Building Automated Decision Making into BI System Design – A Methodology Overview May 18, 2007
Posted by Cyril Brookes in BI Requirements Definition, Decision Automation, General, Issues in building BI reporting systems.4 comments
Automated decision making for business is about flavor of the month. Most emphasis has been on automating business analytics, say, underwriting in the insurance industry and stock market program trading. But there are ample opportunities for incorporating automation in more conventional BI systems, especially corporate performance management, where there has been, so far, little discussion.
Tom Davenport’s recent work on business analytics has been widely reported and commented. The consultants and software marketers are circling the wagons.
To highlight opportunities and stimulate discussion among BI analysts this post explores how relevant BI system targets for automation might be identified.
Most BI analysts see their role as designers of systems to support management decision making through effective presentation of information. That is, of course, commendable and important. But is that all there is? That focus doesn’t preclude building automated decision making systems if the context is suitable. It’s just that it isn’t done often. We seem to be reluctant to try and replace managers, maybe it’s because they are our bread and butter?
There are three generally accepted classes of decisions in business; operational, tactical and strategic. It’s pretty obvious that automatic decision making is almost always associated with operational, and perhaps some tactical, contexts. If it’s strategic, then forget it. Since many BI environments serve a mix of strategic and operational users, the prevailing focus is almost always on information presentation, rather than active replacement of human decision makers.
This discussion reminds me of a 25 year prediction from a long forgotten business journal article of the 1960s “Boards of Directors will be retained for sentimental reasons; computers will make all the decisions….”. Didn’t happen, and won’t. A similar, but contrary, forecast in the HBR of June 1966 “A manager in the year 1985 or so will sit in his paperless, peopleless office with his computer terminal and make decisions based on information and analyses displayed on a screen…” There still seem to be a lot of executive assistants around!
My intention with this post is to suggest a methodology or process which demonstrates how BI analysts can effectively and efficiently identify opportunities beyond the passive aim of information presentation. Even if the resulting design only partially automates decision making, it is likely to be a better, more effective solution than its passive counterpart, simply because it will be the result of a more creative and challenging design process.
In the current spate of articles there are many examples of apparently successful automated business process systems. While these may whet the appetite of a designer they are not, in my view, useful guides when the task of synthesising a BI system incorporating is being undertaken. When your child is given his/her first bicycle, showing someone cycling down the street isn’t going to be much help in teaching how to ride. Hands-on synthesis is needed. Big pictures may create envy, but don’t instruct much.
I suggest that it will be worthwhile for a BI analyst and executive team to review the corporate BI environment, existing and planned, and assess the potential for including automated decision making in the BI systems supporting each business segment.
Further, such a review should use a project planning method which segments activities into several bite sized Phases. Here’s a suggested outline, with more detail on each Phase to follow.
Phase 1: Identify the controllable business variables in the target businesses, ignoring specific business processes
Most articles on automated decision making start with the business process and BPM analyses. I think this is the wrong initial focus. To me, the optimal review starting point is to identify the control parameters of typical business processes that are amenable to automatic adjustment. The number of business process control “levers” available to management is finite, quite small in fact, and the number that might be controlled automatically, with profit, is even smaller. Examples include: Automatic pricing adjustment, dynamic production scheduling, staff re-assignment.
A more complete discussion on identifying control variables follows in a later post. It is, I believe, the most important part of project selection and specification. Get this wrong and you will certainly miss out on the best opportunities.
Phase 2: Identify potential business processes, existing or planned, that utilize one or more of these candidate control parameters and may benefit from automation
The same control variables are likely to appear in multiple business processes. For example, automatic price adjustment could impact BI systems supporting Order Entry, Production Scheduling, CRM, Inventory Management, etc.
Phase 3: Identify components of the candidate BI systems that may profitably incorporate automated decision making
Management 101, since Herbert Simon’s day, tells us that there is a defined decision making process, with several component steps between becoming aware of a problem or opportunity, and deciding what action to take. Automating the decision process clearly requires that one or more of these steps should be performed without reference to a human.
It is relatively easy to consider each of these decision process components in turn, to determine the extent to which it/they can be automated. My later post will give more detail if you are interested, Dear Reader.
Phase 4: Design the business analytics; business rules, predictive analysis, time series analysis wherever Phase 3 indicates potential utility
This is the fun part. The software tools for business rules management are much improved since I first started playing with IF…AND…THEN….ELSE statements as the basis for automation, as are the forecasting and statistical analysis packages.
I leave it to you to work out the details, as they are always application dependent. But always be aware that rules change, sometimes quickly, so dynamic management, or decision making agility if you will, is important. Enjoy.
