Now that 2009 and the first decade of the 21st Century are drawing to a close, I was thinking that I may not have an opportunity to write another 2010 prediction piece; but today this came in: “The Top 10 Trends for 2010 in Analytics, Business Intelligence, and Performance Management,” by Nenshad Bardoliwalla, an author, recently CTO for enterprise performance management (EPM) and governance, risk, and compliance (GRC) at SAP.
The title struck me because business intelligence is high on the priority list of organizations today, so a piece that provides 10 trend predictions within one of the hottest areas of business and IT strategy is interesting.
The post is brilliantly written and thought out. I summarized the supporting text of each trend for brevity below. Here are Nenshad Bardoliwalla’s top 10 trends for 2010 in analytics, business intelligence, and performance management:
1. We will witness the emergence of packaged strategy-driven execution applications. Strategy-driven execution, as Bardoliwalla defined in his book, is “the complete fusion of goals, initiatives, plans, forecasts, risks, controls, performance monitoring, and optimization with transactional processes.” He cites applications provided by Workday and SalesForce.com as examples that include embedded real-time contextual reporting for the fusion of analytic and transactional capability in the context of business processes.
2. The holy grail of the predictive, real-time enterprise will start to deliver on its promises. The holy grail of analytic technologies has always been the promise of being able to predict future outcomes by sensing and responding, with minimal latency between event and decision point. Combining predictive analytics and real-time complex event processing capabilities will lead to new classes of applications for business management that were unimaginable a decade ago.
3. The industry will put reporting and slice-and-dice capabilities in their appropriate places and return to its decision-centric roots with a healthy dose of Web 2.0 style collaboration. SaaS BI will reduce report-production cost to nearly free. Mashups will allow users to assemble all of the relevant data for making a decision; social capabilities will allow users to discuss this relevant data to generate “crowdsourced” wisdom; and explicit decisions, along with automated inferences, will be captured and correlated against outcomes.
4. Performance, risk, and compliance management will continue to become unified in a process-based framework and make the leap out of the CFO’s office. The disciplines of performance, risk, and compliance management have been considered separate for a long time, but the walls are breaking down for effective organizational governance. While financial performance, risk, and compliance management are clearly the areas of most significant investment for most companies, these concerns are now finally becoming enterprise-level plays that are escaping the confines of the CFO. We will continue to witness significant investment in sales and marketing performance management.
5. SaaS / Cloud BI Tools will steal significant revenue from on-premises vendors but also fight for limited oxygen amongst themselves. From many accounts, this was the year that SaaS-based offerings hit the mainstream due to their numerous advantages over on-premises offerings, and this certainly was in evidence with the significant uptick in investment and market visibility of SaaS BI vendors. Vendors like Birst continue to announce wins at a fair clip along with innovations at a fraction of the cost of their on-premises brethren. There is little reason for any customer to invest in on-premises capabilities at the price/performance ratio that the SaaS vendors are offering.
6. The undeniable arrival of the era of big data will lead to further proliferation in data management alternatives. We have witnessed an explosion of exciting data management offerings in the last few years that have reinvigorated the information management sector of the industry. The largest web players such as Google (BigTable), Yahoo (Hadoop), Amazon (Dynamo), and Facebook (Cassandra) have built their own solutions to handle their own incredible data volumes, with the open source Hadoop ecosystem and commercial offerings like CloudEra leading the charge in broad awareness. Additionally, a whole new industry of DBMSs dedicated to analytic workloads have sprung up, with flagship vendors like Netezza, Greenplum, Vertica, Aster Data, and the like with significant innovations in in-memory processing, exploiting parallelism, columnar storage options, and more. Additionally, significant opportunities to push application processing into the databases themselves are manifesting themselves. Visionary applications of this technology in areas like metereological forecasting and genomic sequencing with massive data volumes will become possible at hitherto unimaginable price points.
7. Advanced visualization will continue to increase in depth and relevance to broader audiences. With consumers broadly aware of the features of Google Maps or the tactile manipulations possible on the iPhone, these capabilities will find their way into enterprise offerings at a rapid speed lest the gap between the consumer and enterprise realms become too large and lead to large-scale adoption revolts as a younger generation begins to enter the workforce having never known the green screens of yore.
8. Open source offerings will continue to make in-roads against on-premises offerings. Much as SaaS BI offerings are doing, open source offerings in the larger BI market are disrupting the incumbent, closed-source, on-premises vendors.
9. Data quality, data integration, and data virtualization will merge with master data management to form a unified information management platform for structured and unstructured data. Increasingly, data quality and data integration will be interlocked to ensure the right, cleansed data is moved to downstream sources by attacking the problem at its root. With the amount of relevant data sources exploding in the enterprise and no way to integrate all the data sources into a single physical location while maintaining agility, vendors like Composite Software are providing data virtualization capabilities, whereby canonical information models can be overlaid on top of information assets regardless of where they are located, capable of addressing the federation of batch, real-time and event data sources. These disparate data soures will need to be harmonized by strong master data management capabilities, whereby the definitions of key entities in the enterprise like customers, suppliers, products, etc. can be used to provide semantic unification over these distributed data sources. Finally, structured, semi-structured, and unstructured information will all be able to be extracted, transformed, loaded, and queried from this ubiquitious information management platform by leveraging text analytics that continue to grow in importance and combining them with data virtualization capabilities.
10. Excel will continue to provide the dominant paradigm for end-user BI consumption. For Excel specifically, the number one analytic tool by far with a home on hundreds of millions of personal desktops, Microsoft has invested significantly in ensuring its continued viability as we move past its second decade of existence, and its adoption shows absolutely no sign of abating any time soon.
It will be interesting to see how Nenshad’s predictions play out during 2010. I think that online spreadsheet eiVia will make inroads to Excel for predictive analytics in 2010.
For a great overview of SaaS BI, read “What’s Up with Cloud Analytics,” by Dave Wells.
If you want to derive quick, cost-effective, flexible, and scalable benefits from business intelligence during 2010, here are some excellent SaaS solutions to consider:
I am excited that BI is such a high priority for 2010 and the beginning of a new decade. I know it will help optimize business performance and decisions, and possibly also help provide a more stable economy and business climate ahead. An excellent new study by IBM clearly indicates that businesses that applied analytics-derived insights outperformed their peers in the economic downturn, and are poised to break away during economic recovery.
What do you think of Nenshad Bardoliwalla’s top 10 trends for 2010 in analytics, business intelligence, and performance management, and how do you plan to improve business intelligence in 2010?
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