed, complex and expensive BI system that no one uses.

While power users, like business analysts, need little incentive to adopt BI technology, more casual BI users, such as marketing and sales associates and line-of-business managers, are a different story.

For adoption to truly take off among these users, it is important for IT and BI staff to educate them on how the technology will help them achieve personal and departmental business goals. Less important to these users are the BI system's various eye-catching features that might impress a more sophisticated user.

If a salesperson has a goal to find a certain number of new customers in a quarter, for example, the BI staff should show him or her how the new report or dashboard will help achieve that goal, rather than giving a lecture on how many different views of the data are available.

The best way to sell corporate executives, and ultimately casual users, on BI is "by realworld war-gaming and simulations, which can provoke seminal 'a-ha' moments".

"[That is] the best and maybe the only way to demonstrate the merits of real business intelligence."

At the Canadian newspaper, executives were having trouble understanding circulation reports. The data just "didn't mean anything to them,". Recognizing the importance of executive buy-in to maintain BI funding and to encourage wider adoption of the technology.

But whether it's focusing on practical training, facilitating communication, or getting executives to lead by example, the IT and BI staffs to remember that promoting end-user adoption of BI systems is an ongoing process, and not an easy one at that.

Remember: "It's not going to be done in one day or two days”, "It's hard."

10 Mistakes to Avoid in a Business Intelligence Delivery (Part 2/ 5)

Mistake #3: Assuming service provider companies own everything about the successful delivery of the project.

This is yet another critical factor for a successful BI delivery. A service provider who has signed a contract to put the BI project into production definitely has ownership on the delivery. That being said, the delivery cannot be a success without active participation from the client and end users having in each stage and phase of the entire lifecycle. Service providers are specialized consultants who can give you options and best practices, much like a professional home decorator consultant. Because it's your home, you will have to give the consultant your input and exact specifications. If this does not happen, then the decorator will decorate the home according to his assumptions of your likes and dislikes, which you may or may not approve of. And if this happens at the last minute, then not only will you end up paying for the work that has already been done, but you will also invest more time and money on rework. Without active and adequate client involvement at every phase, no BI delivery can ever have an assured success.

 
 

Mistake #4: Bringing in a solution architect halfway into the project and assuming that he/she is going to magically fulfill all the deficiencies.

This is the most common scenario one sees in most of the BI projects. When things are not happening the way they should, the management thinks the immediate remedy is to get a solution architect. What one has to understand is that a solution architect cannot just walk in and wield a magic wand to set things right. The  solution architect s experience will determine how soon he/she can start delivering the value-adds. Also, the time at which you bring in the solution architect is a driving factor for success. Often when it comes to BI architecture, business users are from Mars and IT people are from Venus. To get them to a common platform is in itself a premium skill for a solution architect.

Every BI delivery must have a solution architect with expertise and wide skills in DW and BI. This is vital, as they bring a wealth of knowledge from reference architectures and similar implementations with them. This ready-recon eventually reduces the cost and time to implement technology solutions.

The best time to start their involvement is from the analysis stage itself. If not then, do it at least before you spend a large amount of time exploring technology options and assessing the appropriate solutions. Carefully set expectations of the value a solution architect would deliver. If you decide to engage a solution architect when your data model is near completion and expect the architect to do magic to make a performance-tuned and efficient design, it might be overexpecting, as things would have already crossed certain stages involving a good amount of time and cost. At that stage, again the issue resolution becomes more political than technical.

SaaS BI Tools: Better Decision Making for the Rest of Us

Simple business decisions, each of which impacts a company's performance and efficiency, are made every day, at every level of an organization, by workers in every department. But conventional business intelligence (BI) tools are often not available to most decision makers and are typically designed for use only by trained business analysts. Software as a service (SaaS)–based BI tools are designed to help the millions of people in non-IT "lines of business" (LOBs) who struggle every day with the task of mining Microsoft Excel spreadsheets and other unstructured data sources when performing everyday tasks such as making sales forecasts, planning for resource utilization, or servicing customer accounts. Especially in this time of limited budgets and uncertain futures, inexpensive, easy-to-deploy SaaS BI can help companies put easy-to-use data mining and reporting tools for smart decision making into the hands of more employees and uncover the real "geniuses" of decision making hidden in every department.


Benefits of SaaS BI

BI offerings delivered via the cloud provide tremendous additional benefits of scale and efficiency,lower cost, and better consumption of cloud and local data sources, and they are changing the way businesses license, deploy, and utilize BI to support decisions at their companies. Some benefits of SaaS BI are as follows:


Access by more employees to more data. Key beneficiaries of the trend toward SaaS BI have been the millions of people in non-IT lines of business who struggle every day with the task of mining Excel spreadsheets and other unstructured data sources when performing everyday tasks such as making sales forecasts, planning for resource utilization, or servicing customer accounts. Users of LOB applications produce the production data that drives BI requirements, and the powerful BI reporting and analysis capabilities are especially impactful in the hands of the users who created the data, resulting in greater adoption and utilization. Every business can be more efficient by putting better reporting and analysis tools into the hands of the LOB and departmental employees who are the subject matter experts in their domains. SaaS BI can make their jobs easier by providing browser-based access to sophisticated but easy-to-use data mining and reporting tools and uncovering the "geniuses" of decision making hidden in every department.

Business optimization for hard times. SaaS-based analytics can help companies be more resourceful in volatile times by helping them identify cost savings, efficiencies, and opportunities for process improvement they may have otherwise "missed in the data."