Also, note that Phase 4 will be an iterative process, with frequent Phase 5 reviews to ensure that business sense prevails, limiting the scope for white elephant projects; even though they can be fun.
Phase 5: Evaluation and feasibility reviews of the costs and benefits of automated decision making components within the BI system
Try not to let the excitement of creating rules and embedding predictive analytics in a BI system carry you away; well only a little bit anyway! To me, this is one of the most interesting and absorbing roles of being a BI analyst and designer; certainly it beats specifying reports.
Building automation into BI is highly recommended, especially if you are looking for a challenge!
DIY BI Design Best Practice April 23, 2007
Posted by Cyril Brookes in BI Requirements Definition, General, Issues in building BI reporting systems.add a comment
Backing up my conviction that DIY business intelligence is going mainstream, I’ve put together a set of good practice guidelines that might, with profit, be followed by the responsible BI Rogue. Will these renegades with spreadsheet in hand, data warehouse on tap and a vague specification in mind have regard for guidelines? Only time will tell, but we won’t have to wait long, the Mongolian hordes are at the PerformancePoint gate.
Many of these points are covered already in this blog, but Dear Reader, let’s face it; a man only gets a few good ideas in a lifetime, so one must expect some repetition!
Check #1: Existence
Does another existing report or spreadsheet cover the perceived requirements, fully or partially?
A no-brainer, but has to be asked
Check #2: Compliance
Will reporting these data and information complicate the Corporate regulatory situation in respect of SOX and similar? Are there security issues relating to the data to be purloined, massaged and disseminated?
This is probably best ignored by the average DIY BI Rogue, except in a bank or some such place where spooks abide. Worry about it when a result is to hand?
Check #3: Iterations
Irrespective of your confidence in your spreadsheet skills and all other aspects of this BI project, be assured that it will require several iterations of specification, build and test before the result is deemed adequate, or other issues supersede the whole episode.
Plan on starting simple; and increase complexity and report niceties in subsequent iterations.
Check #4: Specifications
This is where it is all at. Do this right and it will be fine, ignore it and a mess will result. Make sure you have a specification for each iteration. A whole treatise can be written here, but see for example, Dear Reader, if you want detail look here.
It is self-evident to say that you need to know what information is to be provided, the data required to obtain the information and the transformations needed to convert data to information. Don’t start without at least this. See Check #6 for suggestions on presentation, but they can be later iterations – get the data and basic transformation going first.
Check #5: Know your data
Knowing your data implies – metadata, lineage, update schedules, dimensions, planned amendments. My tool to do this is described here.
Just because a cube has the data you want today, doesn’t mean it will be there tomorrow, or that the update schedule is right for your specification. Don’t waste a lot of time on MDX expressions that will only work on Thursdays to Mondays, because that’s when the update cycle is complete.
Check #6: Presenting results to aid assessment
Part of the specification task, but best left to later iterations, is the design of result presentation. I don’t mean graph versus table versus bar charts, this is relatively trivial. What is important is the way the raw information obtained from the data transformations is pre-analyzed to aid the assessment of implications. This is the point where the amateur and professional, or competent, DIY Rogues part company. Chalk and cheese has nothing on this differentiator.
Again there’s a treatise here, but basically the conscientious DIY BI Rogue should be aware that he/she can offer at a minimum:
Goal Variances (exception reporting if you will);
Benchmark Comparisons (actual versus budget, plan or anything reasonable);
Trend Analysis;
Forecasts (based on time series of the data, if it’s available of course)
Drilldown (more detail about a context, provided the narrower dimensions are in the data cube)
Check #7: Validation
Even DIY Rogues should be aware that the non-numeric data associated with supposedly factual data is important. By this I mean the comments, previous assessments, opinions, suggestions, etc. that relate to this sales or gross margin figure. My more complete and earlier exposition is here.
At a minimum, the subject expert who can offer clarification and amplify context for a number should be identified as part of the reporting. Links to team comments, forecasts, etc are probably beyond the scope of your average DIY BI project, but keep them in mind for later iterations.
See, it’s not that hard!
Collaborative BI Implies a Personalized Grapevine – but, make it Smart Alerting or its all Blah! February 12, 2007
Posted by Cyril Brookes in BI Requirements Definition, General, Issues in building BI reporting systems, Tacit (soft) information for BI.3 comments
Effective collaboration depends on the dynamic creation of groups that can exchange and share intelligence. Collaborating people in a group create knowledge; often it is new knowledge that can improve business performance. However, finding the right group participants, and disseminating the knowledge to empower action, both require targeted, selective dissemination, of information – that’s personalization. Truly, I heard it on the grapevine!
Some regard personalized alerting in BI as creating a “market of one” for information..
