Interministerial Collaboration to address policy system gaps

As both a policy student and a public servant I have seen numerous examples of what is referred to in policy as a “wicked problem”.  A wicked problem is defined by Wong as a “social or cultural problem that’s difficult or impossible to solve—normally because of its complex and interconnected nature” (Wong, 2020). Solutions to wicked problems are often complex and involve multiple sectors, and may at times outline macro challenges with underlying system gaps (Rao, 2019).

My focus as a student and public servant has been applying the client centered approach to develop a strategy to close gaps for clients involving a careful analysis of the systems and structures to ensure these gaps are addressed (Roundtreee and Pomeroy, 2010). 

Research suggests that collaborative networks and strategies are key to resolving complex problems (Agranoff, 2006). In government, effective leaders are able to apply interconnected strategies within Ministries and intersectorally at the Municipal, Provincial, and Federal level. The interconnectedness of the public sector involves problems that cross traditional boundaries which at times require collaborative strategies (Longo, 2019). Being aware of the cross jurisdictional issues as well as strategies to address them is key. Interministerial committees and joint initiatives are both methods public servants utilize to support the common client.

Conklin outlines the steps to true collaboration which includes the need for all members of the team to be a true part of the decision making process.

The first two steps are:

  1. Developing a shared understanding of the problem. This step is key as often the “problem” may be defined differently by each sector; next develop a
  2. Shared commitment to potential solutions, as well as a clear agreed plan on how to address (Conklin, 2020).

Examples of these system gaps often appear in the areas of homelessness, poverty, addictions, domestic violence, and mental health. All five areas are often supported by different agencies, and responsibility at times falls to specific Ministries.

Looking specifically at homelessness in Saskatchewan, not one specific Ministry is responsible which can result in gaps to clients. One Ministry may have a mandate to support clients at a specific point of time or system specific such as the hospital, correction systems, or financial assistance, however there is not an overall mandate to address these complex issues.

Research has shown clients with multiple factors often face the biggest system gaps and require support to navigate multiple systems.

Policy analysts  play an important role in closing the gaps and addressing societal issues.  Prates describes this role as “effective connection between policy, science and society” (Prates, 2020). O’Leary speaks about the importance of public servants being aware of system gaps and the need to form Intersectoral partnerships (2012) .

Cross sectoral impacts of homelessness are evident requiring a cooperative approach by ministries, various levels of government, along with coordination with the community.  Coordinated strategies involve identification of system gaps and strategizing together to address common issues.  In Saskatchewan some of the main stakeholders in this area are Ministry of Health, Education, Addictions Services, Corrections and Public Safety, and Social Services. Coordination and communication between these stakeholders is key. Awareness of each systems mandate and ability to support shared clients as well as a development of a shared pathway to support is crucial.

When you look specifically at homelessness in Saskatchewan, several municipalities have completed research and developed plans to end homelessness in the last few years. The research outlines the high shelter-income-ratios for households as well as the cost efficiency of providing supports to reduce costs for numerous sectors including health and justice. Saskatoon’s study outlined the need for Interministerial support in order to effectively support clients in homelessness (Reaching Home: Canada’s Homelessness Strategy; Saskatoon Community Plan).

This strategy is transferable across service areas specifically in the human services sector. 

Collaborative strategies that work include a joint understanding of the issues, agreed outcomes, strong communication, as well as a commitment from all parties toward the agreed outputs. Collaboration has proven to reduce silos and bring multiple divisions and agencies together to work on a common goal, often resulting in innovative strategies and increased efficiency.

As a policy analyst champion innovative strategies that step outside of the box to explore alternative new ways to address issues. Ensure stakeholders, and specifically the clients impacted by decisions have a voice in proposed changes. When possible work Interministerially toward positive outcomes for cross divisional clients, applying the approach of “One Team” by reflecting the goals of diversity, inclusion, and reconciliation, which will support positive social impact.  Piloted projects and Interministerial partnership such as HUBs show that coordinated services leads to better outcomes for clients.

Reference List

Agranoff, R. (2006). Inside Collaborative Networks: Ten Lessons for Public Managers. Public Administration Review, 66, 56-65. Accessed January 12, 2021, from http://www.jstor.org/stable/4096570

Cohen, Allan and Bradford, David. 2017. Influence Without Authority. Hoboken, New Jersey: John Wiley  & Sons, Inc.

