I hate numbers, can I learn to love numbers?? Yikes! All I wanted, was to enlighten myself with the Canadian system of government and enhance my public service career. I realize STATISTICS is a hurdle I have to cross! “This class isn’t just about numbers” ( My Prof Justin said), “…this course aims to make you an intelligent consumer and manager of statistical analysis through critical assessment and working first-hand with data…”. Too early to tell if I believe him. In the meantime, I am saddled with the task of writing on the benefit of statistical analysis for effective public administration. So here it is. Continue reading “IMPORTANCE OF STATISTICAL ANALYSIS FOR GOOD POLICY MAKING AND EFFECTIVE PUBLIC ADMINISTRATION”
The United Nations Development Programme (UNDP)’s Human Development Index (HDI) is used to measure human development of countries, which are then ranked according to their scores. The higher the score, the better a country is said to be ‘developed’.
I had to create my own ‘wellness index’ using their system. For my countries of choice, I wanted to use the top ten ranking countries from 2015. But because I also wanted Canada in by all means, I had to take out Singapore and Hong Kong. So based on that elimination, the ‘top ten’ countries from the UNDP HDI, 2015, for me was:
Canada (originally ranked 12. I wanted to see how Canada would fare with my own indicators, against these other countries, but still keep it at 10 countries)
My choices for Dimensions were- Inequality, Employment and Education. The corresponding indicators for those dimensions were ‘Inequality in Income’, ‘Labour Force Participation Rate (% rate, ages 15 and older, female)’, and ‘Mean Years of Schooling, Female+Expected Years of Schooling, Female’. Why did I go with these indicators? I wanted to see how these countries measured considering their overall income inequality gap against Labour force for females as well as overall quality of education for females. My thought process on wellness? Good quality of female education equals higher labour force participation for females, equals smaller gap in overall income inequality in the society, and that put together equals my own WELLNESS INDEX (WI).
How did I calculate my index then?
I had to use the existing formula within the UNDP’s indices calculating excel sheet which I downloaded. I had to adjust that formula with the figures from my indicators which I also downloaded from the UNDP’s webiste- http://hdr.undp.org/en/data. Generally, the formula as directed in the UNDP’s techincal document is in two steps:
- Identify the Dimension indexes = actual value – minimum value/maximum value – minimum value (For education index, however, the value of ‘mean years of schooling (female)’ derived is added to the value of ‘expected years of schooling, females’, which is then divided by two (2), to get the educational index)
- Producing the HDI (WI), which is expressed as the geometric mean of the three Dimensional Indices using the GEOMEAN function. See full details here
Although I must confess that instead of using the MIN and MAX values in excel to determine my own values, I just sorted in ascending/descending order (blame it on laziness). After all was said and done, how did these indicators change the ‘top ten’?
That is my new ranking having streamlined along those indicators. Canada went from the far bottom to the second highest ranking.
MY WI Vs. UNDP’S HDI
I guess the UNDP and I are on the same page when it comes to how we choose to define development beyond GDP and GNI, to include people (humans) and their capabilities/development to determine the overall development of any country. The greatest difference is that the UNDP obviously has more indicators than I do, and a wider range of countries than I do.
I am also saddled with the responsibility of coming up with a policy area that could benefit from simulation exercise. One of such policy issues that readily comes to me is the issue of homelessness. According to a report by ‘homeless hub’, about six thousand (6000) Canadian youths are homeless on any given night (homeless hub.ca, 2018). Of course this is not an issue that affects youths only, but is a growing social concern that needs to be addressed.
A number of factors could lead to homelessness, ranging from job loss and not being able to find suitable job, to fleeing violent homes, natural disaster etc. Homelessness is also tied to poverty. The path that leads to homelessness is not exactly a linear process.
As such, a simulation game that factors in a number of ‘What Ifs’ could look at the different possible causes of homelessness by making choices such as creating an identity (your status based on race, gender, age working or not, family size, single parent etc). Using different policy options such as social welfare ( child benefits, access to employment insurance, moving to shelter homes, etc). These are inputs that could help determine the most vulnerable groups to homelessness, as well as determine if and how social policy tools such as welfare has helped in combating the issue of homelessness. The type of choices made in the game could also give insight into whether or not people are aware of some of these options. This could help inform better policy options to come up with or refine existing ones to mitigate the issue.