I disagree. As I see it, it is creating a group of relevant people, the “A list” if you will, for the issue at hand. How can this happen, not occasionally with serendipity, but routinely? Groups must be dynamic, different for each issue, expanding and contracting in size as the issue grows in importance, or declines.
Markets of one work for marketing situations, e.g. books with Amazon.com, but I don’t believe it is the paradigm for collaborative BI.
Clearly, the traditional BI report, with information prepared by others submitted to potential decision makers is discredited. Today we have lakes and lakes of information available; Herbert Simon got it right in 1971: “Information abundance creates scarcity of attention”. And one can add: Knowledge poverty.
Informing decision makers doesn’t cut it anymore. Maybe it never did? We need to change the process, introducing dynamics to the grapevine.
Issues grow in business importance when people, in the know, determine they have grown in importance. There’s no other way.
All messages, ideas, news items, etc. on a topic are not of the same value or criticality to a business. Most are irrelevant to decision makers; they are waffle, padding, dross, blah.
Some of those items will be interesting to the professional; fewer are important, business-wise; but very few are critical to the business. How do we distinguish? Well, it’s simple: subject experts tell us they’re critical.
If you’re still with me, Dear Reader, personalized alerting, selective dissemination, of intelligence items on a topic can only be effective, therefore, if someone tells us (or the dissemination authority/process) what is important and what is not.
I don’t believe that automated importance classification works in practice – in a business anyway. It might do for spooks, but not the rest of us.
Some years ago, I built a selective dissemination collaboration system based on a patented importance escalation process. I called it grapeVINE. It employed this model of escalation and dynamic audiences for information. It was most effective when seeded with news, marketing reports, or other items. They were automatically classified, using a standard taxonomy or vocabulary, and selectively disseminated based on client interest profiles.
grapeVINE’s special character emerged when a subject expert commented on an item, raising it’s importance level – saying something like “this is important because the implications are….”. Immediately the audience would increase for this, and only this, discussion thread. More people are interested in important stuff than dross. One of these new recipients might then escalate the discussion further, bringing in more people – likely action oriented players. Then the game is on.
Two dimensional personalization of business intelligence, based on a combination of subject matter and importance to the business, is an effective driver of dynamic group formation.
Provided the culture of sharing is established in the business (and that’s an important IF), the potential for improvement in decision making is immense. It is the optimal vehicle for combining structured (numeric) and unstructured (text) information into BI systems.
Paraphrasing Crocodile Dundee: THIS IS A GRAPVINE!
Specifying Boardroom BI: Helping Directors Find Problems for Executives to Solve? November 19, 2006
Posted by Cyril Brookes in BI Requirements Definition, Boardroom BI, General.add a comment
I believe there’s a lack of focus on Boardroom BI which reduces corporate performance. In my experience, the phrase Boardroom BI has no obvious connotations to most business analysts. It doesn’t show up on the BI project radar. Everyone knows that executive BI reporting includes performance monitoring, CRM, ERP analysis, and financial benchmarks. But they rarely have any awareness of what comprises effective information reporting for non-executive directors.
If you’ve read my last post, you’ll know I believe that key concerns for the independent board member range from assessing risk to proposing new ideas and executive performance analysis. Apart from a necessary awareness of enterprise status, their BI emphasis is on finding and assessing potential problems that may impact shareholder value.
When creating any BI specification, I always try to understand the mental models used by the target executives (or directors in this case) to make their decisions. In turn this requires an understanding of the business processes; or, more accurately, an understanding of the business processes as they are envisaged and employed by the targets.
The optimal information reporting of the target executives ought to service these mental business process models; Chris Argyris called them “Theories-in-Use”. Presumably in contrast to the “Theories-not-in-Use” held by others in the business that don’t make decisions (but wish they did?).
It’s obvious, at least I think it is, that independent directors don’t have detailed mental understandings of the enterprise business processes. Executives should have this detailed mental model, but not part-time advisors. The directors’ focus is normally on representing shareholders’ interests, protecting the enterprise from excessive risk, and monitoring the performance of senior executives.
It follows, if you’re still with me, that loads of numeric facts that may be useful to a divisional vice-president are not high on the list of required information for independent directors. What they need, to feed their mental models, are combinations of fact plus commentary that focus on their principal concerns.
My approach to BI report specification distinguishes between information required to give the recipients:
- Awareness of current status; i.e. comfort that they know what is happening in the business, enterprise wide
- Ability to find problems; i.e. situations that need a response, and
- Capability to solve the problems when they are found.
