Blog de GAIA Program
Master in Decision and Innovation
First at alI I would like to congratulate all of you for your participation in the activity and hope you have enjoyed as much as we did. As you know, all of us are immersed in a reality progressively taken over by AI.
In this activity related to the Human Resource Role in companies we wanted you to reflect on how AI can help HR to predict your personality and skills. We know this possibility raises unsettling scenarios akin to “black mirrror” plots.
So our first concern was to assuage any alarm AI’s potential could bias your performance of the experiment we wanted you to take part. Hence we asked you to submit, -without saying what was it for- at least, 2000 words in which, you would explain who you are, your hobbies, what aspects define you, how do you approach life, etc…
As you already know after doing the experiment you have been able to compare what IBM Watson Personality Insights program thinks about your “real profile” taking into account the analysis of your writing description within the Big Five model.
Beforehand, we provided you with extensive information on how the algorithm works on the Human Resource Role activity’s page 3 on www.gaianext.com
As IBM Watson recommends in order to obtain more precise results we advised you to write the 2000 words text in Spanish or in your mother tongue. Sorry if we misled some people into writing in Catalan, Basque or Galician because currently the program only analyses in English and Spanish.
Our intention was to introduce you through a scientific approach to the basis of IBM Watson’s fundamentals backing the AI´s IBM software. To support the experiment we invited Luis Eduardo Imbernon to lecture on AI’s potential for recruiting based on his PhD research on AI and education.
Before Imbernon’s webinar, students were asked two questions:
- Do you think that AI could really predict people’s behaviour and preferences?
71,1% thought that it’s possible
- Do you think that HR departments could take advantage of those predictions to face a recruitment process?
83% thought that it’s possible
After the webinar and the students experiment themselves with the IBM Watson Personality Insights, we asked two similar questions:
- Do you think that IBM Watson has provided you correct results about your personality using your 2000 words text?
76% thought IBM’s program was correct in its prediction.
- Do you think that this service performs better the work of guessing a candidate’s personality than a professional recruiter?
19% thought that IBM Watson perform better than a recruiter.
It’s clear that students’ opinions about AI’s power prediction on personality didn’t suffer significant variation after trying the software. On the other hand, regarding the second topic (AI’s ability to improve human recruitment) has suffered a significant decrease (64%) in the support students gave it in first instance.
It is true that the second question wording had probably pushed many students to reconsider their former sympathetic opinions towards AI potential. However, in light of this decrease of support for AI’ use in recruitment we wonder if students’ opinion were also strongly influenced by theirs visualizing a not-so-distant scenario where machines may effectively assess humans without taking into account human interaction, feelings and the ever present aspiration that chance and fortuitous meetings matter.
Welcome to the near future! Enjoy it!
Master in Decision Making & Innovation
During the second part of the Product Management and Productivity module, you have been requested to develop the activity “Twitter: Product Challenge”.
In the case the Expert Vanesa Barrero has shared with us some considerations after reading and assessing each team answers:
You can read the general feedback were she has pointed out important considerations about what you have achieved and need to improve!
What we should have learned (or at least, I hope so!)
- To gain awareness about some of the steps of product management process. Don’t forget to read the chapter to have the complete vision!
- How to face a product analysis in several perspectives: business, users and the product itself,
- New tools to describe and communicate your acquired knowledge: business, customer needs and requirements,
- Decision-making can be made not only from numerical data, it can be done based on several inputs: Long term objectives, business model, user needs, time constraints, technical constraints, etc. The hypothesis should be as objective as possible,
- It is possible to get out of the building and your comfort zone (Google),
- Teamwork is possible, enriching and enjoyable
- Everybody can translate ideas or research in a more visual way (canvases, wireframes, personas, matrixes) and it´s very helpful to communicate your ideas to others,
Some of the common mistakes:
Your exercises were great, because all of you follow the most of the process required and concrete an improvement. But I would like to point out several points you can have take into account:
General to all stages:
– Lack of steps: the prioritization and its reasoning, for example, was missed most of the times,
– Lack of explanation: why did you take each of your decisions?
– Lack of concrete info: Is the info presented relevant? Is it clear and concrete?
– Lack of supporting material for the surveys, interviews, sources, etc.
– Lack of clarity: listings, boxes, bold font, typography, and clear conclusion.
– Lots of copied material without additional reasoning showing its understanding or linked references
– Some of you did not define a different value proposition for every specific customer segment
– The business learning’s where not used in the reasoning or the prioritization
– Surveys were a clever solution for the lack of time but there were many without open questions. Close question narrow the possible answers.
– Too much demographic info: this kind of data was only relevant in few cases.
– Few interviews, and many of them without any conclusion or quote.
– Ask directly to the users to prioritize. It´s a source for your decision-making but it’s not your only one.
Ideation and Prioritization:
– Only based on users needs or personal opinion without reasoning.
– No decision-making: some of you did not choose one hypothesis to develop.
