Frustrated with IT But Still Wanting a BI Solution?
July 13, 2010 | Leave a Comment
The volume of structured data, contained in transaction systems generated by organizations, is at an all time high and will continue to increase. This structured data, however, now needs to be combined with the unstructured data that represents the majority of corporate data and the new social network data. More importantly, knowledge workers and decision makers want this data accessible and made available for analysis. Additionally, much of the unstructured data is already is in the hands of the departmental knowledge workers, but they lack the tools to use it.
Business Intelligence Platform selection has traditionally required the approval of two groups at once, Information Technology (IT) and the departmental knowledge workers, which has always made purchasing and implementing a business intelligence (BI) platform a tricky thing to do. Anyone reading this can probably relate to the tension you’ve observed between your IT department and departmental end-users. Trying to get consensus and agreement on a new platform, typically dead in the middle, takes time and normally leads to some sort of compromise. But the new economic conditions are forcing IT and knowledge workers to look at different approaches for BI.
The new economic realities are driving CIO’s to look at lower cost solutions that provide the additional analytical capabilities demanded by knowledge workers. See my last post for additional information. But the knowledge workers can no longer wait and their increasing frustration appears to be fueling a growing bifurcation with central IT over the nature and future of BI. Specifically, IT led/managed BI versus departmental led/managed BI. Pressured by the new economic realities, the need to cut costs, the need for more information and analytics, and the need to quickly demonstrate business value is pushing the knowledge workers to look past central IT to address their unmet needs. The perceived benefits of improved analysis and decision making are so compelling that the knowledge workers are making the choice towards SaaS/Cloud, despite the risk of creating new fragmented silos of applications and tools.
What makes SaaS/Cloud so compelling?
SaaS/Cloud BI’s key selling points, the ones that are getting the knowledge workers to open their wallets include: (a) the ability to get a BI solution with an almost total lack of IT involvement; (b) little or no upfront cap-ex expenditures for the solution; and (c) op-ex based subscription model that allows you to pay-as-you-go (subscription fee per month instead of a large annual license fee).
Is the future of BI in the Cloud? I‘d like to hear your comments.
I would like to remind our readers that this blog is not just about ASR, nor is it about any specific vendor , infrastructure or solution– it’s a forum for “us” to express thoughts and ideas about the nature and state of business intelligence (BI). I say “us” because a blog is only a one-sided conversation unless there is input from you. Keep the comments coming and make this a repository for industry awareness and better practices. Also, feel free to ask questions or let me know if there are special topics that are interest to the ASR community, and we will try to find the answers for you.
CIO’s’ Top 5 Technology and Business Priorities for 2010
July 8, 2010 | 1 Comment
Recently, Gartner released its 2010 survey of chief information officers (CIO) priorities. The survey of 1,560 CIO’s notes that “2009 was the most challenging year for CIO’s in the corporate and public sectors as they faced multiple budget cuts, delayed spending and increased demand for services with reduced resources”. Gartner also notes that “CIO’s have suffered through a difficult budget tightening period, with budgets essentially cut back to 2005 levels”, but Gartner predicts that budgets will stabilize or grow slightly this year.
Listed below are the top five technology and business priorities for 2010 in order of importance.
Top 5 Technology Priorities
- Virtualization
- Cloud computing
- Web 2.0
- Networking, voice and data communications
- Business intelligence
Top 5 Business Priorities
- Business process improvement
- Reducing enterprise costs
- Increasing the use of information/analytics
- Improving enterprise workforce effectiveness
- Attracting and retaining new customers
Collectively, the respondents indicate that there main focus is on business process improvement and increased use of information. Specifically, the use of business intelligence (BI) solutions, cloud computing and virtualization technologies. Additionally, the findings indicate that business expectations and CIO strategies appear to be in alignment.
Traditionally, technologies like virtualization and cloud computing have been used to enable organizations to get out from under a front-loaded heavy capital investment. Paradoxically, Business Intelligence solutions have traditionally required a front-loaded heavy capital investment (CAPEX) that can initially limit the agility and flexibility of both IT and the business. Additionally, given the cutbacks in organizational budgets, the only new funds available for IT investment and process improvement come from reductions in organizational costs, which are typically operational budgets (OPEX).
