from DSSResources.com

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                          DSS News
                     D. J. Power, Editor
             December 8, 2002 -- Vol. 3, No. 25
         A Bi-Weekly Publication of DSSResources.COM

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         Check article "Competitive Intelligence  
          Software Applications" by Arik Johnson
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Featured:

 * Ask Dan! - When is "real-time" decision support desirable 
              and needed?
 * What's New at DSSResources.COM
 * DSS News Releases

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            Happy Holidays from DSSResources.COM
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Ask Dan!
by Daniel J. Power

When is "real-time" decision support desirable and needed?

My Ask Dan! column in DSS News (Vol. 3, No. 24) titled "What is 
'real-time' decision support?" struck a chord with some readers. This 
column is a follow-on, expansion and discussion stimulus on the topic of 
"real-time" decision support. The following "answer" draws extensively 
on email comments from Nigel Pendse and Marc Demarest. Nigel Pendse is 
principal of OLAP Solutions and co-author of the OLAPreport.com. Marc 
Demarest is President of Noumenal, Inc. He served as CEO of 
DecisionPoint Applications and prior to that he held a number of 
positions with Sequent Computer Systems. 

On Tuesday, November 26, 2002, Marc Demarest and I exchanged a number of 
emails. Marc initially wrote "I think it'd be worth it to open up this 
can of real-time decision support worms on your pages, and get (a) some 
clarity and (b) some discussion started." This column is a start at 
getting some additional clarity.  I'm sure that further discussion will 
occur in various forums and settings.

So in the next few paragraphs I'll quote from Nigel and Marc's email 
comments.

Nigel Pendse wrote "In the BI context, a common meaning of real-time is 
that you can change data or assumptions in a planning model and see the 
results more or less instantly. This is easy enough with small Excel 
spreadsheets, but much harder with larger, more complex multidimensional 
models, and harder still if multiple people are doing it at the same 
time, each doing 'what if?' analysis of their own parts of an overall 
plan. In fact, only a few tools can even do this. This is much more 
useful than real-time analysis of operational data, where management 
level decision-making depends on medium or long term trends, not what 
someone bought five seconds ago. Yes, real-time analysis is important 
for some operational decisions, but not for many that would fall into 
the BI category."

Nigel continues "The form of real-time data warehousing that is being 
currently pushed is, in my view, a somewhat cynical consequence of the 
fact that some ETL tools can do it, so the vendors are inevitably 
suggesting that there's a major business need for it. I think this is 
vendor-push, not market-pull. Most business decisions based on data 
warehouses are not damaged by being based on last night's (or even last 
week's) data. But real real-time planning is genuinely useful -- and one 
reason why Excel remains the number one planning tool. It isn't as 
thorough as a proper, large-scale tool, but the fact that it's fast (ie, 
real-time) means that many people compromise their requirements in the 
interests of true interactivity."

Marc Demerest emailed me extensive comments.  He made four major points:

1. REAL-TIME MEANS "AS SOON AS THINGS CHANGE"

To begin with Marc suggests we need a better definition. He notes "In 
every situation I have been in, in which real-time DSS is discussed, the 
adjective 'real-time' means that informational inputs to decision-making 
processes are available as soon as there are state changes in the 
environment that alter those informational inputs. Examples: as an 
inventory manager or purchasing manager, I can see SKU-level stock 
changes as items are picked; as a cost center manager, I can see the 
state of my cost center as soon as any credits or debits are applied 
against that cost center; as a sales person with territory 
responsibilities, I can see all customer support incidents logged for 
any customer in my territory as soon as the trouble ticket is opened."

2. THERE IS ALWAYS SOME LATENCY IN "REAL-TIME" DSS

According to Marc, "Real-time refers to data, not to user response rate 
experience and shame on the vendor for attempting to corrupt the 
definition that badly. Real-time also means 'near-real-time' in practice 
because there is always some latency between (a) the actual state 
change, (b) the reflection of that state change in data in one or more 
systems of record and (c) the availability of the changed data to 
decision-makers. In my cost center example below, when D.J. Power clears 
Invoice #12 from Marc Demarest, Inc., the $10,000 Power pays hits Marc 
Demarest Inc.'s bank account (typically) a couple of days before Cost 
Center 983 in Marc Demarest Inc.'s financial ERP system gets the update 
indicating that Invoice #12 has been paid and the Cost Center has a 
$10,000 credit. Some number of microseconds-to-days thereafter, the 
financial data mart used by the manager of Cost Center 983 is updated. 
Total lag time from receipt of payment to 
information-available-for-decision is 2+ days. In other environments -- 
SCM, inventory, and logistics, for example -- the total elapsed 
wall-clock time between business state change (truck leaves depot with 
package) and information-available-for-decision may be as little as a 
few milliseconds to a few seconds."