– Lack of criteria in prioritization. Very few of you have actually prioritized and explained the reasons behind your decisions.
– Very few groups were able to brief even one user story.
– Very few of you describe the hypothesis, the requirements, the steps, the metrics, etc. Most of you have only thought in the interface.
– The possible output or success of the proposal were not evaluated because I don´t have data as they were not real tested. The focus was about above all in you showing clarity and communication. Some of you did not explain the wireframes and their impact.
Please consider this as constructive criticism about areas that could be improved.
Really, congrats all for your work. All of you went through a difficult journey and you get to very impressive and original solutions.
It was a pleasure, good luck to you all, Gaians!
Master in Decision Making & Innovation
During the last month of November you have study the module Product Management and Productivity.
As part of the first mandatory unit of “Economics” you have developed an interesting activity: Analyse your Smart City!
The idea was to encourage you to approach the Economics definition, the two main areas Microeconomics and Microeconomics go through important questions like: How does the economy change? What is an economic cycle? And some others, to make you reason in a more specific context: The goal of this activity was that the students could be able to make recommendations of Strategic Planning in a medium and long term about a previous chosen City. The recommendations should be framed within the dimensions and indicators selected from the IESE report “Cities in Motion”.
From the Academic team, it is important to share with you some final comments about your performance during this activity.
We have based our assessment in each student’s fulfillment of the different stages
Stage 1: Choose the Smart City
Stage 2: Indicators Analysis
Stage 3: submission of the final document with the city analysis considering some specific requests:
1. Present in a table form the data that you have found of each indicator.
2. Carry out a brief SWOT analysis (Weaknesses, Threats, Strengths and Opportunities) of the chosen city. Do it in a reasoned way and according to the selected indicators (16).
3. Make medium and long-term strategic planning recommendations for the chosen city in two of the chosen dimensions from the IESE study.
4. Depending on the elective unit chosen in your 2nd week (Financial Crises or International Institutions) try to contextualize your answer:
– How has the international financial crisis impacted on your City’s strategy? Compare the evolution of your position in the “Cities in Motion” index and indicate 1 or 2 reasons that, in your opinion, explain this evolution.
– Which are the “Smart Cities” development strategies of the International Institutions operating in the region of the City that you have chosen?
First of all, I would like to congratulate the students who have shown good involvement during the different stages of the Activity, those who have asked for clarifications within the activity section and the participants of the Academic forum who have shared their knowledge and collaborated with other mates after all the research. The exchange of opinions has been beneficial for all.
We have received the answers from a high percent of our students although the have been some students that due to different circumstances have submitted their answer with delay and have been admitted by the Academic Team as exception!
What we have expected for an outstanding answer and what we think that could have been improved:
* The fact of accessing early to the unit content and activity orientation has allowed some students to choose the city they wanted to work with in the first place, it has have been a good way to put them in the mindset for developing the task successfully.
– Some students have accessed in delay and have to work with cities we have assigned at random having less interest in the information they should have researched about.
* The best answers, shows that some of you have followed the activity orientation and the IESE report as a base, but did not constrain your research just to the sources used by the report writers. So we have valued as positive the student who managed to find reliable data from official institutions or local webpages from their respective cities’ administrations.
– Some students’ answers show evidence of poor research and analysis; this resulted in reports without accurate identification of the better and lower performance of the cities in some indicators.
* In any report it is important to make a clear identification of the sources consulted.
– The lack of references and the omission of a correct citation model, has limited some students analysis in some works.
* If you have started by identifying correctly the performance of your city according to the indicators we have listed from the different dimensions and present all the required data in a table, you would have a good base for the rest of the activity.
– Broaden summary based of fragments but with not coherent link to specific dimensions or indicators have not helped.
* If after the preliminary research you have been able to determine the strengths, weaknesses opportunities and threats of the city by means of a SWOT analysis in a reasoned way (having the % of the indicators into account).
– Providing a not reasoned SWOT that was too sketchy or that was of linked to the previous stage also limited the analysis.
* If you were able to identify whether your chosen city has active policies and concrete actions or not related to the dimensions from the provided chart and used the indicators and its units of measurement so as to finally make a diagnosis: Where is that your city need more actions for improvement? How would you think that the weakness could be turn into strengths and so on?
This Feedback is intended to summarize the pros and cons from your analysis in a general sense. But you will have your qualitative result at the personalized feedback that you will find attached to your answer in the activity page or just clicking on the Tutor’s alert and looking for the corresponding notification.
I know you have put a lot of time and effort in the activity development, so I hope you can take advantage of the experience. For me it has been a pleasure to reading your workouts.
Master in Decision Making & Innovation
It is time to announce that the assessment process of Financial unit has already finished and you have a feedback available in the Community. We would like to share with you some final comments about your performance during this activity.
The main goal of Finance unit activity was that you were able to put in the investor’s shoes investing in a real stock market. In order to get that goal, you were proposed to face a new challenge and participate in ROBOTvsGAIA 5, where you represented the GAIA Community in a competition against the Robot through the Stock Exchange Simulator.
