The rise of data warehousing in the ‘90s and early ‘00s resulted in a huge consulting wave of developing and delivering analytic modules to support the information needs of groups of executives or workers of an enterprise. However, getting access to this information at the right time, relevant to making a decision or answering that next question in the minds of the business user, created a demand for BI tools that would help take the data from data warehouses or from relational database management systems and convert them into intelligent information. Although, IT organizations developed a strategy around data warehouse and information access that catered to the information needs – the IT organization is constrained by resources and budget. A prioritization exercise, be it value based or based on whoever is screaming the loudest, results in the typical 80-20 rule, 80% of an organization’s reporting needs are met in a generalized fashion, while only a smaller portion of the analytical requirements which are specific to a department receives the attention, resources and focus needed.
Introducing Packaged Analytic Applications
This challenge gave rise to the concept of packaged analytic applications – in 2001-02, packaged analytic applications were touted as the panacea for all data warehousing evils with a case made for the various offerings that existed in the market. A decade has gone by and we see now that packaged analytic applications are starting to rise in adoption, and in solution maturity. In deference to the BI add-ins that were becoming prevalent during those times in particular by consultants and promoted by the BI tools vendors, packaged analytic applications were promoted by enterprise application vendors to be purpose built to solve a particular department’s information needs in terms of metrics, analysis and information presentation and came with vertical integration to one or more source systems that generated data.
Today, a decade later, with the convergence of enterprise application vendors and BI tool vendors – we see a real opportunity in providing customers with packaged analytic applications that are not only vertically integrated but also in building a horizontal data set foundation, supporting data relationships to match the complex business process relationships across the company. Bringing together the business process expertise and the BI capabilities, vendors such as SAP are delivering packaged analytic applications that can be rapidly deployed.
The Advantage of Analytic Applications
Analytic Applications – contextually relevant, delivering the right sized information and at the right time, is fast being recognized as the panacea for information overload. Every worker – from shop floor to top floor, from producers to retail stores – needs information to guide their next steps, and as such the concept of pervasive business intelligence started to evolve in 2004-05, and is catching on rapidly amongst IT organizations and their business counterparts are fast relying on pervasive BI to transform their organization. SAP is uniquely positioned to take advantage of such a convergence of business process knowledge and technology assets, to provide analytic applications bringing BI to every user in an organization, via:
Examples of solutions from SAP include Supply Chain Performance Management, CRM Analytics, Cross Talent Management Analytics (HCM), Financial Analytics, Spend Performance Management. We will take a look at some of these solutions and their inherent nature to provide relevant, contextual insights to business users at the right time and place, stay tuned.
Pre-packaged and purpose built Analytic Applications help IT deliver relevant solutions to their businesses and yet keeping to a common BI platform, with ease of deployment and minimizing the time it would take to build a solution from scratch and the cost of maintaining such solutions. At the same time, the businesses enjoy the benefit of quick time to value in terms of having their information needs met. Built on the basis of self-service access and usage capabilities, analytic applications from SAP can be administered and operated by the business, with minimal IT support required on an ongoing basis.
These applications still require a level of data extraction and information gathering from various sources – with the emergence of in-memory analytics, connecting directly to the application data source, the data integration complexity can be further simplified. Stay tuned also for a future blog post on in-memory analytics, which would define the next decade of analytic applications, fulfilling perhaps the dream of combining horizontal dataset integration with vertical integration into business processes…