Now, non-executive directors don’t have to solve problems, or they shouldn’t. But they do need to be aware of significant enterprise-wide issues, their significance, and especially any issues that pose significant risk. Specifying BI for the boardroom, therefore, requires an approach like the following:
Comfort and Awareness information – routine report formats:
Directors do not have the same detailed understanding of the business processes as executives. They will, therefore, have difficulty with absolute numeric data, e.g. Sales were $450,000, Inventory is 568,000 units.
Instead, their summary reports (Stafford Beer’s “Attenuation”) should emphasize relativities, e.g. Sales were above plan by 10% at $450,000; Inventory fell below plan by 15% to 568,000 units. Further, numbers like these mean little without the accompanying commentary soft information that qualifies them, and places them in context, for example:
“Sales were above plan by 10%, due mainly to there being 5 Fridays in the month, and several customers place orders on a Friday”; or
“Inventories are lower due to production downtime caused by routine plant maintenance”
The objective clearly is to give the directors enough information so that they understand adequately where the enterprise is in terms of current and likely future performance. The actual requirements for routinely presented “Comfort” information to non-executive directors is ideally determined following structured interviews or workshops that canvas the available KPIs – such as those I outline as part of the BI Pathfinder methodology.
I don’t think it’s worth your time, Dear Reader, my expanding on this. Either you accept that not enough thought currently goes into Boardroom BI, or you don’t. If you do accept my premise, then really the solutions are simple, just avoid the mass of detail, and concentrate on comparative data and include many comments from subject experts.
Problem Finding and Risk Identification – the directors’ main game
If enabling independent directors to be aware of enterprise status is important, and it is, then facilitating their problem and risk identification is critical. Of course, some CEOs and Executive Chairmen may not want this latter capability to exist! But, I jest; I don’t believe this is the prevalent attitude, and if it is, then you should quit.
Obviously, variations from benchmarks are indicative of potential performance issues, depending on the implications apparent in the accompanying commentary. Finding a problem is therefore a corollary of becoming aware of status. But there’s more to it than this.
In addition to benchmark relativities, independent directors will usually find benefit in enterprise wide exception, trend and time-series analyses. This is because their limited understanding of the business does not normally allow them to project future performance issues from current data in the same way as executives can.
What independent directors do have, or should, is a wide range of experience with business situations generally. Therefore, they are often able to spot potential generic problems or opportunities long before the enterprise data will show up the specifics. In many cases, this is their principal reason for appointment.
Hence, my emphasis on the importance of exception reporting based on trend and time-series analyses. Creativity on the BI designer’s part is the key to success here. Beyond highlighting the value of these types of data mining, I won’t indulge in specifics, since every corporation is different, but the objective is the same: to identify situations that diverge, or are diverging, from planned or acceptable performance.
Nevertheless, the most fruitful source of problem and risk identification for directors is, in my view, soft information about corporation events and important issues, industry trends, government regulatory compliance, plus major customer and competitor trends. It is in this context that the wider experiences of directors will enable discovery of potential issues. Therefore, any BI specification for directors ought to include ensuring that they are fully informed about happenings in the company; compliance issues, the industry, its dynamics and milestones; relevant and significant blogs; plus analyst commentary and forecasts.
Diagnosis Support
Conventional BI reporting specifications will include problem solving support, as discussed in my blog post of August 27. But directors aren’t normally hired to solve problems, they exist to represent shareholders, and protect shareholder value.
So what do non-executive directors think about when they believe they’ve identified a problem, or substantial issue? The executive would reach for the Drilldown button. Normally, the non-executive director will reach for the phone, and call the CEO or other nominated contact person, and ask.
But if solving the problem isn’t a role for directors, diagnosis is. Will this HR dispute affect shareholder value? What is the worst thing that can happen with this union dispute? Can we live with that? What data do I need to compare this competitive situation with what happened last year in the automobile parts business?
Once again, I stress that the commentaries of subject experts and industry analysts are a major part of the directors’ diagnosis process. It’s inescapable. They want to know: What happened last time? How was a similar issue resolved in another industry? Who is the guru on this compliance matter? These are immensely valuable insights that can enable a director to save the company from huge consequences.
BI for the boardroom is much more important than many companies treat it.
Boardroom BI – It’s Different from Executives’ Corporate Performance Reporting November 7, 2006
Posted by Cyril Brookes in BI Requirements Definition, General.2 comments
A colleague has asked me to comment on the issues in building business intelligence systems to support the independent directors on a company board. He sits on three boards, and is disappointed with the information he is routinely given to support his role. These are companies with quite advanced executive BI systems. Specifically, he says the reporting he receives has too narrow a focus, and is all numeric – mostly divisional rather than corporation wide. He finds it difficult to assess risk, and to determine implications for shareholder value.
