Businesses are tempted to postpone integration projects related to business intelligence or BI projects in general. Our advice is please don't. At Capitals & Squares LLC, we believe that both BI and CPM software can help companies navigate the current economic climate, and help confront the integration challenges they'll have to overcome.
BI allows organizations to get a more accurate and detailed picture of what is going on in terms of business, processes, and customers. It can do this in varying ways – using an accurate view of costs, liabilities, risks, customer buying patterns, supplier cost-effectiveness, etc. BI can bring visibility into the organization at coarse levels and help link different aspects together. Take budgets, for example. It is all too easy for organizations to think that they have more money than they do and over-commit on budgets, only to find themselves later with liabilities that they cannot afford.
Whilst rolled up financial reports from spreadsheets can show expenditure and commitments against cost center codes, it is important to be able to drill into the figures, see where they have come from and to have some context around the expenditure. The expenditure, for example, can be viewed against progress and what should be expected next, and so enable organizations to forecast and be ready for invoices that are to come. This is particularly important when organizations need to minimize outgoings and risks. It also enables them to plan savings in an informed and effective way.
Now that consumer confidence is returning, it is also important for organizations to be ready to do sales and promotion campaigns at the right time. BI can help with that. It can allow organizations to review customer behavior so that they can time special offers to get customers back before their competitors do. In this way, a Company can use Business Intelligence to optimize business and improve corporate performance, develop a full cycle of CPM right from the planning and budgeting stage through to implementing, monitoring and very importantly, improving. BI relies on data collected from other systems, so the quality of the data is very important to BI. The intelligence provided by BI has to be trusted enough to be acted upon. There are many data quality software tools that can be used to improve the quality of data that comes into the BI or CPM system. But there is more to data quality than just tools. Data quality should be built into processes so that data is correctly captured and stored, that errors are not introduced in other processes that use the data, and that the data is integrated, i.e., brought together from different systems so that the information that it provides can be compared and contrasted to provide intelligence.
As far as BI and CPM integration goes, many vendors offer their own integrated BI/CPM packages or integrate with software from third parties. Many of the leading software applications have support for standards. Some support other third-party tools or connectors to different pieces of BI/CPM software. Following the spate of acquisitions in 2007 and recent years, vendors have integrated some of the acquired products, for example, recently acquired OLAP engines, but there is still work going on in this area. It is advisable for organizations to ensure that their preferred software applications work together.
Vendors are addressing embedded BI in different ways, e.g., through SOA, operational BI or real-time BI. The latter is a different kind of BI that collects data from message queues or real-time events and builds process or event profiles to use for reference and comparisons. Deviations from the norm can then be spotted in real time and alerts generated or even other processes activated automatically. There are also BI software tools with open APIs and support for Flash, and many similar options. This allows BI output to be used in composite applications (mash-ups).
Finally, data integration is very important and also benefits from years of development in this market. There are many ETL tools and other data integration applications that can interface to a myriad of BI applications and vice versa. The sort of problems experienced in this area include different data definitions, or reference data used in different parts of the organization and in different data sources, making it difficult to consolidate data, and compare and contrast info in different business contexts. Other problems include increasing volumes of data that can lead to data warehousing performance and scalability issues. Data quality is very important, too. If you put garbage in, you will get garbage out. Data quality is important for business efficiency anyway and it is essential for gaining trusted business intelligence.
Edmond Arrey