Conklin, Jeff. October 2005. Dialogue Mapping: Building shared Understanding of Wicked Problems. CogNexus Institute. Accessed January 15, 2021. https://cognexus.org/wpf/wickedproblems.pdf

Coughlan, Paul and Ana Carolina de Almeida Kumlien. October 18, 2018. “Wicked Problems and how to solve them”. The Conversation. Accessed August 2020. https://theconversation.com/wicked-problems-and-how-to-solve-them-100047

Engel, Jim. 2020. JSGS  808 Ethical Leadership Course Material. ““Resilience and Healthy Workplaces  Power Point Presentation”.  March 12, 2020.  

Everyone is Home: A Five- Year Plan to End Chronic and Episodic Homelessness in Regina. Accessed December 2020. http://endhomelessnessregina.ca/wp-content/uploads/2019/06/P2EH-Full-Final-0610.pdf

Government of Canada. 2021. Public Safety Canada: The Hub Model/ Situation Table, Accessed August 16, 2021. Crime Prevention Inventory (publicsafety.gc.ca)

Government of Saskatchewan. 2016. Taking Action on Poverty: The Saskatchewan Poverty Reduction Strategy. Accessed October 2020. https://www.saskatchewan.ca/government/news-and-media/2016/february/24/poverty-reduction-strategy

Graham, John R., Shier, Michael L., and Roger Delaney. 2017. Canadian Social Policy: A New Introduction,   Fifth Edition. Toronto: Pearson

Kouzes, James M. & Posner, Barry Z. 2003. The Five Practices of Exemplary Leadership Article. Pfeiffer, A  Wiley Imprint.

Longo, Justin. 2019. JSGS  807 Statistics of Public Managers Course Material.

Marshall, Jim. 2020. JSGS 838  Financial Management Course Material. “Week 6 and 7 PowerPoint”. UR Courses.

Nilson, C. (2014). Risk-driven collaborative intervention: A preliminary impact assessment of Community Mobilization Prince Albert’s Hub Model. Saskatoon, SK: Centre for Forensic Behavioural Science and Justice Studies, University of Saskatchewan. Available from: http://www.mobilizepa.ca/tools-docs/documents/risk-driven-collaborative-intervention
Notten, Geranda & Laforest, Rachel. 2016. Poverty reduction strategies in Canada: A new way to tackle an old problem? United Nations University.


O’Leary, Rosemary & Gerard, Catherine. 2012.  Collaboration Across Boundaries: Insights and Tips from  Federal Senior Executives. The Maxwell School of Syracuse University


Ontario Ministry of the Solicitor General. (2016). Guidance on information sharing in multi-sectoral risk intervention models. https://www.mcscs.jus.gov.on.ca/english/Publications/PSDGuidanceInformationSharingMultisectoralRiskInterventionModels.html


Prates, Ines, January 22, 2020. “How to use evidence in policymaking. Can evidence in policy be the antidote we need for climate change?” Apolitical. Accessed April 2, 2021. https://apolitical.co/en/solution_article/how-to-use-evidence-in- policymaking#:~:text=Why%20is%20evidence%20in%20 policy%20important%3F&text=In%20this%20context%2C%20 there%20is,key%20scientific%20findings%20into%20account

Rao, Saskriti. September 5, 2019. “The Gaps Model of Service Quality: Chapter 3”. Mad About Growth. Accessed January 2021. https://medium.com/madaboutgrowth/the-gaps-model-of-service-quality-chapter-3-30fc290f06b0

Reaching Home: Canada’s Homelessness Strategy; Saskatoon Community Plan 2019-2024. Accessed December 2020.
https://strategicmanagementmusingshome.files.wordpress.com/2021/10/d1e8d-saskatooncommunityplan-2019-2024.pdf

Rocha, Cynthia J., and Alice K Johnson, “Teaching Family Policy through a Policy Practice Framework.” Journal of Social Work Education, 33(3) (1997), 433–444. Academic Search Premier, EBSCOhost (accessed March 10, 2007).

