Leading for Success with your Business Intelligence Initiative: Part 4
September 3, 2010 | Leave a Comment
In my previous post Leading for Success with your Business Intelligence Initiative: Part 3, I discussed the value of increasing your understanding of the BI ecosystem and how it can enable the use of self-organizing teams. The next key to improving your BI success is maintaining the commitment of key constituents, improving your institutional communication around the BI initiative and setting the stage for your BI development teams’ success.
The C’s in Success
Communication
In my experience, there’s usually a poor communication strategy behind any really good idea that doesn’t quite get off the ground. Too often BI leaders tend to focus too long on the larger business case (ROI, institutional benefits, etc) and fizzle out on building the personal commitment, the “hearts and minds” part. What is required is continuous and focused communication with key constituents before, during and after the launch. In my experience, the success of an institutional wide BI initiative is as dependent on your political success as it is on your technical success.
To keep the institutional BI visibility high and retain the commitment of the key constituents take a cue from the masters: politicians. Political campaign platforms are based on the three C principles: (1) Crisp and Clear; (2) Context Centric; and (3) Consistent and Consistently. Every stump speech, every sound bite, every public conversation and every written message needs to be rigorously “on message,” All the BI sponsors and members of the BI development team need to follow the three C’s principles.
1. Crisp and Clear
How do you describe the BI initiative and what value will the BI initiative have for the person you are talking to? Let’s go back to that tried-and-true technique–the elevator pitch. Can you clearly describe the goal/value of the BI initiative in 30 seconds or less? When you talk to someone about the BI initiative does your description hold that person’s attention? Or do their eyes glaze over or wander across the room?
Being crisp is about informing people about the value, what you plan to accomplish for them, in as few words as possible, and using that same crisp message in written materials.
Take this Test
Find a friend who is the least likely to understand your BI initiative, and test your “message crispness” on them. Tell them what you are doing with BI in two or three sentences. Avoid industry jargon and technical terms that only people in the BI field will understand. Then ask them to repeat what they think you are doing back to you. If they don’t come back with the right answer, the message isn’t crisp and clear.
2. Context Centric for each Stakeholder type
You need to communicate the role they play and the value proposition to each Stakeholder type (executives, BI developers, end-users, etc). You need to inform stakeholders about what you are doing, why you are doing it, their role in the BI initiative and the value it has for them. People need convincing as to why they should spend their time and limited resources with you. Your story should focus on how they benefit from the BI initiative (communicated from a “what’s in it for them?” perspective).
3. Consistent and Consistently
Once you’ve nailed down your crisp message, and you’re telling your story from your stakeholder’s perspective, make sure you tell it consistently in your conversations, e-mails, in print materials, via etc.
Nothing is more disconcerting to stakeholders than hearing one story from one communications channel or individual and then hearing or reading a different version of the story from someone else or someplace else. They don’t know which version to believe. Reestablish who you are and what you are doing with every stakeholder interaction. Reinforce your story as often as possible.
In the next post we’ll explore some additional C’s to you BI development teams’ success.
Leading for Success with your Business Intelligence Initiative: Part 3
August 27, 2010 | Leave a Comment
In my previous post Leading for Success with your Business Intelligence Initiative: Part 2, I discussed the value of Structuring-creating a shared vision and building an atmosphere of engagement and energy for the BI initiative. The most important aspect of Structuring is that it incorporates and defines the entire BI ecosystem (culture, goals, people, process, technology, information) that people want to be a part of and contribute to. The next key to improving your success is improving your Understanding of the ecosystem.
The U in Success
Understanding
Another good investment is taking the time to build relationships with and among the BI development team and stakeholders. Actively involving others, with a working knowledge of the BI ecosystem, in planning and design issues is critical to building institutional commitment and designing the right solution. Research shows that the bigger the issue, the more likely we are to suck it up to ourselves. While this may seem like the wise course, think about the message it sends. Either that your people aren’t capable of handling these issues or that you don’t trust them. Another implication is that they don’t gain the experience and skills they would need to eventually handle tough issues. So, you create a self-fulfilling prophecy. Most importantly it prevents you and the BI initiative from utilizing self organizing teams-one of the other keys to BI success.
