We have identified a parsimonious set of strategies and counter strategies related to
information politics, and some ways in which such politics could be prevented. In an era where information has been equated with power and prestige, information politics will increasingly come into play: it is the norm, not an exception. Organizations that recognize this have the greatest chance to reduce failure rates of IS projects.
INTRODUCTION TO INFORMATION RETRIEVAL
This lecture will introduce the information retrieval problem, introduce the terminology related to IR, and provide a history of IR. In particular, the history of the web and its impact on IR will be discussed. Special attention and emphasis will be given to the concept of relevance in IR and the critical role it has played in the development of the subject. The lecture will end with a conceptual explanation of the IR process, and its relationships with other domains as well as current research developments.
INFORMATION RETRIEVAL MODELS
This lecture will present the models that have been used to rank documents according to their estimated relevance to user given queries, where the most relevant documents are shown ahead to those less relevant. Many of these models form the basis for many of the ranking algorithms used in many of past and today’s search applications. The lecture will describe models of IR such as Boolean retrieval, vector space, probabilistic retrieval, language models, and logical models. Relevance feedback, a technique that either implicitly or explicitly modifies user queries in light of their interaction with retrieval results, will also be discussed, as this is particularly relevant to web search and personalization.
This chapter introduces the notion of Information Retrieval (IR). it discusses after a survey of classification of various IR systems and major components of an IR system, the notion of Boolean Retrieval model and Invertex Index and extended Boolean are presented.
We have identified a parsimonious set of strategies and counter strategies related to
information politics, and some ways in which such politics could be prevented. In an era where information has been equated with power and prestige, information politics will increasingly come into play: it is the norm, not an exception. Organizations that recognize this have the greatest chance to reduce failure rates of IS projects.
INTRODUCTION TO INFORMATION RETRIEVAL
This lecture will introduce the information retrieval problem, introduce the terminology related to IR, and provide a history of IR. In particular, the history of the web and its impact on IR will be discussed. Special attention and emphasis will be given to the concept of relevance in IR and the critical role it has played in the development of the subject. The lecture will end with a conceptual explanation of the IR process, and its relationships with other domains as well as current research developments.
INFORMATION RETRIEVAL MODELS
This lecture will present the models that have been used to rank documents according to their estimated relevance to user given queries, where the most relevant documents are shown ahead to those less relevant. Many of these models form the basis for many of the ranking algorithms used in many of past and today’s search applications. The lecture will describe models of IR such as Boolean retrieval, vector space, probabilistic retrieval, language models, and logical models. Relevance feedback, a technique that either implicitly or explicitly modifies user queries in light of their interaction with retrieval results, will also be discussed, as this is particularly relevant to web search and personalization.
This chapter introduces the notion of Information Retrieval (IR). it discusses after a survey of classification of various IR systems and major components of an IR system, the notion of Boolean Retrieval model and Invertex Index and extended Boolean are presented.
Building a 'single digital presence' for public librariesFleurMartin3
This presentation is taken from a webinar the single digital presence team held with public library staff from across the UK. In it we communicate our latest vision for the project, outlining what we've been up to since the publication of our report and how we've refined our recommendations building on an extensive period of user research.
About the project: The Single Digital Presence project, based at the British Library is exploring how to improve digital services in the United Kingdom's public libraries. Our goal is to equip public libraries with the right tools and to increase public library use both on and offline.
You can find out more about our project by reading this blog:
https://www.bl.uk/press-releases/2019/june/new-research-proposes-five-options-for-a-digital-presence-in-public-libraries
or by emailing us singledigitalpresence@bl.uk
The (standard) Boolean model of information retrieval (BIR) is a classical information retrieval (IR) model and, at the same time, the first and most-adopted one. ... The BIR is based on Boolean logic and classical set theory in that both the documents to be searched and the user's query are conceived as sets of terms.
Speaker: Charlie Swanson, Software Engineer, MongoDB
Level: 200 (Intermediate)
Track: How We Build MongoDB
Learn how MongoDB answers your queries from a query system engineer. If you've ever had a performance problem with a query but didn't know how to find the cause, or if you've ever needed to confirm that your shiny new index is being put to work, the explain command is an excellent place to start. MongoDB's explain system is a powerful tool for solving this type of problem, but can be intimidating and unwieldy to use. In this talk, we will discuss how the explain command works and break down its output into digestible pieces.
