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Kate Armel's blog
SLIM-Collaborate 3.1 Brings Flexible Risk Management Online
January 24th, 2019 by Kate Armel
If you've been using SLIM-Collaborate's convenient, web-based project access to keep your stakeholders engaged and informed, you know SLIM-Collaborate offers streamlined, role-based estimation and data collection services designed to complement our feature-rich desktop tools. SLIM-Collaborate's simplicity and ease of use make it easier to promote consistent standards and practices to users across the enterprise, while seamless data exchange with the SLIM desktop tools lets your most experienced users leverage the power of advanced features.
Recently we talked with SLIM-Collaborate users, and one request stood out: they wanted us to bring Contingency planning into SLIM-Collaborate.  Release 3.1 of SLIM-Collaborate does just that, and even adds new risk buffering capabilities to the probability-based risk modelling available in SLIM-Estimate.  Here's how it all works.
Step 1: Create Reusable Contingency Profiles (Back Office)
Part of SLIM-Collaborate's innovative approach lies in letting experienced users (the "Back Office") analyze the business, then design and publish reusable building blocks (templates, trends, filters, dashboards, profiles) that simplify and standardize estimation and data collection for less experienced users. 

SLIM-Collaborate QSM News
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QSM Releases SLIM-Suite 10.1 with a New Look and Feel
December 13th, 2018 by Kate Armel
QSM has recently released an update to the feature-rich SLIM-Suite of tools.  For a detailed list of updates, download the SLIM-Suite 10.1 release notes. The 10.1 desktop release updates the look and feel of SLIM-Suite tools with easier-to-read fonts and a cleaner, simpler color palette inspired by modern Business Intelligence and Data Analysis applications. A new, high resolution theme also offers better support for high DPI and high resolution monitors.
Bird's Eye Staffing View
Many of the visual updates are subtle, so this post will cover the high impact features you're likely to notice on upgrading to SLIM-Suite 10.1. In SLIM-Estimate, cross-hatched phase shading on time series charts has been replaced by lighter, transparent curve fills that grow progressively darker for successive phases.  The view below shows staffing over time, not broken out by role, for a project using a traditional lifecycle.
Detailed Staffing View
Agile projects may prefer a more granular view of project staffing by role, with sprints delineated over the project timeline:
Task-Based Schedule View
SLIM Suite QSM News
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Making the Case for Software Estimation
March 8th, 2018 by Kate Armel
The challenges surrounding software estimation are both well known and well documented.  Most discussions on this topic center around the technical challenges estimators face: tight schedules, unclear scope, evolving requirements, and accounting for dependencies and risk.  But there's a more fundamental challenge we don't hear so much about – educating stakeholders and making the business case for structured, yet practical estimation, and why it is a critical success factor. 
Let's face it: process improvement is rarely cost-free.  Businesses expect a visible return on investments made in estimation tools and training.  The benefits of quality software estimation can be compelling, but moving decision makers from "open to the idea of estimation" to "willing to commit money and resources" can be difficult for busy analysts and managers juggling multiple roles and tasks.
In her latest video, QSM's Laura Zuber explains what makes a good software estimate and how empirically-based estimation helps projects:
Estimation Training
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Top Programming Languages Revisited
November 8th, 2016 by Kate Armel
Mike Harris at the Davis Consulting Group blog links to a 2014 list of 11 Essential Programming Languages from Baseline Magazine:
If you want to learn about the hottest programming languages today, don't miss this list from IEEE Spectrum. This respected organization, which has 400,000 members and is considered the world's largest association of technology professionals, enlisted the services of Nick Diakopoulos, a well-known computational journalist and assistant professor at the University of Maryland, to compile the language rankings. Diakopoulos proceeded by weighing and combining 12 metrics from 10 sources, including IEEE Xplore, Google and GitHub. The result is a compilation of languages that cover big data analytics, graphics, system administration, network programming and virtually every other tech-supported function.
IEEE’s interactive list, which you can explore here, generates customized rankings for various sectors (Web, embedded, enterprise). In evaluating the results, it makes sense to ask, “What makes a programming language, ‘essential’?” Language popularity can be measured several ways:
Languages QSM Database
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Extending SLIM Tools with Extension Menu Items
May 29th, 2014 by Kate Armel
Extension menu items are one of the best new features in SLIM-Suite 8.2.  You don’t have to be a programmer (or even pretend to be one online) to create customizable menu items that perform tasks like these right from the menu of any SLIM-Suite application:
Once you get the hang of it, creating your own custom menu items is easy: if you can unzip files and use Notepad, trust me – you can do this!
