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Estimation of Production Support Projects

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Production Support White Paper

About this Document It is very difficult to make a vigorous, plausible and job-risking defense of an estimate that is derived by no

quantitative method, supported by little data and certified chiefly by the project managers guesstimates. At

the same time, the conventional use of Function Point Analysis for Production Support projects is not

possible in terms of both numerical size and implementation effort estimation since the support projects are

primarily transaction based (i.e. ticket driven). Customized approach and guidelines are therefore necessary

in order to estimate these projects.

This document gives an overview of the process of Estimation for ‘Transaction Based’ Support

Projects. The introduction deals with the steps of estimation in a broad spectrum and is followed by a

dedicated section on the detailed steps of Estimation for Support projects.

Purpose

The intent of this document is to present an approach: a consistent methodology that can be used to

measure the size, effort and FTE requirement of Production Support projects.

Intended Audience

Project Managers, Project Leads for Production Support projects.

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Contents 1.1 Problem to be Addressed .................................................................................................................................................................... 4 1.2 Production Support Projects – An Overview................................................................................................................................ 4 1.3 Estimation Approach - Production Support Projects ................................................................................................................ 4 1.4 Estimation Process Flow for Production Support Projects...................................................................................................... 5 1.5 Size Estimation for Production Support Projects ........................................................................................................................ 5 1.6 Effort Estimation...................................................................................................................................................................................... 6 1.7 FTE Determination ................................................................................................................................................................................. 8 1.8 Outstanding evidence of validity...................................................................................................................................................... 8 1.9 Take homes from this estimation model ....................................................................................................................................... 9

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1.1 Problem to be Addressed

We are in an era where the significance of software estimation has been understood and efforts are channelized to build robust estimation frameworks. The majority of these efforts have been put into for developing estimation guidelines for Application development and Maintenance(ADM) projects. Time has come to address the estimation needs of other important areas of the IT industry.One such area would be the support projects, since the schedule for these projects is fixed in most of the cases, the neccessity of an estimation model has not been at the top of the agenda. An indepth analysis of the profitability of the support projects will show the vitality of estimations in profit margins. A fixed schedule does not ensure profit as it finally boils down to the effective resource employement which primarly depends on the estimates.This paper would bring in a dimensional shift in terms of estimation guidelines built in for IT industry as it addresses the estimation issues of one type of support project namely production support.

1.2 Production Support Projects – An Overview

An application after being built is set in for production. The various stakeholders of the application need supports of different dimensions. The support activities could vary from creating users and it can go up to making minor changes in the application based on the requests raised by the users. Many a times the time frame for this kind of support is fixed by the customer . For example a project might be expected to provide support for 24*7 for five days a week for a period of three months.

1.3 Estimation Approach - Production Support Projects

Even prior to addressing how to estimate the question to be answered is what to estimate.The parameters to be estimated for a production support begins with the volume of work i.e size of the project. This paper considers the work volume to be performed as part of the production support projects in terms of the number of tickets/requests raised by the stake holders.Using the size value the effort for the project can be estimated. From effort the next parameter to be estimated will be the number of ‘Full Time Equivalent’ i.e. the number of resources to be employed. As schedule for a project is fixed it is not considered for estimation. The estimation model presented in this paper is independent of the schedule as the the estimates derived from this model are for a week and this estimates are repeatable across weeks if there is no change in the work volume (i.e. no of tickets raised).

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1.4 Estimation Process Flow for Production Support Projects

The approach for sizing Production Support projects can be explained through the diagram provided below. In this paper the ticket inflow is taken as the input for determining the size. Applying the productivity figure, we can then come up with the base effort. Additional effort contributing factors applicable for the project can then be applied on top of the base effort to get the resultant effort. This effort figure is then used to get the number of Full Time Equivalents (FTE)s required to support the job.

Start of Estimation

Ticket Distribution

Collect Input Data for Project

YES NO Tickets inflow Information Available?

Use some defect prediction model to determine the

ticket inflow

Estimate Size in Production Support

Points

Productivity determinator

Estimate Actual Effort

Estimate FTE Count

Effort contributing factors

Apply productivity to Estimate Base Effort

End of Estimation

Estimation Process Flow

1.5 Size Estimation for Production Support Projects

Production support jobs are primarily transaction based i.e. ticket based and mainly consists of the following typical activities

Support given through email, over phone, changing data in the screen (e.g. granting privilege, password reset etc.)

Providing work around solutions, data fixes

Bug fixing, providing minor enhancement works

Based on the work volume involved in each of these activities, the tickets can be categorized into various complexities (for example: Simple, Average, Complex). Normalization can be done for the different categories of tickets to derive the size of a production support engagement which can be represented in terms of Production Support Points (PSP).

PSP calculated using Ticket Distribution hence indicates the normalized size derived from the ticket inflow i.e. the number of tickets to be handled by the project within a span of time

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Note: In case the ticket distribution is not available, a distribution ratio can be assumed based on the historical data analysis from past project data for a particular organization.

1.6 Effort Estimation

Overview

The effort for production support projects is calculated by applying productivity on the size calculated in terms of Production Support Points (PSP).

In its simplest form, this relationship is expressed as:

Effort = Size (PSP) / Productivity where Productivity is expressed as PSP / Person Months.

Productivity

The generic definition of the term productivity is output per unit of input. In terms of estimation parameters it can be defined as size per unit effort. Productivity is the measure of effectiveness/efficiency. Productivity as a parameter provides a standard metric to compare performance between/within organizations. From estimation perspective productivity value enables effort estimation. If the unit of size is in PSP and the effort in terms of person hour (PH) then productivity would be PSP per unit of person hour.

