Lou Gerstner, the now mythological CEO of IBM that many still miss, wrote an excellent book about his tenure as IBM's CEO, much of it is dedicated to his organizational culture battles. The most famous quote from Gerstner's book is: people are doing what they are inspected to do, not what they are expected to do.
This is indeed true in IBM until today, but IBM is just a reflection of the western culture, in which anything is weighed and measured, the metrics are intended to achieve some goals, but get a life of their own, often not keeping close contact with the original goals. Furthermore, people find creative ways to satisfy the metrics in ways that have nothing to do with the original goals, since satisfying the metrics become the goal.
Some examples: In Israel the traffic police guys are measured by the quantity of traffic violation ticket they get credit for. I remember many years ago that I've committed some traffic violation (turned left in a place in which turning left was forbidden between 7-9am, it was indeed a few minutes before 9am), a police car that was quite far saw me, and then started a movie-style chase, the police car not only turned in the forbidden way, but traveled in the opposite side of the road, turning the traffic to stand in the side, and drive in a way that was very dangerous to the traffic, and when they caught me they wrote on the traffic violation ticket" -credit XXX(name)". Hope that the reward for the credit was worth the effort!
Other examples: One of the previous "legal advisers to the government", a position that in Israel is among other things that head of the state prosecution, wrote in his autobiography that he had again and again to remind the prosecutors that their goal is to ensure justice, however, since they are measured by the percentage of conviction, while they have decided to prosecute a person, they cannot back off, it will spoil the statistics. More examples from the education system: I have talked once with somebody who dealt with admission of graduate students in one of the best business schools in the USA, he told me that sometimes they miss students that some indications (and faculty members) show they can be exceptional, but their score in the GMAT is not that great, it is virtually impossible to pass these candidates through the admission committee, since it would spoil the statistics of minimum and average of the admitted students, and this is a metric that the business school measures itself against other business schools. More in the educational system - My long term observation is that for many of the students the goal is maximize the GPA, and gaining useful knowledge becomes secondary, thus elective courses popularity is often determined according to the past statistics about grades distribution. One of my students had a special talent to know how to learn to exams, get very high grades, and not remembering much a week later. According to the metrics he won -- he was on the president list. This talent still helps him in his life. Getting to the business world, the fact that corporations that are traded in the stock market, are measured by Wall Street analysts quarterly on accounting measure (Earning per Share) has a major impact on how the business world behave, first considerations are often short term (due to the quarterly metrics), and second, accounting thinking is not always consistent with economic thinking, furthermore, it enforces some low common denominator in the behavior of the business world and reduce variance in goals and natures of companies.
While metrics are not necessarily bad, there are two observations about them:
- There should be constant check whether the metrics still reflect the goals, and whether those who satisfy the metric do it in a way consistent with the goals - and adjust the metrics (or the goals) to avoid misuse (same kind of thinking as "fraud detection").
- There are cases in which goals are not translated well to metrics, or there are exceptions that are consistent with the goals, but not with the metrics -- people should be brave enough to stick to the goals and ignore the metrics (or handle them later).
I started with quote from Lou Gerstner --- which I see as one of the cornerstones of my own behavior, over the history I had several times "motivation talks" with people instrumented by metrics to advise me how to behave, and I'll end with another phrase I like , which I use for this people: My behavior is driven by a a compass and not by a weather wane"
The credit for this idea goes to my colleague Zohar Feldman.
A good way to illustrate the proactive idea is to watch the video clip from the movie NEXT,
In this movie Nicolas Cage acts like a person who can see two minutes into the future, in the clip he is trying different alternatives how to approach a woman he is trying to pursue, understanding why they fail he improves it until success is achieved. This illustrates the proactive idea: event happens, their consequences are predicted and a decision what to do in order to achieve some goal should be taken. There might be different decisions, but we need to predict the consequences of these decisions and make the best one that will get us to the desired solution. Enjoy!
There have been some visible floods in recent years, like the one in Australia. Prediction of the course of floods can be tricky, since rivers can have multiple splits. Today IBM announced that IBM Research together with UT Austin a prediction model to predict the course of flooding. This combines IBM analytics research with UT research in the physics of rivers.
Note that disaster management is an area where proactive computing hold significant potential, however in order to realizing this potential, strong prediction abilities are required.