What You Will Learn:
- Exactly how indexes are used during your queries and aggregations
- How to diagnose your poorly performing operations
- How to tune your most important operations to ensure that they scale seamlessly
Building a 'single digital presence' for public librariesFleurMartin3
This presentation is taken from a webinar the single digital presence team held with public library staff from across the UK. In it we communicate our latest vision for the project, outlining what we've been up to since the publication of our report and how we've refined our recommendations building on an extensive period of user research.
About the project: The Single Digital Presence project, based at the British Library is exploring how to improve digital services in the United Kingdom's public libraries. Our goal is to equip public libraries with the right tools and to increase public library use both on and offline.
You can find out more about our project by reading this blog:
https://www.bl.uk/press-releases/2019/june/new-research-proposes-five-options-for-a-digital-presence-in-public-libraries
or by emailing us singledigitalpresence@bl.uk
The (standard) Boolean model of information retrieval (BIR) is a classical information retrieval (IR) model and, at the same time, the first and most-adopted one. ... The BIR is based on Boolean logic and classical set theory in that both the documents to be searched and the user's query are conceived as sets of terms.
Speaker: Charlie Swanson, Software Engineer, MongoDB
Level: 200 (Intermediate)
Track: How We Build MongoDB
Learn how MongoDB answers your queries from a query system engineer. If you've ever had a performance problem with a query but didn't know how to find the cause, or if you've ever needed to confirm that your shiny new index is being put to work, the explain command is an excellent place to start. MongoDB's explain system is a powerful tool for solving this type of problem, but can be intimidating and unwieldy to use. In this talk, we will discuss how the explain command works and break down its output into digestible pieces.
What You Will Learn:
- Exactly how indexes are used during your queries and aggregations
- How to diagnose your poorly performing operations
- How to tune your most important operations to ensure that they scale seamlessly
Oklahoma City Economic Development Information SystemGIS Planning
A presentation given by B. Workman about the Greater Oklahoma City's website service for site selection given at the International Economic Development Council's 2002 Annual Conference. The GIS system provides real estate, demographic, and industry information with interactive maps.
The worldwide market for over-the-counter (OTC) drugs could exceed $70 billion by 2015, according to a report by Visiongain, a British research company. The U.S. market for OTC drugs was $17.4 billion in 2011, according to the Consumer Healthcare Products Association (CHPA), an OTC industry trade group. That's a steady, though not radical increase from 1964 when OTC sales were recorded at $1.9 billion.
Information Overload in the Attention EconomyOlivier Serrat
Information has become ubiquitous because producing, manipulating, and disseminating it is now cheap and easy. But might perceptions of information overload have less to do with quantity than with the qualities by which knowledge is presented?
Investment in business information technology (IT) should not be valued in a vacuum. The investment must be for business purpose that is used to increase company revenue, market share and profit (via reduced expenses); therefore, IT projects need to be evaluated as any corporate use of funds.
Building a Credible Performance Measurement BaselineGlen Alleman
Establishing a credible Performance Measurement Baseline, with a risk adjusted Integrated Master Plan and Integrated Master Schedule, starts with the WBS and connects Technical Measures of progress to Earned Value
Building A Credible Measurement BaselineGlen Alleman
Establishing a credible Performance Measurement Baseline, with a risk adjusted Integrated Master Plan and Integrated Master Schedule, starts with the WBS and connects Technical Measures of progress to Earned Value
EIA-748-C asks us to “objectively assess accomplishments at the work performance level.” As well §3.8 of 748-C tells us “Earned Value is a direct measurement of the quantity of work accomplished. The quality and technical content of work performed is controlled by other processes.”
Building a Credible Performance Measurement BaselineGlen Alleman
Establishing a credible Performance Measurement Baseline, with a risk adjusted Integrated Master Plan and Integrated Master Schedule, starts with the WBS and connects Technical Measures of progress to Earned Value
BA 3010 Assignment #1During this course, you will be graded on.docxwilcockiris
BA 3010 Assignment #1
During this course, you will be graded on three dimensions:
1. your ability to identify the correct analytical tool to use,
2. your ability to execute the analysis you have selected,
3. your ability to interpret the results of your analysis
To that end, the assignments will try to reinforce those particular skills by directly targeting these dimensions.