Any review of the available papers (I hesitate to call it literature!) on BI shows that information requirements definition for the boardroom is a much neglected area of Business Intelligence theory and practice. Specifying these needs is complex because the independent directors do not have the same set of objectives and concerns as their executive colleagues. Boardroom BI often is simply a regurgitated subset of routine profit center executive reports.
The usual excuse is lack of time to meet board meeting deadlines, but in my experience the hassle of a difficult board meeting caused by lack of adequate information warrants a large amount of effort in preparing appropriate information reports. In this area there is no substitute for quality. There are usually three main players to this equation, the independent director(s), CEO, and Chairman plus the BI analyst/consultant charged with providing the synthesis.
It is a non-trivial task to manage the competing interests, and create what is best for the business (however that’s defined!). Although each situation is different, there are some consistent themes that may be used to build a useful specification.
I’ll offer my prescription later, but first want to discuss the cultural and business issues that drive the reporting needs. Obviously it is the independent directors’ reporting requirements that are the subject of this discussion. The CEO and an Executive Chairman will normally be served by a conventional BI specification – my posts of August 27 and July 28 summarize my approach to specifying executive reporting.
The CEO and other executives have a focus on KPIs, performance metrics, and progress against plans or other benchmarks. Their needs are the main driving force behind data warehouse design, data modeling, cube specification, metadata documentation, etc. This is the mainstream of corporate BI and is certainly over-serviced by software marketing, research and the plethora of white papers.
Independent directors’ information needs are obviously related to their perceived role on the board. They are not executives, they don’t make corporate decisions individually, and their knowledge of the business process models is imprecise. They always want to contribute where they can to the enterprise, but their shareholder responsibilities often drive them to have a risk assessment fixation, especially since the Enrons and Sarbanes-Oxley.
These different objectives are the source of the conflict between optimal executive and boardroom BI specifications, and the need for boardroom BI to be considered a special project.
Independent directors’ concerns often include:
Overall corporate performance relativities
It is extremely difficult to judge absolute values when you don’t fully understand the business process. So comparisons, and relativities, are essential guides to performance assessment. Benchmarks of value to the independent director will often be different from conventional CPM actual versus budget and last period. They include industry best practice, competitor comparisons, and changes in target plans. Trends and forecasts are more valuable than historical analyses. This type of reporting is usually unavailable.
Pre-digested assessments
Probably the biggest BI related complaint I hear from independent directors is the lack of commentary on the numeric performance figures. They clearly look to the executives for guidance on implications for the business from the metrics. Numbers that look bad can really be good if special circumstances are considered, and vice-versa. To the director, the executives are the subject experts and they should advise on implications along with the supplied numbers. All too often, however, the numbers are provided without any commentary.
Identifying and monitoring potential risk of downside for the enterprise
Risk identification takes up much of the independent director’s mind-space. Downside protection for the enterprise, and its shareholders, is a major preoccupation. Regular readers will know that I believe soft information sources are the critical resource for identifying potential problems, be it competitive intelligence, customer relationships or almost any form of risk. Any complete boardroom BI specification will focus heavily on risk, and this must include marshalling the soft (tacit) information resources.
Corporate image and community positioning
Independent directors are often more conscious of, and influenced by, community attitudes than corporate executives. They are also likely to have a wider personal network that is the source of sensitivities and inter-relationships unknown to professional managers. They will want to be aware of events, issues, and plans that have had an impact the corporate image, or have such potential, to a greater extent than their executive colleagues.
Human factor analysis
Directors are always concerned about the human factors that influence the business. The relationship between the CEO and Chairman is the most important by far in any enterprise. However, the quality of the interaction and mutual cooperation between and among all senior executives will be of great significance – since these factors are often the source, or an indication of presence, of risk and potential loss of shareholder value.
Shareholder value preservation
At the end of the day, as they say, the independent director is responsible for enhancing and protecting shareholder value. There is no BI report that can address this specifically, but the directors’ task will be made much easier if we can satisfy the other concerns through intelligent, effective, information reporting.
In my next post I’ll summarize how I approach boardroom BI specification, taking the above as guidelines.
Managing Cultural Barriers to Effective Collaboration; Enabling Action Oriented BI for CRM and Competitive Intelligence October 26, 2006
Posted by Cyril Brookes in BI Requirements Definition, General, Tacit (soft) information for BI.4 comments
In previous blog posts I’ve opined on the cultural barriers impeding knowledge sharing and limiting BI effectiveness in these and other application areas where decision making depends on information about the future probabilities, rather than historical fact. I proposed a “Top Ten” set of reasons why routine collaboration on these issues is difficult to instill in the professional employee’s mind.
