Corporations are bombarded with decisions regarding what BI solution will best meet their business requirements and give them the competitive edge they need. Some of the questions decision makers face include how to differentiate between various vendors and their solutions, what type of deployment to select, what type of BI to implement, which BI solution best meets their needs etc.
An organization’s level of maturity regarding its BI use may also reflect the type of expansion that occurs within their BI environment. For instance, if a business has been using traditional BI for the past 5 years, they may want to move to a more proactive approach regarding their use of analytics. Organizations new to business intelligence, however, may want to immediately embrace the benefits of having both historical and real-time data and not necessarily start with the former and progress to the latter.
How do organizations know which type of solutions they should choose? How do operational and embedded BI differ from traditional business intelligence and what are the benefits? Part 1 of this series explores the structure of business intelligence solutions and some of the business implications to be considered with each. Part 2 discusses the technical considerations associated with a BI deployment, the types of deployments available, and how each can meet the requirements of organizations evaluating BI.
The general structure of traditional BI involves the capturing and storing of a subset of operational data in a data warehouse to be able to analyze, report, and identify trends without affecting operations. In the past, information was collected weekly, monthly, yearly, etc., with little opportunity to use BI for anything other than longer-term planning and trend analysis.
As data warehousing becomes more robust, corporations can pull data daily and intra-daily, thereby shifting from historical to immediate forms of analysis. Couple this with the ability to develop what-if analyses using scenarios to forecast future performance and BI becomes a tool to plan based on past results, to increase efficiencies using intra-day transactions, and to manage the company’s performance. This occurs by combining both historical and immediate data with forward-looking synopses of the organization and external factors that may affect various activities such as sales, inventory, etc.
Taking this even one step further, corporations can use their historical trends-based data to identify what has been happening within the market. Has pricing been affected by newer product releases, diversity in the market, or competition? After the identification of factors that may be contributing to changes in performance, the organization can use them to develop what-if scenarios to gain a better perspective on what may contribute to future successes. With this new knowledge, organizations can develop the necessary steps to attain future success and plan according to trends that have occurred in the past with the additional knowledge of how several scenarios may play out.
Now that organizations can deploy BI in different ways to meet various business and performance requirements, and because of the fact that organizations want to deploy BI on a wider scale throughout the organization, there has been a transition - from using BI as a separate application to embedding BI within an organization’s business processes.
Continuous process improvements are a focus of any successful corporation. To be a leader in the industry it is essential to have a commitment to constant improvements, whether in the call center, supply chain, or within finance and accounting. With operational BI, the focus is on the use of business intelligence solutions to help drive process improvements. An example for manufacturers would be capturing the status of products while on the assembly line to identify and rectify any potential quality control issues before they occur.
In general, businesses using data captured multiple times daily are subscribing to operational BI. By using regular intervals of data updates to help drive more immediate decision making and by embedding business intelligence solutions within actual use of operational systems, organizations have access to up-to-date analytics and are able to identify successes and weaknesses in near real-time adjusting their go-to-market strategies. This differs from the traditional approach that looks at static data to plan strategically. With a current view of what is happening within the organization, decision makers can more easily react to day-to-day activities as they occur.
This approach however, does not work for all organizations. Considerations such as IT infrastructure need to be addressed based on high quantities of data capture and the increase in frequency. This will be addressed in Part 2.
Choosing a BI solution is no simple task. Aside from the plethora of solutions available, the implementation of BI does not offer a one-stop solution to an organization’s business pains. To accomplish BI success, organizations should identify their business pains and align their solutions to these issues. By matching the technical requirements to business requirements the overall BI environment is more likely to deliver the desired results.
Some general considerations are:
- What problem the organization is trying to solve. The identification of sales trends by region over time differs from increasing customer retention or identifying the reasons for higher rates of customer churn. Alternatively, financial planning and budgeting may require different application use than embedded analytics to increase efficiencies within operations.
- How often data is required. If weekly data is required for decision-making, pulling data more often may not be of any added benefit. Consequently, not enough information also increases the likelihood of gaps within the analysis process.
- How to roll out the solution. Aside from how the tool will be used, the identification of who will be using BI within the organization may require diverse tools to be deployed. For example, business analysts may want access to OLAP cubes and the ability to drill through to access multiple data sources, whereas a manager may want a quick view of how products and employees are performing.
Part 2 of this article will help corporations identify what solutions and deployment methods are available to help them make their software selection less complicated.
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