All of your work should be done in an Excel spreadsheet, including your text responses. Do not send in a Word document. You should submit your assignment via the submission process in Blackboard.
Identify
Q1) Open up the file Assignment 1 and examine the data set on the worksheet Q1. This is a data set of 500 Bakersfield households that were recently surveyed. A definition for each variable (unless self-explanatory) can be found in the comments section (place your cursor over any cell with a little red triangle – a comment box will pop up). Our objective is to learn about the financial state of all Bakersfield households. Answer the following (a text box for your answers is provided to the right of the data):
a) Is this cross-sectional data or time-series data?
b) Is this a population or a sample?
c) Ignoring the variable Household, which is just an identifier variable (household #1, household #2, etc.), identify the variable type and sub-type for each variable.
d) If you wished to examine the distribution of the variable monthly payment, what would you do? List any graphs or calculations you think appropriate.
Execute
Q2) Create the following graphs. Note we are still using the data in Q1.
a) For the data in sheet Q1, do a histogram for the variable debt. Don’t be afraid to redo it a couple of times (resetting the number of bins or the “span” of the bins) until you get one that is satisfactory and revealing.
b) Again, for data in sheet Q1, do a boxplot with the variable first income.
Q3) Examine the data set in the worksheet Q3. This data set lists the 24 players who were on the roster of the Colorado Avalanche at the beginning of the 2001-2002 NHL season. The variables include the name, position, and salary for each player (see the definitions in the comments).
a) Calculate the following values for the variable Salary:
i. The average/mean
ii. The median
iii. The standard deviation
iv. The maximum, minimum, and range
v. The 1st and 3rd quartiles and the inter-quartile range
vi. The salary that 35% of players earn less than
vii. The salary that 20% of players earn more than
b) Create a box-plot for the variable Salary.
Interpret
Q4) Examine the graphs shown below. What do you learn from this graph? In other words, what can you tell us about the distribution of first_income? It might help if you pretend you are summarizing the results in a few sentences for your boss. Please type your answers on the Graphs page of the assignment 1 spreadsheet.
Graph (from data set 1 in the assignment 1 spreadsheet)
Q5) Interpret the following. .
BA 3010 Assignment #1During this course, you will be graded on.docxrosemaryralphs52525
BA 3010 Assignment #1
During this course, you will be graded on three dimensions:
1. your ability to identify the correct analytical tool to use,
2. your ability to execute the analysis you have selected,
3. your ability to interpret the results of your analysis
To that end, the assignments will try to reinforce those particular skills by directly targeting these dimensions.
All of your work should be done in an Excel spreadsheet, including your text responses. Do not send in a Word document. You should submit your assignment via the submission process in Blackboard.
Identify
Q1) Open up the file Assignment 1 and examine the data set on the worksheet Q1. This is a data set of 500 Bakersfield households that were recently surveyed. A definition for each variable (unless self-explanatory) can be found in the comments section (place your cursor over any cell with a little red triangle – a comment box will pop up). Our objective is to learn about the financial state of all Bakersfield households. Answer the following (a text box for your answers is provided to the right of the data):
a) Is this cross-sectional data or time-series data?
b) Is this a population or a sample?
c) Ignoring the variable Household, which is just an identifier variable (household #1, household #2, etc.), identify the variable type and sub-type for each variable.
d) If you wished to examine the distribution of the variable monthly payment, what would you do? List any graphs or calculations you think appropriate.
Execute
Q2) Create the following graphs. Note we are still using the data in Q1.
a) For the data in sheet Q1, do a histogram for the variable debt. Don’t be afraid to redo it a couple of times (resetting the number of bins or the “span” of the bins) until you get one that is satisfactory and revealing.
b) Again, for data in sheet Q1, do a boxplot with the variable first income.
Q3) Examine the data set in the worksheet Q3. This data set lists the 24 players who were on the roster of the Colorado Avalanche at the beginning of the 2001-2002 NHL season. The variables include the name, position, and salary for each player (see the definitions in the comments).
a) Calculate the following values for the variable Salary:
i. The average/mean
ii. The median
iii. The standard deviation
iv. The maximum, minimum, and range
v. The 1st and 3rd quartiles and the inter-quartile range
vi. The salary that 35% of players earn less than
vii. The salary that 20% of players earn more than
b) Create a box-plot for the variable Salary.