Rountree, M., & Pomeroy, E. (2010). EDITORIAL: Bridging the Gaps among Social Justice, Research, and Practice. Social Work, 55(4), 293-295. Retrieved September 7, 2021, from http://www.jstor.org/stable/23719696

Wong, Euphemia, December 2020. ‘Can you solve it?” Interaction Design Foundation. Accessed  January 10, 2021. https://www.interaction-design.org/literature/article/wicked-problems-5-steps-to-help-you-tackle-wicked-problems-by-combining-systems-thinking-with-agile-methodology

Saskatchewan’s Homelessness Crisis

 Canada has high homelessness rates with 35,000 Canadians experiencing homelessness on any given night with as many as 50,000 as hidden homeless (couch surfing etc.). Saskatchewan although we have no major cities – has high homelessness numbers, especially in Regina and Saskatoon. In Regina the number of homeless is larger than average for most cities in Canada per capita. It is estimated at approximately 2,000 people. Homelessness is hard to measure each year there is a PIT count (Point in Time Count) done where agencies call for volunteers to assist with gaining the true numbers of homelessness. What causes homelessness? When questioned during one of these PIT counts out of 139 respondents 18.3%% said they had experienced abuse, 20.2% said they had family conflict which included spousal abuse, 14.2% said they had job loss, 27.7% said due to addiction or substance abuse, and 19.6% said due to their inability to pay rent.

Indigenous homelessness is increasingly rapidly across Canada particularly in urban settings. 28-34% of the shelter population is Indigenous. A study completed across Canada gathering data from numerous shelters the shelters were comprised of: 15% LGBTQ2, 51.4% Women, 25.7% Indigenous, 7.1% Veterans, and 25.7% were others (male/youth). Stat’s Canada completed a study in over a period of time referencing 2016-2018. What they found was that the number of people accessing shelters in decreasing but the number of bed nights used by individuals in increasing (https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1410035301). Specifically in Regina a PIT count was done in April of 2018, 286 people were found homeless and an additional 2,000 not included in the research. Out of the 286, 91 stayed in Emergency shelters, 85 were couch surfing (often considered the hidden homeless), 81 stayed in transitional housing facility, 6 stayed in makeshift shelters in public spaces, and 3 were accessing Detox or hospitals as a place to stay.

What caused homelessness? We know that rental rates or quite high in Regina, this contributes to 20% of homelessness. Average Rental rates in Regina are: 3 bedroom – $1,290.00, 2 bedroom – $1,205.83, 1 bedroom – $961.25 and bachelor – $711.50 . 25% of Canadian renters spend more than 30% of their income on housing. Specifically in Regina, 12 % persons measure low income after tax, and 22.1% of households spend over 30% of their income on shelter. What are the answers how do we address homelessness? We know that it is cheaper to provide increased supports, reduce homelessness, as costs more to support people through the criminal systems or the hospital. One study showed that it costs $15.00 per day to provide housing supports to homeless, in lieu of $364.00 per night in hospital, or $144.00 per day in jail. Some families on income assistance only have $1,000 per month to cover rent, food, transportation and other facilities. Often the result is eviction notices when there is a constant shortfall. The new Saskatchewan Income support program rates are $575.00 for singles, $750.00 for couples, $975.00 for families with 10 or 2 kids, and $1150 for families with 3 or more kids. These shelter rates include rent and utilities. Options are often limited for families. Increasing social housing availability and housing supports will decease costs of shelter use. What do we currently have in Regina? We have the housing continuum: homeless, emergency shelters, transitional housing, social housing, and affordable housing, followed by ownership options. Social housing rates in Regina are affordable and often there is availability, however there is a long wait list for larger families and there are limited options for singles. What programs are working? Housing First Program was started in 2016 in Regina. Since their inception there has been 81% police call reduction, 89% arrests reduction, 40% days in hospital reduction, 75% less ER reduction, 66% EMS reduction, and 93% Detox visits reduction. Phoenix Residential provides supports to some of the higher acuity members, they find it hard to keep up with the demand. The proposed five year plan for Regina proposes spending $63 million to address homeless which is reportedly less than the $75million that the same population would cost health and the criminal system if left as is. The National Data Survey set I uploaded shows the limited supports we have in Saskatchewan. Saskatoon has 306 beds in 23 shelters, wherein Regina has only 256 beds in 13 shelters. Statistics Canada has completed several reports about this issue, one notable data set is completed in 2017 on the 2016 data. “Core housing need” which is used data to tabulate dwellings considered unsuitable, inadequate or unaffordable and whose income levels are such that they could not afford other options. These high core housing needs often lead to homelessness. Saskatchewan had a 13.5% Core housing need (https://www12.statcan.gc.ca/census-recensement/2016/dp-pd/chn-biml/index-eng.cfm).

