Almost everyone uses BI and analytics, whether simply for performance reporting or predicting future strategy. As organizations extend their abilities, key considerations should include ease of use, functionality, and scalability. These factors, together with an understanding of the benefits of BI and advanced analytics, play major roles in selecting the right solution.
Where Are You and Where Do You Want to Go?
As a first step, evaluate where you are on the analytics curve. Are you using backward looking BI to diagnose past performance, predictive analytics to forecast future performance, or planning advanced analytics such as prescriptive analytics to determine the organization's future? Key questions include:
- Are you ready to take the next step?
- Do you have a clear strategy of where you want to go?
- Have you the necessary commitment to see it through?
Once your organization understands what it wants, you can move onto the next phase. This will consist of determining those features of BI and advanced analytics that are important and essential for achieving these goals, and which features are irrelevant.
Ease of Use
According to research by The Aberdeen Group, the most important factor behind BI and analytics success is ease-of-use. This research shows that high ease-of-use:
- Significantly increases revenue growth
- Results in greater confidence in data
- Highly motivates employees to use BI and advanced analytical tools
This finding is consistent with Gartner's view that ease of use is the most important criterion, even more important than functionality.
For business users this means the ability to get results quickly, the capability to dig down into data, easy collaboration, and intuitive functionality. From the IT perspective ease-of-use includes simple deployment, an ability to access disparate data sources, scalability, intuitive user interfaces, and automated reporting and processing.
Functionality and Performance
Functionality comes a close second to ease-of-use. The degree of functionality needed is closely related to the level of BI or advanced analytics, such as:
- Descriptive analytics— Use of standardized and Ad Hoc BI reports that detail historical performance
- Diagnostic analytics— User-friendly BI solutions that determine reasons for historical performance
- Predictive analytics — Advanced analytics tools that predict demand, volumes, and prices
- Prescriptive analytics— Advanced analytics simulation software that emulates actual performance used to determine optimal business solutions
The level of functionality needs to be a good fit for your business and its future growth. Key factors include: analytical capabilities such as suggestive and predictive intelligence; visualization, integration with statistical programming languages, and the capability to build complex models that replicate your business.
The success of BI and analytics depends upon accessing and interpreting data. Thanks to its exponential growth, no shortage of data exists. However, much of these data are unstructured and fast-moving. Social media is one example of unconventional and unstructured data. Other examples include Google analytics, CRM retail data, and the Internet of Things (IoT).
Solutions must access these data streams, manage, combine, and interpret data to support business intelligence and advanced analytics.
Nothing frustrates BI or advanced analytics users more than relying on IT or data scientists to make minor changes and iterations. While IT support for analytics is essential — especially those that are predictive and prescriptive — a feature must be available for users to interrogate, iterate, and analyze data themselves. User autonomy means greater likelihood that employees will make effective use of BI and advanced analytics rather than ignore it.
BI and Advanced Analytics Platforms
Various platform solutions are available including cloud-based packages, on-premise solutions, and even simple desktop applications. The best decision is closely related to the level of analytics you intend to perform and your organization's IT and data science capabilities.
- Desktop, on-premise, and cloud BI applications — Self-service, backward-looking reporting solutions that analyze past performance but don't have advanced analytical capabilities
- On-premise advanced analytics — Self-hosted and developed solutions are expensive and entail a long-term commitment; they are very capable but may be inflexible
- Cloud-based advanced analytics platforms— Relatively easy to set up with vendor support, are capable, flexible, and allow you to get up and running quickly; they don't depend on in-house IT skills
Scalability often receives insufficient attention. Initially, primary concerns include processing capability and the ability to support users. However, as your ability grows and more employees get involved, two additional challenges arise. First is the requirement to train and support less sophisticated users. Second is an ability to handle increased data volumes and connect to different data sources.
Total Cost of Ownership
The total ownership cost of BI and advanced analytics solutions needs to take into account:
- Initial license costs
- Configuration costs
- Model design and validation
- Ongoing model development
- Support costs
These costs can be mitigated in various ways. Cloud-based vendor solutions are cheaper than on-premise solutions. Nonetheless, evidence shows that basing the investment decision on the cheapest solution often leads to lower overall business benefits.
Specifying BI and Analytics Requirements
Before launching your BI or analytics program, bring everyone on board, evaluate what you want to achieve, and establish how to proceed. Key steps include:
- Involve stakeholders — Ensure that all departments and key individuals are represented
- Establish where you are — Assess the organization's maturity level. Determine if you are seeking to understand and analyze organizational performance (BI) or whether you are looking for an advanced analytics solution to predict and determine the organizations future
- Develop a clear strategy — Clarify the objectives of the program with particular emphasis on realistic and clear goals
- Understand your capabilities — Evaluate your in-house capabilities; do you need to recruit specialists or will you use a vendor's skills?
- Features — Identify those features that are necessary to achieve your goals
- Decide who is going to do the work — Establish a project team
- Plan for growth — Although you may initially target certain clear-cut goals, you will likely identify new opportunities, so ensure your BI or analytics solution allows for growth
If you set clear, realistic goals, appoint a strong team, carefully select your vendor, and properly capitalize the project, you will achieve real and tangible business benefits.