Interpret
Q4) Examine the graphs shown below. What do you learn from this graph? In other words, what can you tell us about the distribution of first_income? It might help if you pretend you are summarizing the results in a few sentences for your boss. Please type your answers on the Graphs page of the assignment 1 spreadsheet.
Graph (from data set 1 in the assignment 1 spreadsheet)
Q5) Interpret the following. .
To Explore the Role of Artificial Intelligence in Digital Branding of a FirmNavin Sood
This study will also identify how AI is changing perception in International context through Google and in Indian context via TCS. It will be interesting to study if AI is changing our perception about how we perceive a brand based on factors like Application Values, Ethical Values, Social Value, Development Values, etc.
USDA Loans in California: A Comprehensive Overview.pptxmarketing367770
USDA Loans in California: A Comprehensive Overview
If you're dreaming of owning a home in California's rural or suburban areas, a USDA loan might be the perfect solution. The U.S. Department of Agriculture (USDA) offers these loans to help low-to-moderate-income individuals and families achieve homeownership.
Key Features of USDA Loans:
Zero Down Payment: USDA loans require no down payment, making homeownership more accessible.
Competitive Interest Rates: These loans often come with lower interest rates compared to conventional loans.
Flexible Credit Requirements: USDA loans have more lenient credit score requirements, helping those with less-than-perfect credit.
Guaranteed Loan Program: The USDA guarantees a portion of the loan, reducing risk for lenders and expanding borrowing options.
Eligibility Criteria:
Location: The property must be located in a USDA-designated rural or suburban area. Many areas in California qualify.
Income Limits: Applicants must meet income guidelines, which vary by region and household size.
Primary Residence: The home must be used as the borrower's primary residence.
Application Process:
Find a USDA-Approved Lender: Not all lenders offer USDA loans, so it's essential to choose one approved by the USDA.
Pre-Qualification: Determine your eligibility and the amount you can borrow.
Property Search: Look for properties in eligible rural or suburban areas.
Loan Application: Submit your application, including financial and personal information.
Processing and Approval: The lender and USDA will review your application. If approved, you can proceed to closing.
USDA loans are an excellent option for those looking to buy a home in California's rural and suburban areas. With no down payment and flexible requirements, these loans make homeownership more attainable for many families. Explore your eligibility today and take the first step toward owning your dream home.
how to sell pi coins in all Africa Countries.DOT TECH
Yes. You can sell your pi network for other cryptocurrencies like Bitcoin, usdt , Ethereum and other currencies And this is done easily with the help from a pi merchant.
What is a pi merchant ?
Since pi is not launched yet in any exchange. The only way you can sell right now is through merchants.
A verified Pi merchant is someone who buys pi network coins from miners and resell them to investors looking forward to hold massive quantities of pi coins before mainnet launch in 2026.
I will leave the telegram contact of my personal pi merchant to trade with.
@Pi_vendor_247
What website can I sell pi coins securely.DOT TECH
Currently there are no website or exchange that allow buying or selling of pi coins..
But you can still easily sell pi coins, by reselling it to exchanges/crypto whales interested in holding thousands of pi coins before the mainnet launch.
Who is a pi merchant?
A pi merchant is someone who buys pi coins from miners and resell to these crypto whales and holders of pi..
This is because pi network is not doing any pre-sale. The only way exchanges can get pi is by buying from miners and pi merchants stands in between the miners and the exchanges.
How can I sell my pi coins?
Selling pi coins is really easy, but first you need to migrate to mainnet wallet before you can do that. I will leave the telegram contact of my personal pi merchant to trade with.
Tele-gram.
@Pi_vendor_247
Poonawalla Fincorp and IndusInd Bank Introduce New Co-Branded Credit Cardnickysharmasucks
The unveiling of the IndusInd Bank Poonawalla Fincorp eLITE RuPay Platinum Credit Card marks a notable milestone in the Indian financial landscape, showcasing a successful partnership between two leading institutions, Poonawalla Fincorp and IndusInd Bank. This co-branded credit card not only offers users a plethora of benefits but also reflects a commitment to innovation and adaptation. With a focus on providing value-driven and customer-centric solutions, this launch represents more than just a new product—it signifies a step towards redefining the banking experience for millions. Promising convenience, rewards, and a touch of luxury in everyday financial transactions, this collaboration aims to cater to the evolving needs of customers and set new standards in the industry.
how to sell pi coins at high rate quickly.DOT TECH
Where can I sell my pi coins at a high rate.