The Extension Menu Item feature is documented in its own chapter in each SLIM-Suite user guide, but if you’re like me you could probably use a few real life examples and some sample configuration settings to jump start the process.  In a fairly short period of time, I was easily able to create the following menu items in SLIM-DataManager:
The menu items I created fell into several categories: launching an external application, launching a SLIM-Suite utility/API, pointing to an external process guide, launching a Windows utility. I’ll cover each one, providing sample configuration text for each.
CREATING THE .INI FILE
SLIM Suite Tips & Tricks
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Software Cost Estimation Article in The DACS Journal
March 30th, 2012 by Kate Armel
The February issue of the DACS Journal of Software Technology focuses on Software Cost Estimation and Systems Acquisition. My contribution, which you can read here, addresses the challenges faced by estimators and the value of establishing a historical baseline to support smarter planning, counter unrealistic expectations, and maximize productivity.
Using several recent studies, my paper addresses the following questions:
Read the full article.
Estimation Articles
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Part III: Finding the Optimal Team Size for Your Project
February 17th, 2012 by Kate Armel
In part one of our team size series, we looked at Best and Worst in Class software projects and found that using small teams is a best practice for top performing projects. Part two looked at differences in cost and quality between small and large team projects and found that small teams use dramatically less effort and create fewer defects.  But simply knowing that small teams perform better doesn’t tell us how small a team to use. Most software metrics scale with project size, and team size is no exception. Management priorities must also be taken into account. Small projects can realize some schedule compression by using slightly larger teams but for larger projects, using too many people drives up cost but does little to reduce time to market:
Larger teams create more defects, which in turn beget additional rework… These unplanned find/fix/retest cycles take additional time, drive up cost, and cancel out any schedule compression achieved by larger teams earlier in the lifecycle.
In a study conducted in the spring of 2011, QSM Consultant Don Beckett designed a study that takes both system size and management priorities into account. He divided 1920 IT projects into four size quartiles. Using median effort productivity (SLOC/PM) and schedule productivity (SLOC/Month) values for each size bin, he then isolated top performing projects for schedule, effort, and balanced performance (better than average for effort and schedule):

Team Size
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Part II: Small Teams Deliver Lower Cost, Higher Quality
January 26th, 2012 by Kate Armel
This is the second post in a three part investigation of how team size affects project performance, cost, quality, and productivity. Part one looked at cost and schedule performance for Best in Class and Worst in Class IT projects. For this study, Best in Class projects were those that delivered more than one standard deviation faster, but used more than one standard deviation less effort than the industry average for projects of the same size. A key characteristic of these top performing projects was the use of small teams: median team size for best in class projects was 4 FTEs (full time equivalent) people versus 17 FTEs for the worst performers.
What is the relationship between team size and management metrics like cost and defects? To find out, I recently looked at 1060 medium and high confidence IT projects completed between 2005 and 2011. These projects were drawn from the QSM database of over 10,000 completed software projects. The projects were divided into two staffing bins:
These size bins bracket the median team size of 4.6 for the overall sample, producing roughly equal groups of projects that cover the same size range. Our best/worst in class study found a 4 to 1 team size ratio between the best and worst performers. 
Team Size
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Top Performing Projects Use Small Teams
January 23rd, 2012 by Kate Armel
Last week, Carl Erickson of Atomic Spin referenced a study performed by Doug Putnam several years ago:
A study done by consultancy QSM in 2005 seems to indicate that smaller teams are more efficient than larger teams. Not just a little more efficient, but dramatically more efficient. QSM maintains a database of 4000+ projects. For this study they looked at 564 information systems projects done since 2002. (The author of the study claims their data for real-time embedded systems projects showed similar results.) They divided the data into “small” teams (less than 5 people) and “large” teams (greater than 20 people).
To complete projects of 100,000 equivalent source lines of code (a measure of the size of the project) they found the large teams took 8.92 months, and the small teams took 9.12 months. In other words, the large teams just barely (by a week or so) beat the small teams in finishing the project!
Since then, QSM has performed several studies investigating the relationship between team size and metrics like project scope, productivity, effort/cost, and reliability. The results have been surprisingly consistent regardless of application domain, technology, or year group.  I’ll be reviewing what we found in a series of posts.
Team Size
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SLIM Suite Quick Reference Guide
October 13th, 2011 by Kate Armel
Have you ever found yourself wondering which SLIM tool to use for a task, or what interfacing features are available for various SLIM Suite applications? We've created a handy Quick Reference Guide that offers a concise, "at a glance" summary of the great features built into SLIM Suite! This one page table is chock full of useful information about import/export capabilities, major tool features, and interfaces to other SLIM tools or applications like Microsoft Project and IBM Rational Focal Point and Rational Team Concert.
Here's what you'll find:
Whether you've licensed one or two applications or the entire tool suite, we hope our Quick Reference Guide will be a helpful resource. 
You can find more resources in the QSM Support section of our website.
Tips & Tricks Quick Reference
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