3. IS "REAL-TIME" DECISION SUPPORT PUSH-BASED OR PULL-BASED?

Further, Marc explains "Now, assume a system capable of making 
decisional data available to decision-makers as and when those data 
elements change. The first and obvious question is: HOW is that data 
made available? Do I have to ask for it? Or does it 'come to me'? If I 
have to ask for it, of what resource do I ask it? If it just comes to 
me, HOW does it just come to me? This brings us, right away, to the 
first interesting distinction in real-time, and near real-time, DSS: 
pull-based systems that make me, the decision-maker, go get the data I 
need, and push-based systems that 'know' I am a decision-maker for 
certain classes of decision, and push the changed-state data to me as 
and when that data changes. Pull-based systems are not, in my view, 
real-time DSS environments: they are in all likelihood classic DSS (with 
data warehouses in them as repositories) that employ real-time or 
near-real-time extraction, transformation and loading (ETL) 
infrastructure: technically interesting but of no real business value. 
Push-based systems, on the other hand, are potentially dynamite, but I 
have yet to see any commercially-available product that actually does 
role-based changed-state data pushing to decision-makers. Yes, there are 
systems that send reports around in e-mail, but that is not what I mean, 
nor I think what others mean, when they say 'real-time DSS'."

4. IS "TWINKLING DATA" AND "REAL-TIME" DECISION SUPPORT A GOOD THING?

Finally, Marc noted "Real-time DSS has always troubled me. Maybe it's my 
upbringing under the care of Kimball and Inmon and others, all of whom 
made and make the very valid point that every type of decision -- in the 
commercial world at least -- has a stability profile to it. In other 
words, people making decisions see time differently in different 
contexts. As a controller, for example, I think in terms of reporting 
periods of months, quarters and years, because I must. As a product 
manager, I think in terms of milestones that span years, in all 
probability. As a warehouse manager on the downstream side of product 
fulfillment for a B2C e-business, I think in terms of minutes 
(particularly during this season). If we build a system that constantly 
updates all decisional data regardless of who uses it for what kinds of 
decisions, we run the risk of destabilizing whole classes of 
decision-making. For example, if a cost center manager runs a query at 
10 AM on Tuesday that says her cost center is within variance 
boundaries, and her controller runs the same query three hours later 
(after a $150,000 debit has been mistakenly posted by a clerk to that 
cost center and automatically trickled through to the decisional data), 
we have a fight for sure....and an instability problem. When real-time 
ETL first became available, people did it "because we can" -- and 
warehouses were constantly struggling to keep up with load demand, and 
simultaneously experiencing falling user query demand, because users 
asking the same question three times in one day were getting three 
different answers and in many cases assuming the warehouse was 
unreliable. I think the same is likely to happen when companies try to 
implement real-time DSS, unless real-time DSS is restricted to those 
classes of decisions in which decision-makers actually measure time in 
the millisecond-to-hour range. Beyond those classes of decision, the 
nightly refresh on the good ol' data warehouse will continue to be 'soon 
enough'."

CONCLUSIONS

The concept of "real-time" decision support is a broad term that is 
evolving.  Both Nigel and Marc raise good points that need to be 
reconciled. Nigel includes "what if?" analysis using a spreadsheet as an 
example of "real-time" decision support. Marc focuses on the data side 
of "real time" decision support. The issue of "push" versus "pull" for 
decision support is interesting, but my initial inclination is to 
suggest that both situations could qualify as "real-time" decision 
support. Thierauf (1982) argued that "any system that processes and 
stores data or reports them as they are happening is considered to be an 
on-line real-time system". His view is fairly consistent with Marc's 
position, but it doesn't seem to account for Nigel's position.

So when is "real-time" decision support desirable and needed? First, no 
matter what the definition "real-time" decision support is desirable 
when the decision-maker and organization can benefit. Second, 
"real-time" decision support must improve understanding rather than 
increase information load. Third, the support must be cost effective. 
Fourth, we don't what to provide any type of "real-time" decision 
support just because we can! Fifth, "real-time" information needs to 
"make a difference" and it must accurately reflects what is happening in 
the decision situation. Finally, "real-time" decision support and data 
analysis is definitely important for some operational decisions.

So I'm in general agreement with what both Marc and Nigel have written, 
but I want to continue to reflect on the issues and examples they cite.  
I want to give some consideration to what's possible and desirable in 
"real-time" decision support in crisis situations, for strategic 
control, during face-to-face business transactions, and for operations 
management and financial control. Real-time data gathering and decision 
support are closely linked in some decision situations, but not in 
others. Even a quick reading of this Ask Dan! and the one in DSS News, 
vol. 3, no. 24 shows more conceptual thinking is needed.  Various 
divergent positions need to be reconciled and probably can be 
reconciled, but as of today I can't provide a rigorous general 
definition of "real time" decision support. As always your comments, 
suggestions and feedback are welcomed.

Thanks Marc, Neal, and Nigel for your various emails.

References

Demarest, M., "RE: DSS News: Vol. 3, No. 24," email, Tuesday, 26 
November 2002.

Pendse, N., "RE: DSS News: Vol. 3, No. 24," email, Sunday, 24 November 
2002.

Thierauf, R. J., "Decision Support Systems for Effective Planning and 
Control," Englewood Cliffs, N. J.: Prentice-Hall, Inc., 1982.

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   Send your Ask Dan! questions to power@dssresources.com
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What's New at DSSResources.COM

12/06/2002 Posted article by Johnson, A., "Competitive Intelligence 
Software Applications"

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