Pi is not launched yet on any exchange. But one can easily sell his or her pi coins to investors who want to hold pi till mainnet launch.
This means crypto whales want to hold pi. And you can get a good rate for selling pi to them. I will leave the telegram contact of my personal pi vendor below.
A vendor is someone who buys from a miner and resell it to a holder or crypto whale.
Here is the telegram contact of my vendor:
@Pi_vendor_247
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
NO1 Uk Divorce problem uk all amil baba in karachi,lahore,pakistan talaq ka m...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
#vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore#blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #blackmagicforlove #blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #Amilbabainuk #amilbabainspain #amilbabaindubai #Amilbabainnorway #amilbabainkrachi #amilbabainlahore #amilbabaingujranwalan #amilbabainislamabad
The European Unemployment Puzzle: implications from population agingGRAPE
We study the link between the evolving age structure of the working population and unemployment. We build a large new Keynesian OLG model with a realistic age structure, labor market frictions, sticky prices, and aggregate shocks. Once calibrated to the European economy, we quantify the extent to which demographic changes over the last three decades have contributed to the decline of the unemployment rate. Our findings yield important implications for the future evolution of unemployment given the anticipated further aging of the working population in Europe. We also quantify the implications for optimal monetary policy: lowering inflation volatility becomes less costly in terms of GDP and unemployment volatility, which hints that optimal monetary policy may be more hawkish in an aging society. Finally, our results also propose a partial reversal of the European-US unemployment puzzle due to the fact that the share of young workers is expected to remain robust in the US.
The secret way to sell pi coins effortlessly.DOT TECH
Well as we all know pi isn't launched yet. But you can still sell your pi coins effortlessly because some whales in China are interested in holding massive pi coins. And they are willing to pay good money for it. If you are interested in selling I will leave a contact for you. Just telegram this number below. I sold about 3000 pi coins to him and he paid me immediately.
Telegram: @Pi_vendor_247
Even tho Pi network is not listed on any exchange yet.
Buying/Selling or investing in pi network coins is highly possible through the help of vendors. You can buy from vendors[ buy directly from the pi network miners and resell it]. I will leave the telegram contact of my personal vendor.
@Pi_vendor_247
Introduction to Indian Financial System ()Avanish Goel
The financial system of a country is an important tool for economic development of the country, as it helps in creation of wealth by linking savings with investments.
It facilitates the flow of funds form the households (savers) to business firms (investors) to aid in wealth creation and development of both the parties
how to sell pi coins effectively (from 50 - 100k pi)DOT TECH
Anywhere in the world, including Africa, America, and Europe, you can sell Pi Network Coins online and receive cash through online payment options.
Pi has not yet been launched on any exchange because we are currently using the confined Mainnet. The planned launch date for Pi is June 28, 2026.
Reselling to investors who want to hold until the mainnet launch in 2026 is currently the sole way to sell.
Consequently, right now. All you need to do is select the right pi network provider.
Who is a pi merchant?
An individual who buys coins from miners on the pi network and resells them to investors hoping to hang onto them until the mainnet is launched is known as a pi merchant.
debuts.
I'll provide you the Telegram username
@Pi_vendor_247
how to sell pi coins effectively (from 50 - 100k pi)
Information economics
1. Information Economics
The classical approach
Jeroen Hoevenberg
2control4IT
Jeroen.Hoevenberg@2control4IT.nl
2. Classic Information Economics
Information Economics regards the ex-ante
assessment of IT investments. It is regarding
both the individual project and the project
portfolio and is meant as a frame work in order
to assign the scarce IT budgets in such a way
that the highest Added value is generated.
Information economics is a multi criteria analysis
instrument taking into account both tangible
indicators as intangible indicators.
The subject of Information Economics was developed by Parker and Benson (see Benson, 1991).
3. Main used Benefit Indicators (1)
1. Return on Investment (ROI)
A performance measure used to evaluate the efficiency of an investment or to compare the efficiency of a
number of different investments. To calculate ROI, the benefit (return) of an investment is divided by the
cost of the investment; the result is expressed as a percentage or a ratio.