What is needed is increased supports up front and more support put into preventing homelessness. We know what the major factors are, if we focus on the harder to house and provide good tenant support, increased addiction support options, and easier access to social housing stability will be increased. How do we ensure who is housed doesn’t become homeless again? Access to funding for those who have rental arrears, so instead of eviction and needing to move and start over again which includes a new damage deposit – one time support is made, with training and supports to ensure the cycle leading to this incident doesn’t continue to occur. Our homeless population knocks across the doors of detox, hospitals, police, addiction services, housing, and other centers. Increased collaboration between the areas will ensure they are supported completely. Coordinated entry systems with online access point can ensure the different service areas communicate. Using predictive analytics to apply increased supports to those at greatest risk of eviction or currently homeless needing emergent support. See my Google Data Studio Report/ Two page Infographic about this issue.

https://www.google.com/url?q=https%3A%2F%2Fdatastudio.google.com%2Freporting%2Fbe443fe8-1c44-4735-afc5-7681e5aba790%2Fpage%2FlNG8 Click here Get involved let your city councilor know your thoughts.

Source List: Amy Brison- Enterprise Media (2014) “Impact of Affordable Housing on Families and Communities: A review of the evidence base” https://www.enterprisecommunity.org/resources/impact-affordable-housing-families-and-communities-review-evidence-base-13210, Accessed December 5, 2019.

“Everyone is Home a 5-Year Plan to End Chronic and Episodic Homelessness in Regina”- Executive Summaryhttps://docplayer.net/151152716-A-5-year-plan-to-end-chronic-and-episodic-homelessness-in-regina-executive-summary.html, Accessed December 4, 2019.

Stephen Gaetz and Erin Dej. (2017) “A New Direction: A Framework for Homeless Prevention” https://homelesshub.ca/sites/default/files/attachments/COHPreventionFramework_1.pdf, Accessed on December 3, 2019.

Stephen Gaetz, Fiona Scott, and Tanya Gulliver (2013) “A Framework for Housing First: Housing First in Canada: Supporting Communities to End Homelessness” (www.homelesshub.ca/housingfirstcanada

Stephen Gaetz, Erin Ej, Tim Richter, & Melanie Redman (2016): “The State of Homelessness in Canada 2016. Toronto – Observatory on Homelessness”

Stephen Gaetz, (2012) “The Real Cost of Homelessness: Can we Save Money by Doing the Right Thing? https://www.homelesshub.ca/sites/default/files/attachments/costofhomelessness_paper21092012.pdf Accessed on December 3, 2019.

Statistics Canada. 2019 Dimensions of Poverty Hub. Accessed on December 6, 2019. https://www.statcan.gc.ca/eng/topics-start/poverty

Statistics Canada. 2017. “Core housing need, 2016 Census” https://www12.statcan.gc.ca/census-recensement/2016/dp-pd/chn-biml/index-eng.cfm, Accessed December 6, 2019.

Statistics Canada. 2019 Table 14-10-0353-01 Homeless shelter capacity, bed and shelter counts for emergency shelters, transitional housing and violence against women shelters for Canada and provinces, Employment and Social Development Canada annual (number) Accessed on December 2, 2019. DOI: https://doi.org/10.25318/1410035301-eng

Statistics Canada Website https://www150.statcan.gc.ca/n1/pub/75-006-x/2016001/article/146-eng.htm#a11 Accessed December 8, 2019: Statistics Canada Website https://www150.statcan.gc.ca/n1/pub/75-006-x/2016001/article/146-eng.htm#a11 Accessed December 8, 2019:

As a Policy Analyst in the Public Service it is important that all facts are accurate and the information is clear and correct when presented to the decision maker. Data Analysis using visuals has its place but sometimes Visuals do not show enough information or may not clearly represent something. Cabinet Decision Items for most Ministries do not use visuals but rather describe the situation clearly and briefly. When presenting information visually as a Policy Analysis it is important to use a persuasive presentation and not manipulate the data or visuals. What is the difference between a persuasive presentation vs using visuals to manipulate?? How do we ensure we aren’t manipulating? Ethical integrity is very important in analysis and presentation and is a requirement for public servants. Leadership rely on the information provided to them to be accurate and unbiased. Clear wording must be used, avoid words that can be interpreted different ways. In the public service major decisions affecting multiple people are made base on the analysis. Data must be clearly defined with clear sourcing. Does the data display show all the accurate information or for just a specific favorable period of time? Be honest show all data, even data that doesn’t fully report your recommendation. The Decision maker must make an informed decision. It is important to learn how your Decision Maker prefers his information some wish for no visuals whatsoever and some are ok with a mixture. Visuals have their place but can’t replace clear data. If making visuals do not just show the positive statistics or the statistics that support your recommendation, but rather show all sides of an issue. Identify other alternatives or explanations for specific data rather than skewing it to support your suggestion. Ethical Policy Analysis means reporting on all of the areas requested not just on areas you wish are reviewed. Ethically it is important all data is provided not hidden when the statistics aren’t favorable.

The public needs an increased understanding of what probabilities mean. When making decisions in public policy, percentages and probability statements are useful. When a policy analyst breaks down specific issues and outlines the percentage of a specific issue this directly connects the user to the possible impact. If we indicate there is an 80% chance of being assaulted in a specific area, this may impact a person’s willingness to travel to a specific region. Possibility and likelihood of issues and breaking it down to the public is important and is good public policy. When discussing climate change if we discuss this issue as a whole it often doesn’t hit home for people as they feel there is such a low possibility of specific issues arising, if we instead provide the likelihood and list the possibilities of specific issues arising, the public may realize how very real this issue is. Listing the percentage of single use water bottles and listing the probability of results if we reduce single use water bottles and the possible impact creates a direct connection for consumers. Most decisions in government are made with risk management discussions and assessments. We study what is the probability of a specific issue, how likely something will happen versus is this an issue that is very unlikely to happen. Public policy analysis needs to display probabilities in a way that the public can understand the direct impact and explain what things mean. If economists are predicting a slump in markets and housing costs, decisions need to be explained while outlining the strategic plan how the government can counteract those issues. Governments also need to analyze data about events that although having a low probability could be quite catastrophic such as floods, earthquakes, etc. Probabilities often reflect many uncertainties so at times can make consumers and the public leery of their accuracy or believability. Predictive analytics has its strength, the data can help us attempt to predict issues before they arise. For example analyzing a customer’s credit score helps a creditor predict the risk assumption with each customer. The same can be displayed with other social issues, the “credit scores” of particular sectors can assist with the prediction of fiscal reports and budgets. Predicting problems before they arise is useful. These theories are applied in justice, policing, etc. Policy Analysis itself makes proposals including status quo “doing nothing” and provides comparative analysis with predictions on what may happen when you explore alternate outcomes. These clear analysis and comparisons can assist consumers with gaining a clear understanding of why specific decisions are made. #jsgs807 and #probabilities.

Is the new improved Well being Index, and better way to measure “well-being” than the HDI index?

The Well -being index: a better way to indicate wellbeing? Let’s compare this method to the HDI index. Currently the UNDP Human Development Index is used a common method to rank countries. I am proposing a new “wellbeing index” as a better method to indicate true wellbeing of countries. To test this I gathered data from the HDI Public Data Explorer. I isolated different dimensions and indicators for 2015. I chose Health as my first dimension with the indicator of life expectancy at birth as it is the best indicator of true “health”. This indicator includes mortality rates which is a great indicator of true wellbeing. My second dimension I chose is Work, Employment, and vulnerability with the indicator of Employment to population ratio, ages 15 and older. I chose this indicator as high employment is a sign of a healthy country. Studies indicate high unemployment rates go hand in hand with poverty and crime rates being inflated. My third dimension chosen was Socio-Economic Sustainability and I looked specifically at the indicator of percentage of the skilled labor force. This is important for showing a countries health as it takes into considering education and training levels. After calculating the wellbeing index by taking these factors and measuring the geomean, the top six countries are Korea, Qatar, Guinea-Bissau, Burundi, Dominica, and Rwanda. This is extremely different then the top scoring countries for HDI they are: Paraguay, Tonga, Azerbaijan, Guatemala, Togo, and Japan. Why is this so different? The Human Development Index uses a combination of data, it uses Life Expectancy Index, Education Index, and the GNI index. These indexes take more factor’s into consideration. Using the HDI index Korea which is number 1 in my Wellbeing scores #27.