Gartner also notes that CIO’s are prioritizing “technologies that can be implemented quickly and without significant upfront expense, instead of investing millions of dollars to get millions in benefits, with these technologies, up front investments are measured in thousands of dollars to get those same benefits.”
Should CIO’s and the business leaders be looking at BI as a Service to resolve the paradox?
What are your thoughts?
ASR Analytics Named to Washington Technology Magazine’s Fast 50
September 8, 2009 | Leave a Comment
Recently, we learned that ASR would be named to Washington Technology Magazine’s Fast 50, a list of the fastest growing companies serving the U.S. government. While it is certainly gratifying to be provided with such recognition, it was especially exciting to see that the magazine chose ASR as one of a handful of companies on the list to spotlight.
Washington Technology recognized that the story of ASR is built on a foundation of trust. A trust that we try to build with each of our clients and partners.
The following is a press release of the announcement:
Potomac, MD, September 8, 2009: ASR Analytics LLC, a consulting firm providing advanced analytic services to public and private sector clients, was recently named to Washington Technology Magazine’s Fast 50. ASR was ranked 22nd among the fastest growing companies serving the United States government. The magazine’s Fast 50 rankings evaluate the growth of small businesses over a five year period.
ASR was also highlighted in an article appearing on Washington Technology’s website (http://www.washingtontechnology.com/Articles/2009/08/31/Fast-50-ASR.aspx). The article noted that ASR fills a unique niche for its clients in government, higher education, and health care, helping them to integrate enterprise data with predictive analytics.
The magazine cited the company’s work with the Uniformed Services University of the Health Sciences (USUHS) as an example of its specialized work. ASR worked with the medical school to develop a long-term career outcome study of its graduates. The data from the study was integrated with data from the institution’s student information system. Predictive analytics were applied to identify patterns and trends that administrators used to make decisions for recruitment and student retention.
Trust was another key aspect of ASR’s success noted by the article’s author. Forging deep relationships and advancing solutions that emphasize people and process as much as technology helps the company build a high-degree of trust with its clients. “In times like now, when budgets are tight, [organizations] are going to turn to the people they trust,” said Dr. Peter Arena, one of ASR’s founding principals. “That is the kind of reputation we are trying to build.”
About ASR Analytics, LLC
ASR Analytics LLC (ASR) provides specialized business intelligence and analytic consulting services to clients in the public and private sectors. ASR aims to provide policy and decision makers with self-service decision support tools to ensure regulatory compliance and increase organizational effectiveness. To learn more about our solutions visit: http://www.asranalytics.com/.
Stimulus Bill Visualization: Where does the money go?
February 12, 2009 | Leave a Comment
Here’s a nice visualization that shows where the money in the stimulus bill is allocated at a high level. The original can be found at the Washington Post, which created this visualization based upon an analysis conducted by the Congressional Budget Office. This looks to be from the original House bill and not the compromise bill that appears to have emerged from Congress yesterday.
Press Release: U.S. Department of the Treasury Approves Mentor-Protégé Agreement for IBM and ASR Analytics
September 30, 2008 | Leave a Comment
Potomac, MD, September 30, 2008: ASR Analytics LLC, a consulting firm providing advanced analytic services to public and private sector clients, recently entered into a Mentor-Protégé agreement with IBM Global Business Services (NYSE: IBM), under the U.S. Department of the Treasury, Office of Small and Disadvantaged Business Utilization, Mentor-Protégé program. Through this 10 month agreement (with the option to extend), IBM will provide developmental assistance and mentoring to ASR in areas such as corporate management and infrastructure and performance management. The Mentor-Protégé relationship will also foster increased collaboration between ASR and IBM in delivering consulting services to the Department of Treasury, helping the department modernize, manage performance, and provide outstanding service to taxpayers.