The return on investment formula:
It is also possible to use similar indicators as net present value, etc
2. Strategic Match (SM)
Strategic match assesses the degree to which the proposed project responds to established corporate and
business strategies and goals. This dimension emphasizes the close relationship between IT planning and
corporate planning, and it assesses the degree to which a potential project contributes to corporate
strategy.
4. Main used Benefit Indicators (2)
3. Competitive Advantage (CA)
Competitive advantage evaluates the degree to which the proposed project provides an advantage in the
marketplace, for example, inter-organizational collaboration through electronic data interchange.
4. Management Information (MI)
Management information is an assessment of a project's contribution to management's need for
information on core activities, e.g., activities directly involved in the realization of the firm's mission, as
distinguished from support and accounting activities.
5. Competitive Response (CR)
Competitive response evaluates the degree of business risk associated with not undertaking the project.
5. Main used Benefit Indicators (3)
6. Service and Value (SV)
Measurements of customer satisfaction (service and value) must be made from the customer's viewpoint.
This measurement takes into consideration such things as ease of
access, credibility, competence, reliability, courtesy, security and responsiveness. It also attempts to
measure the degree to which customers "like" to do business with the company.
7. Strategic IT Architecture (SA)
Strategic IT architecture assesses the degree to which the proposed project fits into the overall
information systems direction. It assumes the existence of a long-term IT plan, i.e., an architecture or
blueprint that provides the top-down structure into which future data and systems must fit.
6. Main used Risk Indicators (1)
1. Strategic Uncertainty (SU)
Strategic uncertainty is an assessment of the degree to which the business strategy is likely to succeed.
That is, information technology projects associated with a risky business strategy are also at risk, a fact to
consider in assessing a project's viability.
2. Organizational Risk (OR)
Organizational risk is an assessment of the degree to which an information systems project depends on
new or untested IT or Business skills, management capabilities, or experience.
3. IT Infrastructure Risk (IR)
The assessment of IS infrastructure risk is essentially an environmental assessment, involving such factors
as data administration, communications, distributed systems, etc. It assesses the degree to which the
entire IT organization is both required to support the project and the degree to which it is prepared to do
so.
7. Main used Risk Indicators (2)
4. Definitional Uncertainty (DU)
Generally, definitional uncertainty assesses the specificity of the user's or business' objectives that are
communicated to the IT project personnel. When the user cannot properly describe a problem, the
technology department is hard-pressed to supply an answer (quality of requirement engineering).
5. Technology Uncertainty (TU)
Technology uncertainty assesses a project's dependence on new or untried technologies, which may
involve a single technology or a combination of new technical skills sets, hardware, or software tools.
8. Framework for Assessment of Projects
Every participant is scoring the project at the assessment items. The individual
scores are added and a mean result is calculated in order to prevent
manipulation of outcomes. Large differences between individual scores should
be discussed.
Assessment of an individual project
Assesment
Name Function ROI SM CA MI CR SV SA SU OR IR DU TU
A
B
C
D
Average W ei ght
ROI = Return on Investment Score tabel
SM = Strategi c M atch 0= Of no Importance
CA = Competi ti ve Advantage 1= Of somewhat i mportance
MI = M anagement Informati on 2= Of l i ttl e i mportance
CR = Competi ti ve Respons 3= Of i mportance
SV = Servi ce and Val ue 4= Of great i mportance
SA = Strategi c IT Archtecture 5= Of very hi gh i mportance
SU = Strategi c Uncertai nty
OR = Orgi ni zati onal Ri sk
IR = IT Infrastrcuture Ri sk
DU = Defi ni ti onal Uncertai nty
TU = Technol ogy Uncertai nty
9. Framework for Assessment of Projects
• The framework can also be used in
communication with the business or from the
business.
• Scoring can be done by a fixed group and/or
by project related stakeholders (However one
should take into account that stakeholders
tend to over/under-estimate scoring).
• A variance based on the statistical deviation
can be used to analyse the effect of mavericks.
10. Framework for Portfolio Assessment
The whole portfolio is assessed on al criteria. All criteria have received there
own weight. Based on added value and risk a score of importance can be
calculated.