Faster "time to value" for a quicker return on investment. Implementations of SaaS BI solutions can be far faster and less expensive than implementations of conventional solutions. Consider that building a traditional BI solution with a data warehouse implementation, data normalization, and data marts for data staging by query systems typically requires between 6 and18 months, sometimes longer. By contrast, SaaS BI deployments typically require 2 to 4 months, and SaaS vendors cannot book revenue until the implementation is complete — a situation in which both buyer and seller are equally incented to decrease what some vendors call "time to value."

Streamlined architecture, with zero infrastructure. Unlike on-premises BI systems, SaaSbased BI is hosted by a vendor. Users access the various modules (for example, analysis,reporting) securely via any Web browser. From a systems architecture standpoint, this method is optimal because it does not impose an ongoing computing burden on back-office production systems, and because the application is hosted by the SaaS provider, users do not need to maintain an onsite data warehouse. Users conduct their secure sessions via a Web browser, so there is no client software to install, and users are always assured of running the most recent, optimized version of the application code because SaaS applications are not "rolled out" like conventional applications; they are simply upgraded and optimized on an ongoing basis.



Ability to tap operating expense (opex) budgets versus capital expense (capex) budgets. Because SaaS solutions are licenses as subscriptions, their license cost is a monthly, predictable expense and does not require a one-time up-front payment for licenses as conventional software. Further, the ongoing support costs to run associated hardware, management, and integration tools and middleware and hire and train staff members to support on-premises applications are substantial, and nonmaintenance support costs are typically booked as capex. Because these budgets will be flat in 2010–2011, SaaS solutions give users a chance to get access to BI and analytics tools much faster, using opex funds that might reside in their LOB budgets.

Better alignment of business goals. Business units consuming IT resources sometimes feel discordance between the technology they know they need to have to produce good business outcomes and the tools their IT staff has the skills and bandwidth to deploy. But IT is typically a cost center, and its priorities don't always align with LOB requirements. SaaS-delivered BI helps business units get business done and helps align the goals of the business unit with its technology tools.

Worst Practice #1: Assuming the Average Business User Has the Know-How or Time to Use BI Tools

Too Much for Too Few
BI report design, ad hoc query, and OLAP analysis tools have hundreds, if not thousands, of features. Although the user interface is often simple, complexity is introduced from the data side. Even a simple data warehouse has hundreds of columns of data, and it’s not uncommon for more complex systems to have thousands of columns. When an end user is faced with a blank canvas, thousands of columns of data, and hundreds of accessible features, complexity is automatic. “Where do I begin?” is often the first question, shortly followed by “I don't have time for this,” or “I give up.”

The user skill pyramid is a widely discussed and generally agreed upon description of the end users in most organizations. The simple version of the pyramid shown below demonstrates that 90 percent of the users within most organizations fit into the class of users known as non-technical business users, which means that only 10 percent of users are advanced enough to use a BI tool.


What may not be obvious from the pyramid is that most executives and managers, often the primary strategic decision-makers, are in the lower portion of the pyramid – that is the non-technical users.


It’s a Matter of Time
In some instances executives and managers are technical enough to use a BI tool, but they don’t have the time to work with a BI tool and navigate a data warehouse to produce the information they need. Most people need a faster, easier way to get the information they need than that provided by a BI tool.


BI Go-To Guys and Multiple Versions of the Truth
In some cases, moderately successful deployments of BI tools are found in individual departments. Usually that means that each department has identified and relies on a handful of advanced users who become the tool experts, or the “BI go-to guys.” These users employ the BI tool on the behalf of others, and create and distribute information for their department. In these cases, another issue is brought to the surface – the inconsistency of the answers generated by more than one
advanced user, also known as multiple versions of the truth.

Multiple versions of the truth result when two or more people apply different query methods and functions, and arrive at different conclusions. The challenge is that it’s difficult to know which, if any, conclusion is correct.

The tool-based efforts of advanced BI users do not go through the same rigorous quality testing of an IT department. Their work within a tool is typically not auditable. When this occurs, the validity of the information system, the BI tool, and the data warehouse are all brought into question. Valid or not, many companies have more confidence in operational reports generated, and tested by IT professionals. Many become skeptical of pure ad hoc information created with a BI tool because of the potential for variations and inconsistencies.

The Solution
Organizations need BI solutions that are easy to use for the entire user population, especially those in the bottom portion of the usability pyramid. In addition, they need a solution that mitigates multiple versions of the truth by providing access to a common source of enterprise information and standardized report generation methods. A BI platform is the answer to all of these requirements.

A BI platform leverages BI tools along with other technologies, including databases, data integration, and portals to provide an end-to-end solution for a defined business problem or set of business problems that can be termed a BI application. While BI platforms are implemented by IT professionals, their end result, the BI application, is designed for business users.

Organizations have been led to believe that BI platforms are too complex for their needs. This couldn’t be further from the truth. When you consider the data integration, warehousing, and end-user training costs associated with BI tools, a BI application built on a BI platform has about the same time to market as a BI tool. And end users embrace easy-to-use BI applications as part of their day-to-day routine, which is arguably the most critical success factor of any application.
This is why BI platforms have far greater success than BI tools.

The fact is that most non-technical business users can and will access information through BI applications, which are much simpler to use than BI tools. BI applications leverage reporting technology, Web browsers, and e-mail to make information more accessible to these business users in a comfortable, easy-to-use environment.

For example, today’s parameter-driven BI applications provide users a simple Web interface to navigate to the report they want, much the same way they would find an item on eBay or a book on Amazon. BI applications allow users to easily customize the report by selecting options from pull-down menus the same way they would fill in their address and select their home state or a shipping option from a drop-down list.