To complete the presentations list -- another interesting presentation from RuleML'11 (the first out of two) by
Alex Artikis and Nenad Stojanovic talking about AI approaches to situation detection and remaining challenges.
I have written before about temporal databases in this Blog, and in general I worked on temporal databases around 15 years ago, and co-edited the book whose cover is shown here in 1998. Temporal database is noted by the fact that academic people tried to drive standard in this area: TSQL2 lead by Rick Snodgrass and his colleagues. At that time it did not succeed since none of the DBMS vendors had an interest to see it as a high priority, these were the days were the Internet emerged along with XML, and the DBMS vendors had many other things to worry about. However over the time some DBMS vendors have adopted temporal capabilities within their products. Oracle already implemented temporal extensions supporting TSQL in its DBMS product. Recently IBM produced its own version of temporal database within DB2. It seems that there is now traction for temporal databases in various industries. Today my colleague Guy Sharon attracted my attention to a new article on IBM DeveloperWorks entitled "going back in time" describing the DB2 temporal capabilities, the traditional dimensions in temporal databases: transaction time and valid time got converted to new names: system time and business time (I make a note to write a post about the overuse of the term "business" ). These two dimensions enable to ask queries like: what was the value of a certain attribute in 7/7/2011, as observed from 8/8/2011. This can have different answer from the observation time of different days, since the knowledge about the past is changed in time. While the title of that article talks about "going back in time", and indeed using temporal databases is typically viewed about recording the past, temporal databases can also be used about recording the future, this was noted in a work published in 1994 by Arie Segev, Avi Gal and myself entitled "retroactive and proactive database processing" (I don't think that online version is available). Since we are dealing over the last year in proactive event-driven processing, the issue of looking at predicted future events that can be revised with time is very useful, and we are indeed looking on temporal database techniques for that. More on that - later.
I am reading the book "Managing event information" by Gupta and Gain, which is part of the series of short books by Morgan&Claypool synthesis lectures series. The authors, professors from U.C. San Diego, and U.C. Irvine, have concentrated in the modeling of events, the illustration below was copied from the book to demonstrate the flavor. The book starts with an introduction and running example about news agency, it also defines the setting of various types of events: spatio-temporal database events, sensor events, multi-media events (video, audio). Chapter 2 deals with "Event Data Models" starting with temporal database as a tool for event modeling, such that the temporal database represents the collection of states, while event is any transition in any state (value change), then it moves to discuss conceptual temporal models and discusses E* - a graph based event model using RDF and ontologies. formalizing E* and showing some example of modeling using E*. It discusses several modeling constructs such as disjointness (causal or temporal) of events; coverage; ordering' lifespan and spacespan of events, and constraints on graph relationships, such as follows, sub-class etc.. In chapter 3 the book discusses the implementation of the event data model; the illustration below is a UML diagram showing one of the supported patterns - events that participate within a situation, there are other patterns supported such as causality. Later it discusses storage model of various types of events. Chapter 4 is entitled "querying events" and discusses the possibility to query a collection of events. Example of queries are: spatiotemporal queries such as: "which meetings are scheduled in this hotel today after a certain talk", which looks like a regular query in spatiotemporal database, the queries can also support aggregates (looking for frequent meetings with a certain characteristics), and hierarchy, expanding to sub-events. It can also query continuous events, graph relationships etc -- these queries seem to be the same as queries on spatiotemporal and graph databases, except he fact that the database represents events. Chapter 5 brings a major application of the event model - the creation of a story based on the event model. The storytelling is of multimedia type, a thread of research that follows Brooks' paper.
Kevin M. Brooks: Do Story Agents Use Rocking Chairs? The Theory and Implementation of One Model for Computational Narrative. ACM Multimedia 1996: 317-328
The book is summarized with some applications, conclusion and references.
The E* model is interesting in the sense that it shows various relationships among events, and enable to get observation on the events and their relations to states. Since there are no standards in this area, the terminology used in this book is sometimes inconsistent with other publications in this area, but it is generally clear. The book proposes a holistic approach of event modeling, claiming that current event modeling systems are looking isolated aspects of events and cited the famous metaphor on the blind men that touch an elephant from different points, I have used this metaphor talking about misconceptions about event processing.
It still remains to be seen whether such models will penetrate the real-world systems.
I'll give as a project topic in my event processing course more investigation of E*.