Simulations are being used as a tool to inform policy!

There are so many interesting ways to apply simulations to inform policy and make positive changes. One way i had the opportunity to try was the Uber Game ( https://ig.ft.com/uber-game/). First i tried the Easier version, my goal was to meet the $1000 goal for the week. There were really unique elements designed into it, you could chose the car to rent, the things you needed including a gym pass, (which only option given was to shower in it, i was never given the choice to work out.) This game was a great simulation of what being an actual uber driver would be. I think more of these game scenarios should be created for career planning for High school students. It gives a person a good taste of what a day in the life would be like. Although this game isn’t very high tech it gave one the opportunity to make choices like how you would react to a customer in different scenarios, and how far you should drive, and when you should call it a day. Not surprisingly i didn’t call it a day often and ended up working many hours, thus reaching more then the goal amount. I had to try again in the harder version as well, and just as before i made choices that had me working lots of hours, i think 80 to be exact, so i made the bonus and reached the goal income. Uber is a new advancement and an example of the “Sharing Economy”. There are companies utilizing this theory in different ways such as peer to peer sharing. There are a few businesses also developed on this premise. Tradebank is another example, a business performs the work and then is paid in tradebank credits. The business then can use these credits to obtain services in something else available on tradebank.

Simulations are such a unique way to study policies, i would like to use simulations as a way to question Canadians about how they feel about climate change and use their choices as a way to inform upcoming policies. Young Canadians are more likely to complete such a questionnaire if able to do so by playing a game such as this. The kind of data you would need included in this questionnaire would be solutions people would be willing to try to improve the environment. Giving the user similar choices such as in the Uber game as to what time of car you would buy, what food you eat, what type of energy you use. All of these choices could be captured to help inform consumer where consumers are in their willingness to make such changes.

In class we tried a simulation tool called the Global Calculator which allowed people to make choices about how they were going to ensure the C02 emissions stayed under the 2% marker. Check it out as well as it is very information. http://tool.globalcalculator.org/globcalc.html?levers=22rfoe2e13be1111c2c2c1n31hfjdcef222hp233f211111fn2211111111/dashboard/en

Just how much do University of Regina Profs make?

The University of Regina annually publishes salaries of employees with a total of $100,000 or more.  Click here to see attached Google Sheet (U of R Prof wages). It doesn’t specifically say which positions are professors, Deans, etc., but when you Google a few of them it seems that most are Professors or Deans from different Faculties. As there are 513 listed employees I did not completely research this due to time constraints. There is sparse information in the spreadsheet so I was unable to do a good comparative analysis. It provides data from 2018 and 2019 so we are able to do some limited comparisons. It does clear up that not only to U of R employees have salaries they also receive Administrative/ Research Stipends, and Market Supplements. What are Administrative, Research Stipends and Market Supplements? Are they a way to hide true salaries or a form of bonus? Are these total salaries a fair wage in comparison to other Universities? This blog will explain the data, verify the data, and further analyze what this data tells us. My Data analysis spreadsheet is attached below.

What all is included in this spreadsheet? The first few columns show the first and last names of the people. Next you can see the information salary specific in both 2018 and 2019 separately. The spreadsheet also has columns which show Administrative/ Research Stipends and Market Supplements in each year. This is listed specifically for each individual. The data table also totals up for each individual the Total overall Salary for each year. I was unsure how totals were calculated in this spreadsheet as there were no formulas, so I completed calculations of my own. I used Excel formulas to obtain a sum of all 2018 costs and 2019. I calculated these separately for accuracy adding both directions. There appears to be an error in the calculations for 2019 Total Salary there is a difference in $69,207,212.39 is listed however the total is 69,203,654.39 which is a difference of $3558.00. What explains this discrepancy? Is this the only discrepancy? This is of major concern as it affects a lot of the data.