There should be room for feedback on what people think could have helped prevent homelessness based on their identity and status built. The type of data that would help make the exercise more realistic would be information on researches conducted by organizations that work towards reducing homelessness, such as homeless hub, United Way etc. Also, data such as number of shelter homes, minimum income wages, etc could all add to make the process more realistic. We might want to also include options of social welfare that are available to people how might be homeless.
I found this while trying to do this blog, so feel free to try it-
Here are some resources I found useful:
Yaay, I made $1,125 driving an UBER! Of course, not a real-life drive/money, but on the UBER game (I wish it was real).
The challenge was to play the ‘Uber game’, make $1,000 a week. I have often thought about the possibility of becoming an Uber driver, should they exist in Saskatchewan, so it was good to have an idea of what that experience could look like through this simulation exercise.
Given, it is a game of inputs and outputs, pick a certain option, and it is designed in a way that produces a specific response to that item. This doesn’t make it any less fun or ‘real’ in a sense. I must say that I had tried answering the questions more than once, picking different options of responses, just curious about the output would be.
Like me, I am sure that lots of people think about the idea of becoming Uber drivers when available in Saskatchewan, and I wonder how many people like me, never stopped to think about the dynamics/challenges that comes with wanting to take on that responsibility. For instance, the impact on my schedule, peak periods are usually during events, and in the evenings. Would I rather be out making some money? Or would I want to be home with my family?
As far as how this impacts my thoughts on facilitation of sharing economy by governments, it makes sense that these types of interactions are encouraged, as in some ways I believe that it provides alternatives to traditional forms of transactions. However, I do believe that the greatest role governments have to play in all theses is putting in place the right checks and balances through regulation. Shared economy is growing, especially with younger generations. If not encouraged to grow within a safe environment for all parties involved to benefit, it may become a sector that becomes hard to control, considering how the process around it is mostly digital. So it makes sense that governments embrace shared economy as they are doing now, but provide the safety net within which the players can play through regulations, just as Toronto has done, and Saskatchewan is also working on.
So go ahead, play the Uber game, see how you fare, and be better prepared for making that decision when the time comes. Feel free to share your scores, and experience of the game in the comments section.
If you are wondering what I have done this time, I must say this isn’t about what I did, but about what Pew Research has done. My job, was to recreate charts from their data reports, using the existing raw data. For my sake, I hope I did it right!
I started this by identifying which charts I would like to recreate, using a topic of interest- ‘Women and Leadership’. The sub-topic chosen was “Public Says Women are Equally Qualified, but Barriers Persist”. You can find the report summary here .
Having downloaded the data set, I found it quite easy to match the questions that accounted for the chart I was looking to recreate, as the question number is found under the chart in the report. I must say that I had to first convert the file (downloads as an SAV file) into Excel Sheet.
The specific question (Q16a-Q16g) to which I had to recreate data was “What’s holding Women back from top jobs?” Find the results below:
I particularly found it interesting that the top two major reasons was that “Women are held to higher value/standards” than men, and that “businesses are not ready to hire women”. There is a different chart that also shows the version of responses related to women holding political offices.
My second data sets centred on what is best for women who want to reach the top in business, with regards to having kids, graph below:
How did I manage to arrive at these charts? Not really glad you asked, but I am obliged to say anyway:
For the first chart, I used the ‘COUNTIF’ formula in Excel, counting the number of cells within the range of the data that met the individual condition of variable provided within the Pew Research Data. Pew Research provided the values/labels of answers to questions sixteen (16) as -1/Refused: 1/Major reason: 2/Minor reason and 3/Not a reason. So for instance, to get the percentage of respondents who identified ‘Women Don’t Make as good managers’ as a major reason(1), I used the formula- =COUNTIF($A$3:$A$1837,1)/COUNTA($A$3:$A$1837), to which I then hit the percentage short-cut to arrive at the percentage value. Where the first bracket set represents the range of cells within the sheet that identifies as ‘1/Major reason’, divided by the second bracket which is the total number of respondents.
Using similar formula in the second chart, COUNTIFS, I adjusted the data range to reflect the different values I was looking to find the percentage of. For instance, to find out the percentage of me who said women needed to bear children early in their careers to climb to the top, I used =COUNTIFS($A$4:$A$1838,1,B4:B1838,1)/COUNTIF($B$4:$B$1838,1) to reflect the range of men agreeing to early child-bearing for women looking to climb in careers, in relation to the whole data (shown in the first bracket), divided by the total number of men in the second bracket.