Productivity Determination

Analysis of historical reveals that the ‘key’ productivity determinators of a typical production support engagement are

Application Platform

Known Error Database (KEDB) No of Interfaces the application has

1. Platform Selection

.Net

Java VB VC

Delphi

SAP

OracleApp

s

Prod

uctiv

ity P

SP/P

M

Productivity

Regression analysis of historical data shows that the productivity of a support engagement varies with the platform of the application being supported rather than the technology. Some of the possible platforms are Client Server, Mainframe/Legacy, Web based, ERP/Package, etc.

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2. The impact of Known Error Database (KEDB) on Productivity

Not Present Moderate Impact Strong Impact Very StrongImpact

Pro

duct

ivity

Productivity

The productivity for a support job increases manifold with the presence of a strong Known Error Database (KEDB). Hence the base productivity needs to be adjusted depending on the impact of the KEDB present in a particular scenario

3. Impact of the No of interfacing applications present

With the increase in the number of interfacing applications, the resultant productivity decreases. Hence this factor needs to be considered while computing the resultant productivity.

Calculation of Adjusted Effort from the Base effort

The effort obtained from size and productivity is termed as the base effort. The reason behind the terminology is that the productivity considered for effort calculation would be devoid of the factors which have varying impact from one project to another. The effort impact due to these factors is considered after estimating the base effort and these factors are termed as ‘Effort Impacting Factors’.

The base effort obtained by applying resultant productivity on the size determined in PSP needs to be adjusted to take care of the additional effort contributing factors applicable for a particular scenario.

The below table lists some typical example of ‘Effort Impacting Factors’ in Production Support Projects that may be considered.

Parameter Description Incident Handling & Routing

Effort spent on tickets that are not solved by the project but routed to another team. The effort spent on the above tickets involves analysis of such tickets and also the effort required to route them to another team.

Working of Defects with Business

To solve some of the tickets raised by the user, the team requires inputs form business. This is the effort spent to collect this information from the business team.

Tool Usage Usage of tools for solving the tickets. Greater usage of tool indicates a decreasing impact on effort

Reusable Component Availability to access to code blocks of the current/similar application, which can be reused for the current project

Team's Business knowledge

The amount of knowledge the team has on the business functionalities of the application being supported. An extensive knowledge on business reduces the resolving time of the tickets

Team's Technology Experience

It indicates the team’s acquaintance with the technology of the application being supported.

SME availability Number of Subject Matter Expertise available. Lack of SME will have an increasing impact on effort whereas if more SMEs are available, effort will come down.

Code Understandability

The ease of understandability of the code written. If the code is difficult to understand then the effort taken code related problems increases.

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Working of Defects with Dev Teams

For solving some of the tickets the development teams input might be required. This is the effort spent to get the information from the development team.

System Monitoring Monitoring system status w.r.t different parameters like transaction throughput, batch monitoring, job status etc

System Admin Includes administrative activities like privilege setup, buffer space management etc

Reporting & Metric Generation

The effort spent on preparing weekly or monthly status reports, metric reports etc.

Application Meetings The effort spent in attending meetings convened for project purpose.

Supporting Releases The effort required for supporting releases. This effort excludes ticket solving effort.

Training Support Effort spent on training the resources for the project. Outage Management Effort due to preventive and corrective actions to manage outage. Data Reconciliation/Cleanup

Effort Spent on data aggregation, segregation and for data population.

Documentation Work Effort spent on documentation activities in the project. Service Plans Effort spent on constructing service plans. Service Reviews Effort spent on reviewing the defined service plans.

Ad-hoc Queries

All the queries raised by the user which do not come in the form of tickets. It involves queries raised through phone calls or messaging.

1.7 FTE Determination

The effort estimation would pave the basis for estimating the resources to be employed.

Once the effort calculation is done, the next step involves calculation of the Full Time Equivalent (FTE) required to support the job.

In order to calculate the number of FTEs, the 1st step is to calculate the effective working hours per FTE per week. This is less than the total working hours per day specified by the organization since we need to take the following factors into account

Total no. of days spent in training and holidays: This value varies based on projects/geographies etc. User must input this value based on the applicable number of holidays and training days.

Productive hours per FTE per day: This value differs from the organization mandated working hours per day per associate. Only the productive hours needs to be accounted.

Taking the effective working hours per FTE per week, the workload coverage per shift (in case there are multiple shifts operating per day and the minimum FTE requirement per shift), the FTE requirement per shift can be calculated.

1.8 Outstanding evidence of validity

For pilot rollout, few support projects were selected from various TCS branches. Training sessions were conducted to educate the project leaders / managers from selected projects. The project managers of the selected sample projects performed the re-estimation of their projects using the Production Support model. Consolidated data from the sample projects were reviewed and the re-estimation data was compared with original estimation data and the actual effort spent by the projects and actual FTEs engaged for the job. The graph below shows the percentage variation from the actual (for both effort and FTE) for these projects.

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0%2%4%6%8%

10%12%

AMEX Int AMEX Domestic Moneygram

Effort

FTE

1.9 Take homes from this estimation model

The model forms the basis for a single standardized tested approach of estimation for production support projects is available. The estimation framework advocated by the model creates greater level of transparency in terms of estimation when submitted to the client. The implementation of the model in the organization apart from serving the purpose of estimation also servers as mechanism to capture the organization data for production support projects. With advent of PSP a single size unit is available for production support projects. A single size unit paves way for comparison among projects. The productivity value in terms of PSP/PH is an indicator of the efficiency of the project and it can be used for comparison between projects.

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