The Treasury Mentor-Protégé program was created to motivate and encourage firms to assist small businesses, including HUBZone small businesses, small disadvantaged businesses, women-owned small businesses, veteran-owned small businesses, and service disabled veteran-owned small businesses. The program is also designed to improve the performance of Department of the Treasury contracts and subcontracts, foster the establishment of long-term business relationships between these entities and Treasury prime contractors, and increase the overall number of these entities that receive Treasury contract and subcontract awards.
According to Mike Stavrianos, a founding principal of ASR Analytics, the partnership will be mutually beneficial for all parties. “ASR is proud to have been selected by IBM Global Business Services and the U.S. Department of Treasury for the Mentor-Protégé program,” said Stavrianos. “While ASR will certainly benefit from the opportunity afforded by this innovative program, we plan to contribute greatly to make this a win-win-win partnership for all involved.”
IBM has participated in the Treasury Mentor-Protégé program since 2001, having served as a mentor to a select group of small businesses. IBM is a major provider of business and IT consulting services to the federal government and has extensive experience working with the Department of Treasury.
“ASR’s domain expertise surrounding tax policy and tax system administration, combined with their expertise in advanced analytics solutions will enhance IBM’s ability to provide unique solutions to its current and future clients within the Department of Treasury,” said Mona Kotlarsky, Executive Project Manager at IBM Global Business Services.
For more information about ASR Analytics solutions for government clients, visit: http://www.asranalytics.com/solutions/government/
About ASR Analytics, LLC
ASR Analytics LLC (ASR) provides customized business intelligence and analytic consulting services to clients in the public and private sectors. ASR aims to provide policy makers with self-service decision support tools to ensure regulatory compliance and increase organizational effectiveness. To learn more about our solutions visit: http://www.asranalytics.com/.
6 Best Practices for Successful Business Intelligence
February 11, 2008 | Leave a Comment
Business intelligence (BI) is not about technology. No doubt there is much technology involved, but a sound business intelligence strategy concentrates more on methods. The outcome of intelligence gleaned from a strategic reporting or decision support system should be an action or decision. The decisions made from business intelligence will likely lead to changes made in strategy and/or individual business process.
These changes in strategy and business processes will necessitate changes to one’s enterprise resource planning (ERP) or other transactional systems. For example, new business rules or codes may need to be added to the ERP in order to operationalize a decision that was made. This will require an understanding of the business rules engine of the ERP as well as the implications from a historical measurement perspective of changing or adding codes to the system. People will need to be trained and constituents may need to be informed of new rules.
BI is much more about organizational alignment or people and processes around a common set of strategies and goals then it is about technology. To that end, follow these 6 best practices to move your organization from silo-based planning to one that is aligned around a culture of evidence:
- Define areas for exploration – What subject areas need to be studied? Not all can be effectively studied at one time – not at the start – therefore, you will need to prioritize. The organizations leaders will need to set the priorities based on the key strategies that need to be affected.
- Articulate problem statements – Now you have identified the subject areas to be studied. What are the problems in that area? Simple year-over-year trend analysis will often highlight where the problems are lurking. The problem should be stated as follows: [Subject Area] is down by 15% compared to last year.
- Identify causal factors – Perhaps one of the most overlooked steps in the process. Your problem statements only tell you what is happening. It is critical that you find out why it is happening. Statistical models need to be employed to determine the key drivers influencing the problem area. Identification of the key drivers in the area will help you isolate the problem and determine the factors causing the problem.
- Determine corrective action – Once the causal factors have been identified decisions can be made and corrective action taken. True evidence-based decision making.
- Align people, process, and technology – Decisions inevitably lead to change. Most often the change comes in the form of a new business process. The new business process will need to be codified in the ERP system and people may need to be reorganized and/or retrained. This will be the hardest step in the process toward a culture of evidence, yet it is also the most critical.
- Measure outcomes – Now that people, process, and technology has been aligned to solve the problem, you must measure the effectiveness of this action. Be careful that you allow a sufficient amount of time for the impact of the change. In fact, decision makers should agree about the length of time they will permit for the action to take hold and pre-determine a point in time for re-evaluation.