I must say that I observed some slight variances in some of my numbers compared to Pew Research’s, which I believe is the difference in that their numbers does not reflect the non-respondents. There is overall variances of about +/-2% or within that range.
I get it! Relating with someone of the the same cultural origin (or almost anyone else, as there are personal values and ideals that often clash) is hard enough on its own . But to have to relate with people from other cultures? 😱😱😱
And that was what my survey was about- ‘How is your inter-cultural relationship’? The survey was created through Qualtrics software, and sent to family, friends and foes (just kidding about the foes). In all, there were fourty (40) respondents, with fifteen of those from social media and twenty-five from the anonymous link sent through text, e-mail, and WhatsApp. Even though this was not a real-life research, it helped me understand a bit about the people around me as well as myself and how well I have gone out of my way to relate with people from other cultures.
In all, there were eight questions, ranging from understanding the demographics (age, gender, races), to questions like understanding how people from one race relate with differing cultures. For ease of reference, I interchanged ‘race’ to mean ‘culture’. For gender, 57.89% of my respondents were females, 42.11% males. The highest cultural group of respondents turned out to be ‘Blacks or ‘African-Americans’ which accounted for 82.05%, followed by ‘Whites’ at 10%. I can’t say I am surprised about the percentage of Black respondents, I obviously need to mix more. People within the ages of 21-35 were the highest group to take this survey. These first three set of questions were ‘single answer -multi choice’ type of questions.
The next question was a slider that people had to use to show the level of their comfort in dealing with people of other cultures, to which 38.46% of people reported as extremely comfortable, while an evenly spread number of 15.38% reported as very, slightly, and moderately comfortable in dealing with people of other culture. Only 2.56% reported as very uncomfortable.
The frequency of relationship with groups was more of Blacks at 92.31%, with the most relations taking place within work/school, which interestingly shows the relationship more with white people at 71%. A matrix structure of question made it easy to place both questions side-by-side to reflect their inter-connectedness.
Ranking type question showed more preference for wanting to learn more about First Nations. As to whether or not people are willing to attend a workshop that could help them better understand how to deal with people of other cultures, 41% are not likely to, 28% neutral, and 31% are likely to.
This exercise wasn’t so much about the data analysis itself per say, but my exposure to conducting surveys, the process that goes into that, the collation of data, analyzing and interpretation of it. This can be transposed into almost anything about public policy or anything else for that matter, for which we seek to gain better understanding of through statistics, and the use of surveys.
The right survey tool is very key in conducting a survey, as well determining the right potential respondents, bearing in mind, how that can impact the results of your survey. Using Qualtrics for instance, I can see the number of respondents in real time, which is helpful in determining the right number of people I am comfortable to reach, as well as a graphical and numerical representation of the responses received in the ‘report’ section.
I also find that it was very helpful to create simple surveys, which made it easier for people to respond, and the fact that they knew it could be completed within a certain time-frame (1.6 mins). While this might not be a true representation of most real life surveys, especially in more complicated matters, the overall key lesson here or me is that:
- Understand the issue you are looking to deal with
- Determine your targeted audience (age, gender, working group, student, potential cannabis users or producers, etc)
- The survey tool
- What you plan on reporting back, and to whom
- The number of people you will require
- How much time it will require to fill out
- As much as possible, the simplicity of your questions
Finally, by now, I am sure you have figured out that my last question was a personal fun question to see who really loves me enough to score me an ‘A’ regardless, LOL. Fear not, I loved the audacity to say otherwise, how do I get better if no one tells me what they really think? Interestingly, 69% thought I deserved it. That in itself isn’t an ‘A’, but the good thing is this wasn’t a real life survey, if not, I was probably so done. But, on a more serious note, maybe it could be. It would have been interesting to understand what some of the hold backs are for us, and maybe this would help us be more aware of ourselves moving forward.
As you consider that, I am working to expand my circle with non-black folks, as even I have a lot of work to do in this area.
A special thank you to all those who took out time to fill my out survey, I appreciate it. Thank you (English), merci (French), gracias (Spanish), imiete (Kalabari)!
Reference: Evert Lindquist, Richard Marcy, (2016) “The competing values framework: Implications for strategic leadership, change and learning in public organizations”, International Journal of Public Leadership, Vol. 12 Issue: 2, pp.167-186, https://doi.org/10.1108/IJPL-01-2016-0002
This research paper was written by Evert Lindquist and Richard Marcy. The authors sought to bridge the gap between the Competing Value Frameworks (CVF) and the public sector. They believe that public sector leaders work in “over-determined” situations, where they have to find a balance between demands placed on them both internally and externally. While there are existing literature on leadership, they find none addressing situational leadership as a focus and how public service leaders might improve how they lead in “over-determined” environment.
