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  • No data, less chance to make the right decision.

  • It is important for Dora to look at the organization's goal and tools then compare the programs' effectiveness and cost then make recommendation and schedule action.
    The questions she should ask are, which program is more effective towards the organization's goal? which program is lesd effective towards the organization's goal?which program is more costly towards the organization's goal?which program is less effective towards the organization's goal?

    J
    1 Reply
  • Data-driven decision making is the use of facts, metrics, and data to guide strategic business decisions aligned with your goals and initiatives.
    Having these essentials in place supports data-driven decision making at all levels. As a result, business groups will develop a habit of questioning and exploring information to uncover powerful insights that prompt action.

  • To make decision with Data, follow the steps below:

    1. Start with findings. Findings are facts that you pull from the data.
    2. Draw conclusions. Interpret the findings.
    3. Make recommendations. Based on your conclusions, what should your organization do?
    4. Schedule actions.
    J
    1 Reply
  • That's such a great summary.

  • When closing down a program, the steps to follow include; gathering findings, making conclusions, making recommendations and finally, taking action...

  • This is the reason M&E is very sensitive. It may not be in favor of one's opinion, as difficult decisions may need to be made in certain cases...

  • Absolutely, especially honesty as an ethic in M&E...

  • An externla evaluator may also help in making an unbiased decision...

  • Some examples of biases include; conformation bias (making decisions because they confirm what we already believe), the bandwagon effect (making decisions based on popular opinion), and the in-group effect (making decisions based on opinions of people who belong to the same group like us)...

  • All biases must be avoided as one is making a decision...

  • you can make decision with data by following this steps
    starting with finding
    drawing conclusions
    making recommendation
    scheduling actions on how the project will be shut down proceduly

  • To make decisions with data requires carefully observation and good understanding about how data are interpreted. Like the case of Dora, she has to look at same categories of data coming from different sources (activities/programs). This gives her a clear understanding about which program contributes most to the project goal.

  • To make decisions with data you must of all identify what has happened and what you want to change. Firstly, before getting to the database, define which information you want your database manager or M&E team pullout for your perusal. With this you spend less time to get what you want in order to make the right decision. Next, don't compromise what the data interprets, it might be frustrating and disappointing at times because we most times pre-plan before getting to the data. Let your personal opinion be put out this, respect what the data says. If others stakeholders are finding it difficult to accept take with you to review the data sa well.

  • Making decision with data. We need to interpret data, draw conclusion then decide what to do according to the goal or target of your project.

  • Making decision with data need to start with findings, Conclusion then Decision,

  • It is quite unfortunate that Dora had to eventually shut down the mentorship program. However, this was a necessary action because the findings informed this decision.

  • To make decisions with data, the different data should be analyzed using agreed criteria. The criteria could be cost, efficiency, impact, ease, adaptability, etc. Decisions will then be made based on the chosen criteria

  • To make decisions with data, the different data should be analyzed using agreed criteria. The criteria could be cost, efficiency, impact, ease, adaptability, etc. Decisions will then be made based on the chosen criteria

  • Data driven decision making helps in making clear, focused and impactful actions for programs

  • Interesting how data makes decision making straight forward albeit difficult.

  • To make decision will depend on your goal, organization and tool. there are some step to guided 1. start with findings, 2. draw conclusions 3. make recommendation and schedule action.

    M
    1 Reply
  • To decision with data con be made through the following; you start by finding the data and understand the data thereafter you draw conclusions base on the available data source, make recommendation that will guide schedule action at the end of the decision making analysis

  • Steps when making decision with data:

    1. Gather findings - these are facts pulled from your data
    2. Draw conclusions from this data. This coming up with an interpretation on the meaning of the findings. If you do not have enough information to draw a strong conclusion, go back and check if its possible to gather more information from other sources.
    3. Make recommendations based on your conclusions to figure out what should be done. This is where the decision is actually made.
    4. Implement that decision by proposing actions and schedule actions.
  • Decision should be made if the program has more challenges and the o ly way to stop that is following the steps of data Decision making

  • Look at the cost,rating and the effectiveness. If the highest effective has the highest cost then the project has to be closed and vice versa.

  • Making decision with data goes from the findings the team has to recommendations that will be put in action. We compare statistics about what we are going to work on in order to see the most reliable reality in the field.

  • 1.Start with findings- the findings are facts that are pulled from data

    1. Draw Conclusion- Interpreting the findings, this might require analysis skills
    2. Make recommendations- looking at conclusions what should the organization do. This is where the decision is actually made
    3. Schedule actions- After making a recommendation, implement that decision by proposing actions
  • Data is key for decision making. The right information put you or your organization in the right position to be able to make right decision. You have to thoroughly look at or analyze the data gathered from your finds, draw conclusion, make recommendations and them implement those recommendation of the effectiveness of the project or organization.

