BW Estimation Model

HI Gurus,
           I am currently trying to build a BW Estimation model . I would be greateful if you'll could suggest me as to the different objects types and the complexity factors for each objects.  I have labeled some tasks related to Info Objects , data targets and Info source. I am looking for suggestions in the Source connection, Update rules, Transfer Rules, Reports ,I want to know as to which tasks for these objects can be labelled as High or Medium or Low complexity?..If anyone of you could share any estimation model , or if anyone of you could provide me with your valuable input , I would really appreciate that.
Thanks a lot,
sanjeev

Hi sanjeev
Under normal circumstances You can use the following as a rule of thumb.
1) Source system -> Medium complexity depending on which source system to attach. If You are planning on attaching a SAP related source system complexity is low - if You are planning on using a 3 party source system via DBConnect or UDI complexity is medium to high depending on parameters such as accessibility, data capture etc.
2) Updaterules -> In general low however as UR are normally used to conduct transformations they can easily be high (ex. if You need to program start routines, return tables etc.) I would look in to the need for data transformation and rate it according to this.
3) Transfer rules -> Same as for update rules.
4) Reports -> Medium to high complexity depending of the requirements. If You need to create a simple report without any execution logic it is quite simple to do - however if You need to apply some VBA coding or user exits it can easily be more complex.
In general You can say that all standard functionality will normally be rated as low to medium. As soon as You need to expand this with either coding or custom made objects the complexity increases.
Hope it helps
Regards
/Frank

Similar Messages

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    Hi Gurus,
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    Define Source System     24     18     11
    Define Extract Structure     24     18     8
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    Reports                             24     16     8
    Process Chains                  24       16     8
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    Regards,
    Sanjeev

    Hi Sanjeev,
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    Cheers
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    Message was edited by:
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    Message was edited by:
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    <removed>
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    Hi,
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    [email protected]

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    generates a measure of the size of the application in terms of function
    points. This is independent of the implementation; it measures the
    behaviours of the application, rather than the particulars of design
    or implementation, such as class count or lines-of-code. Note that
    expected productivity varies as a function of the overall size of a project.
    FPA has been used as part of the study of literally thousands of
    software projects, so the conclusions drawn from FPA studies done
    by Capers Jones at Software Productivity Research have some
    statistical credibility.
    Looking at the general productivity numbers gathered by SPR
    (http://www.spr.com), there are some productivity measures that
    cover many languages, including Forte. In terms of lines-of-code
    per function point, Forte is 3 times more productive than C++.
    In terms of overall productivity (function points / man month), there
    are too many variable factors to make a simple statement of relative
    productivity levels between C++ and Forte meaningful. This has a lot
    to do with the Forte object model and run-time system, which, in certain
    problem domains, provides a lot of function points (or equivalent)
    "for free." In other words, if you can use Forte's plumbing package,
    you're automatically more productive. Providing the equivalent in
    C++ would be a daunting task (I should know -- I've done it!)
    The best method of determining your productivity is to measure it. There
    are many factors that affect the overall productivity of your software
    organisation; the programming language choice is just one. Using metrics
    drawn on industry averages concerning just ONE variable in the product
    development process is not terribly useful in project management.
    If you are looking for an extremely rough number that is more defensible
    that the good old "gut feel" technique, then class counting is probably
    the least intrusive on the development process.
    -Ron
    At 08:02 AM 6/5/97 +1000, you wrote:
    In his book Object-Oriented Software Metrics (Prentice Hall, 1994), Mark
    Lorenz in proposes an approach for estimating OO projects. Lorenzrecommends
    the average amount of effort spent on a single class is the best indictor of
    the amount of work required on a new project. He suggests Smalltalkdevelopers
    average 5-10 person-days per class, and C++ developers average 25-35
    person-days per class.
    Has anyone a view on average effort to build Forte classes?
    Note, the metrics quoted above relate to Design and Implementation. They
    assume Analysis has been completed, and do not include the time for project
    management, systems testing, and other support personnel. They assume aratio
    of 1:6 OO experts to novices. Higher ratios should result in greater
    productivity (lower average efforts per class). The guidelines also assumeno
    library of reusable components.
    Lorenz is an ex-head of IBM's Object Technology Center and a respected OO
    consultant and author. His method is based on the results of 8-16Smalltalk and
    C++ projects (not all statistics are available from all projects). Projects
    ranged in size from 60 to 700+ project-specific classes. Project durations
    ranged from 6 months to 2.5 years, with teams of 2 to 35 developers.
    Thanks for any help
    gjb.