I also outlined my assessment of the nature of the soft, or tacit, information resources that contain the intelligence, or perhaps the knowledge, that must be marshaled into the BI context if a successful CRM, CI or other subjective decision support system is to be created.
For completeness, these top ten and categorizations are reproduced here:
Culture barriers that compromise the collaboration instinct:
- You (not actually you Dear Reader, but those other unwashed professionals!) don’t want to start a debate you cannot control as it evolves
- Tall poppies lose their heads, so keep your head down
- Messengers, especially whistle blowing ones, get shot – or have short careers, so be silent
- There’s no important person around to hear what you have to say; so keep this intelligence to yourself until there is the right audience – the more valuable it is, the longer you’ll wait.
- You don’t want to embarrass your boss, or peer group, so keep it quiet
- You’re not sure that the intelligence is correct, so just in case, keep it to yourself so you don’t lose “face”
- You’re reluctant to communicate with people you do not know
- You don’t know who to tell, and it’s a lot of effort to find out
- There’s no reward mechanism for contributing intelligence, and it’s a lot of work for no personal benefit
- Your boss will only steal the idea, so don’t even think of telling
- Tall poppies lose their heads, so keep your head down
I know of three categories of soft (tacit) information in my experience. These form the basis of my soft information metadata categorizations:
- Independent Items: stand alone intelligence, e.g. rumors, ideas, industry gossip, leaks from competitor or customer sources, etc.
- Comment, or Qualification, Items: e.g. assessments of a competitor’s new promotion, comments on sales forecasts, qualifications of opinions on a prospect list, etc.
- Reference Items: Lists, with quality assessments, of subject experts or other resources that can supply details or opinions on hard or soft data or events. These cultural barriers and intelligence categories summarize the problem. They also hold the key to effective synthesis of BI design and management strategies that will ameliorate the situation adequately.
- Comment, or Qualification, Items: e.g. assessments of a competitor’s new promotion, comments on sales forecasts, qualifications of opinions on a prospect list, etc.
What, then, are the guidelines leading to effective synthesis that mitigates the culture issues? I divide them into three categories:
- Collaboration rules set by the enterprise
- Subject Expert panels and their operation
- Code of “good collaboration practice”
- Subject Expert panels and their operation
Setting the corporate agenda for collaboration
This is a set of suggested “not-negotiable” rules for establishing instant messaging, chat, different time/different place conferencing, etc. in the enterprise. They are based on my experience with several hundred installations. Of course, they may not be relevant to your business. If I sound dogmatic it is because I have seen so many failures that could have been avoided.
- Categorization, Nazi style: Information that is not categorized cannot be shared effectively in any group over 20 people. Automatic categorization is probably essential for any business unit of reasonable size. Categories used should be drawn from a restricted vocabulary, and synonyms should be banned, or actively discouraged. See my earlier post on Vocabularies for sharing tacit information of September 14.
- Importance Qualifiers: Subject based categorization is insufficient by itself for effective content based dissemination. There are simply too many items on most subjects. A “value to the business” indicator is also required that can be used in search queries and personalization profiles. Most professionals want to receive important items on a subject, possibly even all high importance items irrespective of subject matter,.
- Rewards for Added Value: It takes time and effort for a professional to submit tacit information, especially when it’s related to CRM or CI. Plus there is all the downside potential listed in the above “top ten”. There must be a reward system in place to encourage participation. This requires regular monitoring of the system, and may include public acknowledgement of valuable contributions. The options for rewards are many, and I won’t dwell on them here.
- Seed Items: The most laborious task in contributing soft business intelligence is introducing the context. I have found that often using news feeds and other automatic sources can stimulate the contribution of ideas and assist in recalling intelligence items.
- No Anonymous Items: Intelligence must be owned by the original contributor. This is essential to limit submission of garbage, provide rebuttal opportunity if needed, and especially to assist with assessment of the value of the contribution. The author’s identity is often the best guide of value and importance to a reader.
- Use Subject Experts: This is a critical element. These specialists are essential if the “wheat” is to be separated from the “chaff”. Their role is discussed in more detail below.
- Facilitate Work-shopping of Ideas: Many professionals are reluctant to expose half-formed ideas to an enterprise-wide audience. It should be easy to form dynamic, short life, or long life, workgroups that can refine a proposal before it is released to the “world”.
- Importance Qualifiers: Subject based categorization is insufficient by itself for effective content based dissemination. There are simply too many items on most subjects. A “value to the business” indicator is also required that can be used in search queries and personalization profiles. Most professionals want to receive important items on a subject, possibly even all high importance items irrespective of subject matter,.
Subject Expert Panels
Filtering of soft information is essential to enable appropriate impact and action assessments. On first receipt of an item, of whatever type, subject analysis is probably the only useful action. I have little confidence in the automatic importance assessment tools available, but maybe I’m old fashioned. They may be appropriate in slowly evolving contexts, but not in most businesses.