It’ll be easier for people to get behind you and support the BI initiative if they feel some direct connection to who you are and what you’re about. This doesn’t need to be personal information. What you need to concentrate on is sharing information about (a) how you see the team living up to the vision; (b) improving the depth of understanding of the BI ecosystem; (c) sharing some of the obstacles the team faces; and (d) building trust and soliciting their input. Where feasible, let them in on new developments and provide context that will help them understand the necessity for the change. In short, create the narrative of what’s happening in the larger institution and create an atmosphere of trust and open communication. If you can do this then you have an opportunity to utilize “Self-Organizing” teams. Self-Organizing teams (a) assign tasks to each other; (b) they coordinate and review each other’s work artifacts; (c) they collaborate on project activities; (d) they make project-related decisions (together); and (e) they take on another team member’s tasks when needed. Additionally, working in this way is (a) much faster; (b) communicating and coordinating activities among all the team members is more efficient and less error-prone; and (c) greatly improves synergy and knowledge transfer among team members. These are all critical factors for improving you BI success.
Even if you aren’t ready to unleash a self-organizing team, I would recommend creating a recurring forum where a workable number of employees, say six to ten, can interact personally. In addition to hearing your thoughts, they could ask questions about the institution and provide feedback about any impediments in their part of the BI solution to achieving the vision.
Leading for Success with your Business Intelligence Initiative: Part 2
August 13, 2010 | 1 Comment
This is part 2 on my thoughts on Leading for Success with your Business Intelligence Initiative. In my previous post, I stated that BI success will be improved if you can tap the creativity and commitment of your entire institution and fully engage the BI team. The remainder of this series will explore some thoughts on strategies that may help you do just that.
The ” S” in Success
Structuring and Setting the Stage
A powerful way to get and keep your stakeholders and BI team aligned is to define, and garner complete buy-in to the Nature of the BI initiative. The Nature of the BI initiative is an enrolling vision for the initiative; one that goes beyond defining what currently exists to creating a picture of what it can become and how it will improve the success of the institution. Additionally, you need different granular levels of the vision. You need to have an enterprise-wide vision to get and maintain the executive sponsorship, but you also need to paint a more detailed picture for your BI team and individual projects. Involving as many of your key stakeholders and BI development team members as possible in the visioning will create engagement and energy around the deliverables. Just remember, that everyone involved must have some skin in the game. The three key constituencies for business intelligence that you must address include the executive sponsors of your BI initiative, the principal users of the BI tools, and consumers who will benefit from it.
Defining the Nature of the BI initiative and visions is simply a picture of a desired future state. I recommend staring a discussion using the following questions:
- What will the institution look like if our BI program and projects are accomplished?
- What will be happening within our institution?
- What will we have to do to establish the “Culture of Evidence”
- What will our institutional colleagues be saying about us?
- What will be our call to arms and message be?
- How will we feel?
The most important thing is that it defines the entire ecosystem (culture, goals, people, process, technology, information) that people want to be a part of and contribute to.
Leading for Success with your Business Intelligence Initiative
August 6, 2010 | 2 Comments
In my previous post, Business Intelligence Initiatives Get an “A” for Effort and a “C” for Results, the respondents indicated that the major reasons for the lack of business intelligence (BI) success were institutional and not technical. If you’re a manager, director, vice president or even the president of your institution, I have a simple question for you. Who is responsible for the success of your institution? I pretty sure that your answer is the same as mine, we all are – after all, I can’t do it myself!” Good answer. Unfortunately, research shows that people in a managerial or leadership role regularly take on too much responsibility for the success of their areas, and this predictable behavior has its consequences. Specifically, leaders often feel burdened, exhausted and overwhelmed. Additionally, the leadership for BI initiatives normally falls to an existing successful executive or manger that has BI success added to their existing plate of responsibilities. But, what most institutions fail to understand is that the previous successful behavior of these individuals may be limiting the success of their new BI team and initiative.
Barry Oshry, a leading theorist in human systems theory identifies the behavior of “sucking up responsibility” as the predictable response to the complexity and responsibility inherent in the “Top” space and that this behavior isn’t an explicit choice but a reflexive response. However, this response may be detrimental to the success of your pervasive BI initiative.
Thoughts on improving your BI SUCCESS
No matter how skilled and experienced the leader, an institutions’ BI success will be improved if you can tap the creativity and commitment of your entire institution and BI team. In the next blog posts I will explore some strategies that may help you do just that, but first a note of caution. I’m sure we’ve all heard the familiar refrain, “Don’t ask me; I just work here.” This comment identifies an individual that is uninformed and belies an attitude of non-accountability. Ultimately, you can’t empower others; each individual must make the choice between being truly engaged and challenged in their work lives and being passive and lackadaisical. But that doesn’t let you, as a leader, off the hook. It is in your best interest and the interest of the institution to create the conditions that enable others to take responsibility and to succeed with your BI initiative.