  • On scheduling actions, can you involve other stakeholders such as beneficiaries?

  • The decision Dora made after data analysis is now more reliable and Dora can back it up with facts

  • Dora took the right decision to get her program manager work with her in achieving the analysis of her three program.
    Literally, I would have advised that the two programs: Writing skills and the class on technology be kept, and the number of beneficiaries on the programs reduced. But analyzing the data as done in the example above shows that data driven decisions are better than using our intuitions.

  • The process of making decision depend on goal organization and tool. also steps which my involve in decision making are start with finding which are fact that pull from data also there is draw conclusion where here we interpreted our findings also there is make recommendation based on the conclusion which we have drawn. Lastly is schedule action.

  • The process of making decision depend on goal organization and tool. also steps which my involve in decision making are start with finding which are fact that pull from data also there is draw conclusion where here we interpreted our findings also there is make recommendation based on the conclusion which we have drawn. Lastly is schedule action.

  • Make findings, conclusion and recommendations.

  • Amazing we learn a lot about data drive decision making which the best method rather than simply decide in our belief which can cause biases. On the other hand making data driven decision needs to follow some process or steps which very important to make appropriate decision.

  • When making decisions with data one needs to look across the programmes in question. Then look at the cost of implementation of each programme. Then check how effective is the impact made by each programme. Then draw conclusions and make critical recommendations and the plan for actions. These steps must be taken without any bias action.

  • In situation where things don't move on like business one may make a final decision to shut it down like the one of Dora

  • data helps our decision making to be void of biases and sentiments. Helps in proper decision making that leads to the overall good of the project or organization.

  • This is a very good approach. Data driven decisions are always the best. Dora at first did think of shutting down the mentorship program due to confirmation bias but she found out that it is the least effective and most expensive.

  • This is a very good approach. Data driven decisions are always the best. Dora at first did think of shutting down the mentorship program due to confirmation bias but she found out that it is the least effective and most expensive.

  • This is a very good approach. Data driven decisions are always the best. Dora at first did think of shutting down the mentorship program due to confirmation bias but she found out that it is the least effective and most expensive.

  • This is a very good approach. Data driven decisions are always the best. Dora at first did think of shutting down the mentorship program due to confirmation bias but she found out that it is the least effective and most expensive.

  • This is a very good approach. Data driven decisions are always the best. Dora at first did think of shutting down the mentorship program due to confirmation bias but she found out that it is the least effective and most expensive.

  • This is a very good approach. Data driven decisions are always the best. Dora at first did think of shutting down the mentorship program due to confirmation bias. But in reality according to data, the mentorship program is the least effective and most costly one.

  • for our case it is better to make a decision based on your data as you can be biased , for this scenario , technological skills and writing skills was more contributing to finding jobs after 6 months

  • The steps discussed here seems fruitful for Dora.

  • process on decision making depends on your gaols, organisation and tools.

  • Every decision that is predicted on valid and reliable data always, have proven to yield positive results.

  • Look at the data and analysis it, provides these, finding, conclusion, recommendation and actions.

  • Me, I would say to take action on the decision-making on the data, one must first pass by a comparative analysis on the various programs. And then we will know the results, we will draw conclusions following the results that were drawn for the data, and then we will make recommendations, so what should we do, what program we are going to adopt and then we will plan actions on this recommendation.

  • Do not at all oblige to measure the most effective program to achieve the objective of the organization. Yes, but to achieve the objectives of the organization, it must go through these diagrams to see the objectives first, the most effective program and the least expensive programs to make decisions.

  • Exactly what made Dora,
    She first: to find results by each program and then she took conclusion by interpreting the results to go to the recommendation on the basis of conclusion and finally she had planned which program she had to adopt.

  • Performance based decisions are tough to make. Nonetheless, they have to be made especially in situations where resources are lean. This is where programmes that prove to be more effective are retained.

  • Someone new can only know how accurate your analysis are, by reviewing the available data used in making decisions.

  • Exactly my thoughts

  • In order to take decision driven from data, it is necessary to collect data or use the existing data that has already in the database, then analysis to get the finding. After having the finding, you can do conclusion based from the findings of your analysis. From the conclusion, you can draw several recommendations and finally take the decision based on the recommendations.

    D
    1 Reply
  • Just as I have learnt, I will want to use the cognitive approach this will make my colleagues and team mate appreciate my points and create a transparent and informed decision making in the project.