I believe that only a subject expert can consistently validate the importance and urgency of a raw piece of intelligence, especially in the CRM and CI environments which are so dynamic.
Suggested Subject Expert Guidelines:
- More is better; experts should only be required to cover a few narrow topics. More than one expert per subject is usually beneficial if the topic is important enough.
- Avoid self-appointed experts; there should be a formal approval process
- Experts should be empowered, and encouraged, to add value with text as well as escalating value/importance and adding new keywords if appropriate. Often the original keyword categorization will not be appropriate, or there will be cross enterprise implications only apparent to the expert.
- Avoid self-appointed experts; there should be a formal approval process
Code of Good Practice
Guidelines for collaboration behavior are obviously desirable. Suggestions include:
- Reward and endorse good behavior, ignore bad behavior. “Flaming” generates ill-will and ought to be discouraged. Judicious use of importance escalation is usually effective, and people rarely read routine low importance items on a subject.
- There should be no adverse reaction to items submitted at routine low importance on any subject. The relevant Subject Expert will be able to assess the utility or otherwise of such an item, and escalate its distribution if appropriate, or let it die otherwise.
- Obviously repetitive dysfunctional behavior should be dealt with. But this includes efforts to “shoot messengers”.
- Knowledge creation through idea building should be encouraged, rather than creation of new independent items. Piggy-backing of ideas is important. Retention of original ownership of ideas is important, to encourage participation. If someone adds value to an idea, they should get value for the addition, but not the original concept.
- There should be no adverse reaction to items submitted at routine low importance on any subject. The relevant Subject Expert will be able to assess the utility or otherwise of such an item, and escalate its distribution if appropriate, or let it die otherwise.
There are several collaboration packages available that facilitate implementation of these guidelines, for example that offered by Sun Microsystems Inc. The hard part is setting up the environment, not choosing the package!
That’s about all I can offer on this topic – good luck!
Drilldown specification in BI– it’s harder than the demo makes out August 27, 2006
Posted by Cyril Brookes in BI Requirements Definition, General, Issues in building BI reporting systems, Stafford Beer.3 comments
We’ve all sat through those glitzy demonstrations of canned detailed reporting – solving hypothetical problems that may never exist in practice, or if they have existed, will never be repeated again in the same form.
Drilldown is, in my opinion, one of the hardest aspects to specify and implement effectively in a BI reporting system. Unfortunately, it is also probably the most hyped “silver-bullet” keyword of BI software marketing speak.
You cannot build a detailed report for a problem situation that doesn’t yet exist. Even if the type of problem, say a debtor’s default, is predictable, the specifics will always vary. You can only create an environment to make such reporting easier.
Further the nature of that reporting environment is often complex, involving hypothetical database specification and modelling capability – as I will discuss in a later post.
Drilldown is, of course, a modern descriptor for part of Stafford Beer’s Amplification concept.
In my posts of July 7 and July 28, I introduced and discussed Stafford’s distinction between Attenuation and Amplification reporting in the corporate BI context. In summary: Attenuation reporting is pre-specified and pre-formatted reporting of information that empowers executives:
- To be aware of, and able to assess the implications of, the current state of the business, and
- To be alerted to actual or potential unusual or unacceptable situations.
Or more colloquially: Where are we? What is good and bad about where we are? What is unusual or forecast that I need to know about?
Therefore, Attenuation style reporting makes executives comfortable they know what is happening in their part of the business, and that they are alerted to any problems that can be discovered from the data available. Amplification reporting is more difficult to pin down, since it is only required when a problem, or apparent problem, has been identified.
If Attenuation is about finding problems, Amplification is about solving them.
By this definition, then, Amplification reporting – or Drilldown if you prefer the current term – is difficult to pre-specify or pre-format because we cannot be sure of the exact nature and context of the problem.
In the good old/bad old days of this technology, we used the terms Executive Information Systems for the first type of reporting, and Decision Support Systems for the second. Now it’s all encapsulated in the BI terminology. The names change, but the issues remain the same.
But I diverge.
Drilldown has three basic objectives, as I see it, drawing from classic decision theory – as per, say, Herbert Simon. It is to empower our client executives to: Diagnose the problem/opportunity we have helped them find (using Attenuation reporting). How bad is it? What will happen if we do nothing?
For Diagnosis support, the minimum requirement is more detailed data. Exactly how more detailed, and over what time periods, can only be determined through appropriate research and interviews with client executives. However, models that can answer “what-if” queries, and statistical analysis tools may also be valuable.