References
- Oshry, Barry Seeing Systems: Unlocking the Mysteries of Institutional Life, Berrett-Koehler, San Francisco, 2007.
Business Intelligence Initiatives Get an “A” for Effort and a “C” for Results
July 16, 2010 | Leave a Comment
There is almost universal agreement that the lack of appropriate, accurate and timely information is part of the reason why organizations and even entire nations got themselves into the recent economic mess. Many analysts also agree that business intelligence (BI), the process that transforms data into intelligence, now has the opportunity to help accelerate the economic recovery and aid these organizations and nations in dealing with the new global business complexities. According to a recent Ness BI Market Pulse Survey, BI initiatives continue to be front and center on most organizational business and IT agendas. The problem they found is that BI achievements are falling short of expected outcomes. For instance, according to the report, BI solutions have done a pretty good job of providing a view into the past (hindsight) such as access to planning and financial data. But they have been less successful in providing current performance information (insight) to improve decision-making or information on future conditions (foresight) such as future customer demand.
So what are organizations really doing with business intelligence and are they being successful?
According to the “The Ness Technologies Market Pulse Study on Business Intelligence” (BI), conducted in the fourth quarter of 2009 and published May 2010, BI initiatives just aren’t delivering the results that executives were expecting. The study indicates that results are lagging expected outcomes in 14 of 16 categories as depicted below.
©2010 Ness Global Industries
The largest and most frightening gap is in business agility and planning. Respondents indicate the reason for this discrepancy is that they have run into a number of key challenges. Not surprising, is that the most significant challenges are not technical ones. The top 5 challenges, in order of importance are: (1) lack of alignment with organizational strategy (over 50%); (2) lack of working partnership between business and IT (40%); (3) resistance to change (38%) ; (4) lack of executive sponsorship; and (5) lack of communication by the BI leadership team. This is supported by the fact that less than one-half of the survey respondents believe that those responsible for BI initiatives are in regular contact and coordinate plans (49%).
The two top technical issues include problems with the integration of data and persistence of data silos. Specifically, many organizations do not have a plan and have not resolved issues to integrate their isolated vertical data structures that are the cornerstone for establishing a centralized repository for the “Single Version of the Truth”. Respondents also listed the lack of a strong data governance initiative as contributing to this last issue.
But despite these results, it looks like organizations are committed to the potential payoff of BI. Major North American organizations report an increase in there BI fiscal year 2010 budgets and they anticipate that this allocation will increase in fiscal year 2011 as well.
The planned actions that organizations plan to take or investigate include the following:
Organizational Initiatives
- Ensure that BI is aligned with the organization’s strategy
- Appoint an executive to “own” the BI program, communicate regularly with stakeholders, and assemble a seasoned team, from both Business and IT groups, with the skills to get the job done.
- Set clear objectives and develop an overall BI roadmap that concisely defines what data is needed and how it should be delivered.
- Implement the program in short, phased initiatives that quickly deliver ROI to stakeholders
Technical Initiatives
- Data Silos and integration
- Data Governance
Next-Generation BI Toolset
- Predictive analytics
- In-memory processing
- Software as a service (SaaS)
The technical and next-Generation Initiatives are also consistent with the findings published in Information Week (August 29, 2009) and CIO Magazine (February 2010).
BI Pulse Survey
Would you like to learn how members of the academy are doing with their BI initiative?
Next week, ASR will be sending out a survey to take the BI pulse of the higher education community. By completing the survey (5 minutes) you will be providing your colleagues with the latest information on how members of the academy are cultivating their BI initiatives. We look forward to your cooperation.
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?
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 selected to assist with SAS Fair Banking implementation at major bank
December 15, 2007 | Leave a Comment
ASR has been selected to assist with the implementation of the SAS Fair Banking solution at a very large nationwide mortgage lender. ASR was selected for this assignment based on past success implementing the SAS Fair Banking solution at a midsized morgage lender earlier this year. This will be one of the first implementations of latest version of SAS Fair Banking (version 8). The SAS Fair Banking solution provides a complete set of tools for self-assessing compliance with the Home Mortgage Disclosure Act (HMDA) and the Community Reinvestment Act (CRA). SAS Fair Banking enables mortgage lending institutions to effectively and efficiently collect, validate, store, isolate, aggregate, and report on loan data and loan application data. This enables financial institutions to better understand how their organization is performing based on the key compliance concerns behind HMDA and CRA. As a result, the institutions are able to meet the rigorous HMDA and CRA filing requirements with greater accuracy and timeliness. ASR will be working as a subcontractor to Zencos Consulting LLC and SAS on this engagement.