    Greg,
    In my experience, the class-count metric is a poor one for time estimation,
    for four reasons:
    1. The actual time/class is very domain- and implementation-
    sensitive. Industry averages are fairly unhelpful, unless
    you happen to employ average practices and work in domains
    of "average" complexity (whatever that means!)
    2. It does not account for the overall size of the project; the
    larger the project, the lower overall productivity is.
    3. It requires that a fairly detailed design be done already, which
    represents a fair amount of the total effort; as an estimation
    tool, it is only useful in the latter stages of a project.
    4. Lorenz's research is based on a very small sample; 18 projects are
    hardly enough to have statistical validity.
    (I almost included a fifth point, but it is hardly worthy: class-counting
    can be spoofed. Awareness of the use of class-count as a metric can give
    developers a motive to either artificially increase or decrease the class
    count, depending on other motivating factors.)
    I would recommend function point analysis as a more general purpose tool
    for project management. Using a good statement of the requirements, FPA
    generates a measure of the size of the application in terms of function
    points. This is independent of the implementation; it measures the
    behaviours of the application, rather than the particulars of design
    or implementation, such as class count or lines-of-code. Note that
    expected productivity varies as a function of the overall size of a project.
    FPA has been used as part of the study of literally thousands of
    software projects, so the conclusions drawn from FPA studies done
    by Capers Jones at Software Productivity Research have some
    statistical credibility.
    Looking at the general productivity numbers gathered by SPR
    (http://www.spr.com), there are some productivity measures that
    cover many languages, including Forte. In terms of lines-of-code
    per function point, Forte is 3 times more productive than C++.
    In terms of overall productivity (function points / man month), there
    are too many variable factors to make a simple statement of relative
    productivity levels between C++ and Forte meaningful. This has a lot
    to do with the Forte object model and run-time system, which, in certain
    problem domains, provides a lot of function points (or equivalent)
    "for free." In other words, if you can use Forte's plumbing package,
    you're automatically more productive. Providing the equivalent in
    C++ would be a daunting task (I should know -- I've done it!)
    The best method of determining your productivity is to measure it. There
    are many factors that affect the overall productivity of your software
    organisation; the programming language choice is just one. Using metrics
    drawn on industry averages concerning just ONE variable in the product
    development process is not terribly useful in project management.
    If you are looking for an extremely rough number that is more defensible
    that the good old "gut feel" technique, then class counting is probably
    the least intrusive on the development process.
    -Ron
    At 08:02 AM 6/5/97 +1000, you wrote:
    In his book Object-Oriented Software Metrics (Prentice Hall, 1994), Mark
    Lorenz in proposes an approach for estimating OO projects. Lorenzrecommends
    the average amount of effort spent on a single class is the best indictor of
    the amount of work required on a new project. He suggests Smalltalkdevelopers
    average 5-10 person-days per class, and C++ developers average 25-35
    person-days per class.
    Has anyone a view on average effort to build Forte classes?
    Note, the metrics quoted above relate to Design and Implementation. They
    assume Analysis has been completed, and do not include the time for project
    management, systems testing, and other support personnel. They assume aratio
    of 1:6 OO experts to novices. Higher ratios should result in greater
    productivity (lower average efforts per class). The guidelines also assumeno
    library of reusable components.
    Lorenz is an ex-head of IBM's Object Technology Center and a respected OO
    consultant and author. His method is based on the results of 8-16Smalltalk and
    C++ projects (not all statistics are available from all projects). Projects
    ranged in size from 60 to 700+ project-specific classes. Project durations
    ranged from 6 months to 2.5 years, with teams of 2 to 35 developers.
    Thanks for any help
    gjb.

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