What we should have learned:
1. That the profile conditions are based on how I have to distribute my investment among the different asset classes. A conservative investor should have the greatest weight in public debt and fixed income; and that an aggressive investor should have the greatest weight in equities.
2. That the asset allocation and the geographic distribution is the most important part for the creation of a portfolio. It implies much more than the Stock Picking. How much you destine to RF or RV and in which countries you invest is what will determine your profitability in the long term.
3. Investing in Indexes is much more reliable than investing in stocks directly. The Robot has invested in indexes and had an implicit commission playing against him Vs. the Gaians. Even so, he has won the Gaians in most of cases. The reason is that the Robot only invests in indexes, and the probability of making mistakes is much less than trading or direct Stock Picking.
4. Diversification is the key. Put the eggs in the same basket is not a good strategy if we want to obtain some benefits. It was important to have a diversified portfolio according to our investor profile in order develop this activity in a more profitable way.
Main mistakes made for some of the participants:
1. Some of you did not create a profile in the right competition (ROBOTvsGAIA5) or started too late; obviously, much of the evaluation depended on registering on time and start operating from the beginning doing the three required movements per week. All students who have signed up late or have not done so, had very difficult to overcome the activity.
2. Not to identify the risk profile: Those of you who had operated but had not identified their investment profile, could not be evaluated in two sections: neither by volatility nor in comparison to the Robot. Identifying the risk profile should always be the first step you take before you think about investing.
3. Try to invest in an arbitrary way: Some of you decided to buy or sell in an arbitrary way without doing some research about the companies. In order to do that research, you just needed to use the Stock Exchange platform or just surf the Internet.
4. Invest more than what was due to the profile: some students have had a very high volatility for the profile they have. Even some, who have achieved very positive results, have risked much more than their profile advised them to risk. Even having won, it is a mistake, because if the portfolio has been able to earn 10% in less than 1 month being moderate, for example (120% per year) means that it has risked a lot of equity capital. If it had gone wrong, 10% would have been lost, and a moderate is never willing to risk so much.
5. To have tried to invest in shares directly without having a correct analysis, except for those investors with the capacity to carry out a technical or fundamental analysis of a company, you should not invest in shares directly. You should invest in ETF’s or Funds that replicate indexes. Selecting a specific company is a decision that must be made based on a previous study of the course and the situation of that company.
If you want to know more details about your personalized investing performance, please take a look at the feedback and the document attached to the Community!
Master in Decision Making & Innovation
Now that the assessment process of Financial Information unit has finished and you have your personalized feedback in the Community, it is time to provide you with a general and final feedback that highlights some common mistakes that our expert Egoitz Urrutia has found in your activities and the solution for the three cases: Luko, Harris and Zeltris.
First of all, we would like to congratulate those students who decided to participate in this activity and deliver it on time! You did it!! We all know that you did a huge effort in order to complete this activity and we have taken this aspect into account during the assessment process.
In addition, we are also very happy with the level of participation in the two Webinars that took place during this activity. We hope you could take advantage of them and learn as much as possible.
According to the expert of this unit, Egoitz Urrutia, these have been the most common mistakes:
FIRST CASE STUDY – LUKO
- In order to calculate the FCFs you need to use EBIT (before interests)
- You should have calculated taxes on EBIT
- FREE CASH FLOW Formula: EBIT – Taxes + Amortization – Capex– WC
- Discounting Free Cash Flows: You needed to discount each year and on year 5 discount the Residual Value and the FCF of year 5.
- Enterprise Value: Sum of all discounted FCF and the discounted Residual Value as well.
- WACC= Equity %* Ke + Debt% * Kd *(1-t)
SECOND CASE STUDY – HARRIS
- Price Earnings Ratio (PER): Price / Earnings Per Share
EPS: Earnings/N Shares
2. Price/Cash Flow Ratio: P/CF CF: Earnings + Amortization
3. Ke: Ke= RF+ (RM-RF)*Be or Ke= RF+ Market Premium *Be
Market premium and market rate are not the same thing.
Market premium= RM-RF.
THIRD CASE STUDY – ZELTRIS
- Working Capital: Here we have into account the variation. Current Assets – Current Liabilities
Assets: Cash, Stock, Clients. They are all assets. To have an increase means to have less Cash Flow.
Liabilities: Suppliers. We owe the suppliers more money therefore we have more cash.
2. Pay-out is to be delivered to shareholders from the Profit After Taxes.
Therefore, 45% is a dividend payment and 55% goes to reserves.
Dividend/ N Shares
Moreover, the expert has also prepared the solution for the three cases of this activity in case you would like to take a look and compare them with your answers! Click on the link!
Finally, we would recommend that you take a look at the personalized feedback that you will find in the Community just clicking on the Tutor’s alert and looking for the corresponding notification or going to Financial Information>Activity>page 4 and looking for your name.