The focus or context is on Robert Quinn’s CVF as it has a more encompassing approach on leadership, organizational culture and strategy. The main goal of the article is to explore how Quinn’s CVF can be applied to public sector strategic leadership challenges. To do this, the authors have put the research into four parts: the first part looks at the origin, logic and evolution of the CVF, the second part considers the usefulness and relevance of the CVF to understanding of public sector leadership and management, the third part identifies specific challenges and learning development exercises for public sector leaders at different stages of development. The final part reflects on the CVF and sets direction for where future research might go.
PART ONE- ORIGIN OF THE CVF: COMPETING VALUES AND INSTITUTIONAL CHANGE
The CVF was first articulated by Robert Quinn and some of his colleagues in the 1980s. There was a considerable amount of empirical and theoretical work put into it. The diverse values that exist within and across organizations create competing demands and views. Even though these values are equally considered important, to him, top managers and leaders are those who are better at “seeing and coping with contradictions and paradoxes which often emerge as conflicts”.
To explain the competing values and how leaders can assess situations arising from the different paradoxes and contradictions, Quinn put the framework within two dimensions around which the values were juxtaposed: (i) internal vs external focus, and (ii) centralization/integration vs decentralization/differentiation
From these two dimensions, come the four different information processing models (the quadrants)
- the human resource model i.e. the team
- the open systems model (adhocracy)
- the rational goal model (the firm), and
- internal process model (the hierarchy)
The authors believe that this model has the potential to provide better understanding of leadership, management and organizational strategy in the public sector.
PART TWO- THE CVF AND THE PUBLIC SECTOR
The authors, having come up with a framework of the CVF directed at the public sector, believe that the diversity of values present in the public sector is what makes the application of the CVF useful. They discuss this usefulness for developing public sector leadership and management from three different aspects:
- diversity of values: direct and indirect connections- as stated earlier, there are diverse demands, values and other considerations facing public service leaders sometimes they contradict one another, and sometimes they overlap. The authors believe these numerous values can be placed within the different quadrants of the CVF.
- diversity of organizational contexts: scale and breadth- the article recognizes public service institutes as “multi-faceted collection of diverse entities with distinct mandates and different scales of operation” (Lindquist and Marcy, 2016). They believe that even though the public service has the same general legislative and governance mandate, they are unique in what constitutes the notion of effective leadership and management. The CVF within this context is believed to be useful in ascertaining what people and units within an organization see as critical values and indicators of effectiveness
- Shifting governance contexts: evolving priorities, rotating ministers and executives- with changing governments is changes in “information process”. The CVF helps to provide the framework within which an ‘assessing up’ (engaging new top leaders) and an ‘assessing down’ (executives assessing organizational alignment of values and culture) can be done to ensure everyone is properly aligned to provide public good and services effectively.
- Diversity of external agents: reinforcing diverse values- public service leadership has to sometimes deal with external agents and respond to the direction of such agents and their demands/values. Examples are the Prime Minister, Treasury Board Secretariat, the Public Service Commission, etc. The usefulness of the CVF in this regard is that it can be used to document and categorize the numerous demands of the external agencies.
The authors believe the CVF is useful to students and instructors in assessing public organizations and leadership due to its many levels of analysis. They conclude that it has long been acknowledged that there are paradoxes in the expectations of public service managers and institutes. As such the CVF makes clear the challenges faced by the public sector, therefore the framework can be used to diagnose current culture and leadership capabilities.
PART THREE- COMPETING VALUES, KEY LEADERSHIP CHALLENGES, AND LEARNING OPPORTUNITIES
The authors look at shifting leadership contexts that require re-balancing of leadership competencies, while identifying useful approaches and learning exercise for each. Highlighting them as specific leadership challenges within public sectors, they show how the CVF can be applied, maximizing the self-diagnostic attribute of the CVF in the process. In the table below, I have highlighted the challenges stated and the authors’ recommendations on how the CVF tool can be applied.