As you can see from the diagram above, the process is cyclical. As decisions are made and corrective action is taken, key drivers will change. This will constantly cause the organization to reevaluate and revisit its strategies and tactics over the course of time.
Fair Lending Another Casualty of the Subprime Meltdown?
January 17, 2008 | 1 Comment
You’d have to do a lot to avoid discussion of the subprime mess and the effects that it is alleged to be having on the housing and financial markets (although we think there are more reasons for optimism than many, but more on that in another article). One area where we do have concerns is in the effect of the subprime cleanup on fair lending.
Fair lending compliance requires that regulated entitites (which includes essentially all retail mortgage lending institutions) provide government regulators specific facts on the mortgage applications they did and did not approve. These data are then examined statistically to determine if there is an observable pattern of discrimination in underwriting practices based on the treatment of members of protected groups.
In a recent article, the Washington Post describes the actions that lenders are taking to correct the underwriting excesses of the subprime boom. While the industry experts offer somewhat differing accounts of actions that are expected to be taken, all agreed that credit scores are going to lose some of their weight in the underwriting process, at least in the near term. To quote from the article,
But income matters now, and so does cash, said Sean O’Boyle, a vice president at SunTrust Mortgage in Chevy Chase. Lenders expect borrowers to have several months’ worth of mortgage payments in reserve and a steady job. ‘Job stability. Credit. Cash,’ O’Boyle said. ‘They’re all equally important. Not one of them overshadows the other.’
Unfortunately, moving to a broader set of measures of creditworthiness, while intended as a means of tightening underwriting, could achieve just the opposite, and cause fair lending compliance issues to boot. Remember that the pressure to maintain and increase loan volumes fueled the use of exotic mortgages to increase the number of eligible borrowers. In the same way there will be pressure to use additional information to cherry pick borrowers with borderline credit scores.
Here’s where fair lending compliance comes in – cherry picking borrowers based on any information not included in the compliance data provided to regulators introduces the risk that correlations will be found between protected group status and the probability of receiving a loan, even if no mortgage discrimination was ever intended. Is the value of cherry picking worth the potential compliance issues it might cause? We don’t think so.
Here’s a much less problematic solution to tightening underwriting requirements – demand higher credit scores from all borrowers and stick close to the information reported for fair lending compliance when making the underwriting decision. This would have none of the potential downside of including non-reported information and would require few changes to underwriting processes. It will be interesting to see if the pressure to maintain loan volumes or the need to assure regulatory compliance wins out.
ASR provides A-123 compliance services to the Veterans Administration
August 26, 2007 | Leave a Comment
ASR Analytics is working with Grant Thornton to provide A-123 compliance services to the Veterans Health Administration. ASR is developing samples of financial records to be used as part of a valuation and accuracy study of VHA capital equipment. ASR is also providing discovery sampling methodologies to validate existing inventory records.
ASR again selected to provide A-123 and IPIA compliance services at the U.S. Department of Labor
May 15, 2007 | Leave a Comment
For the second year in a row, ASR Analytics is supporting the U.S. Department of Labor (“DOL”) Office of the Chief Financial Officer to validate controls over financial transactions performed by the Department. ASR is performing a variety of tasks surrounding selection, analysis, and validation of statistical sampling methodologies. DOL seeks to achieve three objectives through this project: (1) test internal controls over the key business processes, in accordance with the requirements of the revised Circular A-123, Appendix A; (2) satisfy the testing requirements for the Improper Payments Information Act of 2002 for designated business processes/programs; and (3) project the amount of monetary misstatement that may exist in all material financial statement line items. ASR is performing this work as a subcontractor to Grant Thornton.
ASR to assist NASA comply with Improper Payments Information Act
April 26, 2007 | Leave a Comment
ASR Analytics is working with Grant Thornton to provide selection, analysis, and validation of several statistical samples of financial transactions to NASA. NASA seeks to satisfy the testing requirements for the Improper Payments Information Act of 2002 for designated business processes/programs.