Determine the available options for solving the problem – or capitalizing on the opportunity
Options may be selected from past experience, or suggestions from experts. Support for this aspect of Drilldown is often based on knowledge sharing and tacit information management tools – see my post of July 27.
Assessing the implications of each of the apparently viable alternatives
Feasibility validation and outcome assessments of options may require pre-specified models, or at least partly constructed versions that can be adapted to the problem situation when it is known. Assessments of the anticipated outcomes of the viable alternatives are often the key information elements required to support decision making and the BI system should include these if at all practicable.
Many people think that Drilldown is only about getting more detailed data, but clearly the client executive is likely to want more – just like Oliver Twist. A quality BI environment design will go much further as discussed above, but at least will extend to a full review of what that ”more detail” should be, and how it is to be collected for inquiry and ad-hoc reporting.
After all that, it’s up to the executives to judge which alternative is best, i.e. make a decision.
I will cover these Drilldown component steps in more detail in a later post. If you want more detail immediately, you can see how these concepts are implemented in the BI requirements methodology at www.bipathfinder.com and how the metadata that supports the method is documented at www.bidocumenter.com.
Your comments on the accuracy and utility of this material are welcome.
BI implies passivity – we need action oriented reporting, bring back KM? August 12, 2006
Posted by Cyril Brookes in BI Requirements Definition, General, Issues in building BI reporting systems.add a comment
BI used to be KM in the management consultant marketing speak. Let’s bring back KM – BI is becoming too passive. Knowledge Management was our buzzword during the late 90s. Trouble was, no one seemed to agree on what it meant. I blame the software vendors for this shambles. KM was the new corporate must have and so every piece of reporting software, from ERM to spreadsheets, became a KM product.
As is usual in this situation, we changed the name, this time to BI. Today, we often see a BI system defined as comprising principally: Corporate Performance Management ERM Customer Relationship Management Competitive Intelligence This seems to suit the software vendors, as they can fit about anything into one of the above categories.
We are missing something, however, that was a key part of the initial Knowledge Management movement, before it was taken over by the marketers.
Herbert Simon once wrote:
The impact of information is obvious. It consumes the attention of its readers. Therefore, a wealth of information creates a poverty of attention.
So often BI is seen as a reporting tool, and BI designers and software has but one objective – Put information in front of executives so they can make better, more informed, decisions. But I believe it doesn’t work like that; executives are time poor and need, in fact deserve,much help to determine what is important, what signifies a potential problem, and what the implications are of the current status. To me, that’s what Knowledge Management was, should be, all about and therefore it’s what BI should also be.
As BI professionals, what can we do about it in our projects and designs? Here are some of the most important issues I believe we face to empower our client executives to perform at a higher level – BTW: I hate the word user in this context.
Empowering effective individual knowledge work is the most important objective. So often the corporate culture is focused on finding the right number or document, rather than the right person, with marginal result.
Practice check 1: We need to put each KPI, metric or measure in front of the right person, PLUS we should identify the expert who will explain the significance and implications of good and bad numbers or documents.
Executives need to need to distinguish between numbers and documents that are significant and those that merely detail or cover a nominated KPI or topic, but are not useful.
Practice check 2: We must know what rules, tacit or explicit, our client executives employ to decide substance, significance and need for response. And/Or, make the system adaptable to meet the changes in these.
The more senior people obviously have to monitor and contribute to broader business performance and strategic areas. They will therefore want to focus on the more important issues, and not be burdened with detail that is not about something significant. Yet, when something is significant, they need much more, fast. What is the more and where is it?
Practice check 3: While this is an obvious requirement, it is very difficult to implement, in my experience. For the BI designer, it comes down to two basic issues: (1) establishing, ex ante, the degree of detail required for drill-down when certain criteria for significance are met, and (2) making it easy to identify and reach the subject experts for each area.
People with high levels of expertise can leverage their contribution to the corporation through collaboration on issue assessment and a process of issue escalation. Leveraging expertise involves sharing the results of problem assessment and creative work among those who will benefit.
Practice check 4: It is a part of the BI designer’s role to ensure that the right people can be brought into the problem solving loop.
Knowledge enabling response to a problem or opportunity is usually not recorded, it is created dynamically as issues are identified, assessed, debated and resolved. Notification about an adverse assessment of data, messages, queries, etc. from an information repository will often trigger creation of more explicit and communicable expressions of knowledge via expert discussion.
Practice check 5: This is the nub of knowledge management, as I understand it. Clearly we cannot achieve KM unless our BI systems recognize both the hard and tacit information resources, allow access to subject experts and promote the recording of the knowledge created as a result.
These five checks on the specification or implementation of a BI environment will materially help you determine how action oriented your systems are.