|CHALLENGES||CVF TOOL APPLICATION AND/OR LEARNING EXERCISES|
|New governments and effects on top public service leadership||· Diagnosing individuals (self and others)
· Assessing individual capabilities as well as culture of the department in question
|Anticipating and navigating the arrival of new leaders||· Appraising the leadership style and competency mix of top leaders and the directions that governments might like to take departments and agencies|
|Beyond competing values: from balancing to transformation- the issue here is the challenges that organizations are likely to face when they require more transformative strategizing and deep change.||· The CVF provides lenses for a deeper interpretation of case studies in public sector innovation, and a better understanding of the often significant shifts which have to be made in how governments and public service leaders must shift their thinking to make headway on significant political, policy and service-delivery challenges
· mapping and analyzing the components and trajectory of departments, and considering the implications for identifying tensions and change management strategies
· Comparing and contrasting organizations using the CVF
In concluding this part, the authors note the importance of leaders at various phases of development interacting with each other, as the CVF is said to be an integrating framework which provides platform for sharing insights, and could foster dialogue across leaders from different generations and different levels of organizations. The assessments are to help learners understand how to re-balance executive or unit management teams.
This part almost makes the CVF look like a one-stop-shop solution to all leadership problems that could arise within organizations, simply by applying the CVF as a diagnostic tool.
PART FOUR- CONCLUSION, IMPLICATIONS FOR FUTURE RESEARCH
The article has shown the diverse ways in which the CVF can be applied in analyzing the leadership challenges in the public sector and how leadership development can be attained, how executives and team can respond to changing circumstances etc.
While we can apply the framework to analyzing competing values and leadership within public sector, other aspects stated in the article such as ‘balancing leadership team’ or ‘skewing them in certain direction..based on new government priorities..’ might pose a challenge. The public leadership is uniquely different from the private for instance, and people do not easily get reshuffled around.
Also, one question that still tends to be hanging is how to successfully apply this seeming complex framework to an already existing complex leadership demands within the public sector, especially when we put bureaucracy and the complexity of governance into the equation?
Couple years back, I had a blog page. No, it had nothing to do with policy matters. I was just a young troubled mind, struggling to survive and it was an avenue to express my struggles with others as I tried to make best of my life.
Social media – Facebook, Twitter etc were the order of the day, life was all about ‘likes’ and ‘followers’. Soon enough I told myself the efforts put into canvassing for likes and followers was not worth it so I let that go. My fight for social media presence soon faded, but not my resolve to attain new heights in life.
That fight to attain new heights in life led me right back to Johnson- Shoyoma Graduate School of Public Policy at the University of Regina. I applied and gained admission as a domestic applicant for the 2017 Fall Semester, having been rejected in 2013 as an international applicant.
While I enthusiastically looked forward to classes and attaining new heights, I did not bargain for what was to hit me in #JSGS882- Strategic Management in Public Sector by Professor Justin Longo tweets, blogs, zoom, seriously??? This was a world I thought I had left behind ‘follows’ and ‘likes’ were so far behind me I laughed every time friends told me I needed to catch up in the world of social media. A world I later realized I have become too afraid to re-enter. Then comes this Professor telling me this was going to be the new order of my life.
Of course I wanted to drop the class at the end of the first class, which by the way ended 10 mins early because we were saved by the fire alarm, thank heavens! But as the days went by, I started re-visiting twitter, created this blog, and opened up zoom profile. Then I remembered my experience on the second day of class in the first week of the program I had changed where I sat from the day before, I and other classmates who did got commendation from the Professor for the act of ‘creativity and show of leadership’.
What they did not know was that I did that because not just JSGS882 scared me, but I started to question my being in the program and thought ‘what the hell am I doing?’. But because my resolve to attain new heights is greater than that fear, I thought to myself this was a good opportunity to step out of as many comfort zones I have set for myself as well as face new fears, one of which was sitting in the front row. But if the Professor said it was a show of creativity and leadership, who am I to question that? The man has a PhD.
Why am I blogging instead of dropping this class? Truthfully, it is a compulsory course that’s why, so the sooner I get over with it, the better for me. Okay, that’s just part of it. But, I realized how much fun I had sitting at the front, and how empowered I felt stepping out of a comfort zone. So twitter, zoom, blog page- not want I want, but another opportunity to step out.
So here I am, decided to do this, it is a journey for me. I am not sure how much formality I am supposed to put into this, but hey, it is my name on the blog page, I can call some shots, within certain confines of course.
For the next couple of weeks I will talk about strategic management, I intend to push myself, learn, share my experiences, thoughts, ideas, and in the end, I hope to come out a better, redefined person than this very first blog.
I ask that you join me in this adventure of strategic management or as I like to put it Strategic Adventure.