In studying the differences from year to year of note in 2018 #73 employees reported in one year but not in the other, whereas in 2019 there are only 36 staff with zero income. This shows an increase of 37 staff in 2019 which may account for the increases in salaries spent on employees. This indicated 467 people in 2018 with income over 100,000 and 504 people in 2019 with income over 100,000.  This is an 8% increase in staff. This increased staff number is not definite as it could mean more staff entered the income threshold. Of the 36 staff who not reported in 2019 a large majority appeared to be well below the average wage. Were they newer staff who have since found better paying jobs elsewhere? It would be good to know which employees only just appear in one or the other as they were raising to the $100,000 threshold. I had insufficient data to fully explore this theory.

In Reviewing the U of R 2017- 2021 Collective Agreement in Appendix A and B, it explains the Salaries, Supplements, and Stipends. In addition to regular salaries, Heads of Academic Departments as well as Library Department Heads receive a stipend, they are taxable income, basically a bonus for being a Department Head. This stipend depends on the department and responsibility. Increases are decided similar to Out of Scope Government employees in that Performance reviews are used to determine if increments are approved. This is where student reviews and questionnaires come into consideration. Stipend also refers to amounts paid for specific works, a Sessional course developer received $9,000 to develop a course. Administrative/ Research Stipends includes payments for Travelling, Accounting Professional Fees, and the U of R Trust Fund. Market supplements are used to recruit academic staff members or keep members in the position, it is only to be paid when there is proof that academic pressures in the academic market require such payments. There is a limit on the max of market supplements however there appears to be quite the broad range. Why are these costs kept separately rather than included in the salary? In 2018 these Market Supplements added up to $1,033,715.00 while in 2019 they rose and totaled $1,157,168.60. The salary Range in 2018 when we exclude the 0 category is $100,007.00 to $365,998.00 whereas in 2019 the Range is $101,196.00 to $388,025.00. The Market Supplement also has quite the broad difference ranging in 2018 from $1,644 to $22,784 and in 2019 from $1,673 to $23,184. I calculated these ranges by using Max and Min function formulas. Why is there such a broad range in this area? Are the professors with the highest Market Supplements those with extensive resumes and experience or an area very hard to hire in? We don’t have this data readily available as this spreadsheet doesn’t show what area the staff is from or their role. How many of the staff received this? In 2018 108 received on average $9,782.00 and in 2019 114 Employees received and average of$10,354.00. This was a 12% increase.          

 The Administrative Category is also quite broad and ranges from $2,500 to $27,500 in 2018 and $1,873 to $27,675 in 2019. However this information appears clearer as the Administrative Stipends appear to refer to specific Department Head Stipends. The Collective Agreement clearly outlines the amounts paid out in each of these roles. The biggest jump from year to year was in the Administrative/ Research Stipend as it increased 38%. The average rose from $7,423.00 to $9,059.00.

So with Administrative Stipends, Market Supplements, and Salary do Professors in the University of Regina receive a fair wage. In My Data Analysis Tab I completed numerous calculations I calculated the average income of in 2018 to be $115,921.96, and the average rose to $128,154.92 in 2019. The salaries rose between 2018 and 2019 at a rate of 9%. Calculating the average was also complicated. I calculated 9% increase however another calculation expression is 3%. Why such a big difference and what is the correct one. The difference here is when you explain the average as a mean or median. When using the MEDIAN of total salary which is not sensitive to extreme scores and a better definition of the midpoint, for 2018 and 2019 total Salary with all additions you get $125,169 in 2018 and $129,417 in 2019 which is only a 3% increase.  Using another calculation and not taking market supplements and other additions into consideration you could report the salary alone barely raised from 2018 to 2019 changing from $132,035 to $133,449. This is an only 1% increase if you add in total salaries with market supplement etc. you get the 9%. I calculated the 9% when using the percentage change option =newvalue – old value/old value with the mean being used as the definition of average.  All calculations completed showed an increase in salary in 2018 to 2019 even though some with the salary only additions are at a rate of only 1%.To me the Range is a more interesting data set in this spreadsheet. The MODE calculation was also very interesting as it was $106,571.00 in 2018 and in 2019 $103,385.00. Thereby these two incomes were the two most common total incomes in these timeframes.