Assesment of Project Portfolio
Added Value Risks
Cri teri a ROI SM CA MI CR SV SA SU OR IR DU TU
Rel ati ve i mportance
Score T
Score +
Score -
W ei ght +/- + + + + + + - - - - -
Project Scoring
A 0 0 0
B 0 0 0
C 0 0 0
D 0 0 0
Score tabel
0= Of no Importance
1= Of somewhat i mportance
2= Of l i ttl e i mportance
3= Of i mportance
4= Of great i mportance
5= Of very hi gh i mportance
11. Assessment Matrix
The results of a portfolio assessment can also be plotted in a matrix table. The
matrix provides more information on Added Value vs Risks.
Execute Reduce
Risk
Added Value Score
Redefine
Kill
Project
Risk Score
12. Example
A ssessm en t of Pr oject A
A ssesm en t
N am e Fu n ct i on RO I SM CA MI CR SV SA SU OR IR DU TU
A 3 4 3 2 5 3 0 2 3 2 4 1
B 4 5 3 4 5 2 1 2 3 3 5 1
C 4 5 3 4 5 1 1 2 3 1 5 1
D 4 4 3 2 5 0 0 2 4 3 5 1
A v er age W ei gh t Pr oj ect A 3,8 4,5 3,0 3,0 5,0 1,5 0,5 2,0 3,3 2,3 4,8 1,0
Assesment of Project A within Portfolio
Added Value Risks
Criteria ROI SM CA MI CR SV SA SU OR IR DU TU
Relative importance 4 5 4 3 2 4 3 2 4 3 3 2
Score T
Score +
Score -
W eight +/- + + + + + + - - - - -
Project Scoring
A 3 4 5 3 3 5 2 1 2 3 2 5 74 37 37
B 4 4 4 4 4 4 4 3 2 2 5 3 80 32 48
C 3 3 1 5 2 5 1 1 1 1 1 1 60 11 49
D 4 3 3 3 3 3 3 3 3 3 3 3 60 33 27
In this example project A has a positive score, but is only third in line within the
portfolio.
13. Assessment Matrix example
The assessment matrix shows that none of the projects is good enough to
be executed.
The model can be extended with a weight for Project costs in order to make
choices from a scarcity point of view.
14. Assesment Matrix with size
Added value
120
110 Execute
Reduce
100 Risk
90
80 B 30
100 A
70
60
C
50
40
30 25 D
20
Redefine
10 Project
Kill
0 Risk
0 5 10 15 20 25 30 35 40 45 50 55 60
It is not only possible to have analysis per project, but also it is
possible to cluster projects to themes.
15. Prioritizing
In PPM Deci si on process
• Continuity (Maintain) Budget
– Budget needed to keep to keep business momentum Pri ori ty < K€ 250 >= K€ 250
Mai ntai n No Yes
– Budget needed for mandatory changes Improve No Yes
Leadershi p Yes Yes
• Efficiency (Improve)
– Budget needed based on ROI for => K€ 250,-
• Business Innovation (Leadership)
– Budget reserved for high risk business innovation
• IT Innovation (Leadership)
– Budget reserved for high risk IT innovation
• Budget limits (<K€ 250,- change)
16. Literature
R.J. Benson (1991), Determining the value of
information Technology, in: “Handboek
bestuurlijke informatiekunde”.
J.A. Oosterhaven (2007), ICT-strategie en –
organisatie in theorie en praktijk, Sdu
Uitgevers BV, Den Haag.
17. 2control4IT
2control4IT is a consultancy company specialized on IT cost management, activity
based costing, IT charge back systems and added value analysis. 2control4IT creates
insight and transparency. These two elements are basic requirements for both
reducing IT costs and increasing IT added value. Transparency also works as a lever for
the quality delivered and is the basis for trust based management.
Services:
• Create transparency in IT costs
– Total cost of ownership
– Indirect costing analysis
– Cost modeling
– Benchmark support
– KPI Frameworks
• Create transparency in IT volumes
– CMDB cleaning
– Uniformity in incident and problem registration
• Create relations between costs and volumes
– Activity based costing
– Activity based management
– Activity based budgeting (including internal transfer prices)
– Scenario planning for strategic decisions
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18. 2control4IT
• Create strong business control
– Coaching
– IT business control training
– Interim IT business control
– Performance dialogues
– Change programs
Contact
2control4IT
Jeroen Hoevenberg
+31(0)6-5894 6176
Jeroen.hoevenberg@2control4IT.nl
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