The information I would like to know when looking at this data, my “wish list” is what is the specifics of each position? There is a broad range of employees at a University, what is their seniority rate of pay? If a professor, how many classes does he/she teach? What are the size of classes they teach, is there a per student ratio affecting their pay? What are the reasons behind the Market supplements? Another question I had from the data provided do these salaries include all expenses such as travel and S4’s? Depending on the role this may be a large part of the employees’ job thus swelling the salary cost.

When comparing with University of Saskatchewan Salaries are posted once they reach $125,000 or more (U of SASK salaries). It is hard to tell if the spreadsheet provided is comparative as the U of R one provided is not broken down by job. U of Sask reports as 1/3 of their funding is from public funds they are obligated to report the higher earning wages.

Now that we know this information is public is it appropriate should it be there? Is this not violating the professor’s privacy? This is discussed in Privacy and open government. Future Internet, 6 (2). I would think in a small city Regina’s size the listing of their wages may make them targets. Does the public deserve to know? In reviewing other public sector jobs such as Government of Saskatchewan Social Services and Health employees, these wages are also public.  On one hand with the tuition increase it was the question public and students were asking was this a direct increase to the professors? Interesting enough though is that some wages may be excluded as the disclosure could threaten the safety of the individual. Why is it safe for some but not for others as the spreadsheet only shows those with wages over $100,000? If some members can ask their information to be protected then this data is not wholesome and may miss a large portion of employees. Is this then a true picture or is the averages skewed?

I found it interesting that this information and other Public Employees info is so public. Overall Public Wages should be public as public funds help cover these wages. Although this information used to be available only through the library it is now publicly available. This is modernizing the availability of this data and keeps them in line with other Public Employees in Saskatchewan.   Public Employees are accountable to the Public and as such their salaries are public domain. Drawbacks to this data being so open is targeted marketing, as well as legal ramifications should liability issues arise personally for these individuals. Privacy concerns exist when this data is in the wrong hands. I think this need to protect personal privacy is balanced by the rule that exists in Regina for people to request their information to be withdrawn. It would be helpful if there was a way their info is withdrawn but the data remains such as Anonymous subject #1, as should not they still be entitled to release the data? As information was limited prior accessible only through the library this would have highly limited who could obtain the data. Could a balance be sought, online library requiring a sign in an out option?

Overall this data is interesting but it is missing the mark in some areas making the data quite incomplete. I don’t feel this data gives me the full picture of U of R Employees wages and is it doesn’t break down the positions I wasn’t able to do a comparative study to other Universities. Any future releases of this data should include these breakdowns.

https://1drv.ms/x/s!AlyR3GUdG3gKhE8cjFVow8y1Fn3W   My Data Analysis

https://1drv.ms/x/s!AlyR3GUdG3gKhE8cjFVow8y1Fn3W

Statistical Analysis is important when creating good policy and running effective public administration. Program and policy changes need to be based on either societal changes or as a response to issues. How do policy consultants and their leaders know what areas to focus on it? Statistical analysis should assist good policy in the right direction can form prediction and assist with risk analysis. Measuring how high a need helps us focus on what areas would have the biggest impact. Should a problem facing 5% of the applicants be developed or should we focus on a problem affecting 95% of the applicants. Good policies take these measurements into consideration. Not only is statistical analysis important in deciding policy change it leads to accountable government. If a significant budget is spent on a low population and a small budget on another larger population group, is this informed decision making? Statistical analysis is an important part in evaluation of policy and projects. Often pilot projects are developed to address an issue, evaluation is required to show statistically were the outcomes achieved, did specific rates reduce? Public administrators must be clear with their statistics, how was the data gathered? Clear data is needed to assist their leadership with their decision making. Interpretation of the data must be ethically based and transparent. Statistics is used to form evidence-based decision making. However, at times data can be manipulated incorrectly to help support decisions. Clear ethical data analysis is key.