  • Decision making using data collected, organized and analyzed requires you to have a grasp in findings, conclusion, recommendations and actions

  • These are pretty good steps that Dora Took. In this way she won't make a biased decision on which program to keep or eliminate. Moreover, the action steps that followed are very precise and time-bound. Which is good, it gives the program enough time to collapse properly.

  • Finding
    Mentorship class is over hyped. The result compared to the cost of the class per year is not commensurate.

    Draw Conclusions
    In as much as mentorship is a great class, the cost of mentorship should be reduced because the result in the space of 6months is low compared to other classes.

    Make Recommendations
    I recommend that the mentorship class should not be shut down because it is beneficial to a selected few even though the percentage is not on the high when compared with the other two classes.

    Schedule actions
    I request that Dora should not ask her project manager to propose a schedule and project closeout plan on mentorship class. Her action plan should be to increase the cost of technology class. This means if mentorship class is $25, writing class should be $35 while technology class should be $50.

    Thank you.

  • Do research, be able to interprete the research in other to help make conclusions, implement your findings, interpretation and conclusions

  • Looking at the findings, Dora draws a few conclusions. It’s clear that the mentorship program is liked by most participants. However, it is also more expensive and less effective than the other programs.

    So, while she would like to keep the mentorship program, she decides to make a difficult recommendation: the program should be slowly shut down over the next three months. She asks her program manager to create a plan for shutting down the mentorship program.
    Your process for making decisions will depend on your goals, organization and tools. However, broadly speaking, it should follow the steps that Dora just followed:

    Start with findings. Findings are facts that you pull from the data. One of Dora’s findings was that only 8% of mentorship program participants found new jobs after six months.
    Draw conclusions. Interpret the findings. For this step, you might rely on the analysis skills that you learned in the last module. One of Dora’s conclusions was that the mentorship program was less effective than other programs. You may find, at this step, that you do not actually have enough information to draw a strong conclusion. In this case, you should decide whether it is feasible to gather more information from other sources.
    Make recommendations. Based on your conclusions, what should your organization do? This is where the decision actually gets made. Dora made the difficult recommendation to shut down the mentorship program.
    Schedule actions. Once you have made a recommendation, implement that decision by proposing actions. Dora asked her program manager to propose a schedule and project closeout plan.

  • This topic is so important in data driven decision making

  • to make a decision with data we must follow these steps:

    1. reviewing the findings. in other words, gather your information if they are not enough we must look for other sources. then read and interpret the findings.
    2. make a decision based on the last step.
    3. make a recommendation based on your decisions.
    4. make a plan to implement your decision.
  • Data driven decision are the best. They are basically unbias much as the data has quality. Organization should not be making decisions subjectively, this might be unethical.

  • It is very crucial to make decisions using data because it helps to avoid biases and helps in making informed decisions.

  • Data is an available resource, which can also helps us with our internal decisions. When we need to decide on whether the programs are effective, if yes how and why - so we can use this data for further programs, if no then we can use this data in order to understand what did go wrong, learnt lessons and then how to fix them for the future programs. We can also make decisions to use them for our own programming decisions like which programs to continue with and which programs not to, just like in Dora's case. When we need to make a decision like Dora, we should stay away from our own intuitions because they can be biased, instead we should use data and look for findings that gives us the facts about the most and least impactful programs and their cost relation, after we interpret the findings then we can draw conclusions and act accordingly.

    M
    1 Reply
  • From what I have learned so far in this module if Dora has followed her intuition she would have closed the wrong program, because she didn't implement those steps.

    1. Start with findings.
    2. Draw conclusions
    3. Make recommendations
    4. Schedule actions
      Rather she was trying to use Confirmation bias.

    So using data to make decision is the best thing to do.

  • Absolutely true

  • In summary, once we have the data, the decision-making process will depend on our objectives, our tools and our organisation. This process will involve several steps: findings, conclusions or interpretation of results, recommendations and actions.

  • To make a decision it will depend on my goals, my organization and tools

  • simple and clear. The "Conclusion" is actually based on the analysis of the data. Make recommendations based on the conclusion and follow it up with appropriate actions.

  • I believe that this was the right decision to make by Dora and all decisions should be data driven in order to make the best decision in the end.

  • How to make decision with data collection is one of the important factor to considered before making conclusion as showed from the examples above, analysis justify data decision. what is the importance of the project and its impact to the beneficiaries and how importance the project to the stakeholders. you can also ask the opinion of the beneficiaries to rate which project is important to them why they so much like the project, the questionnaires should be in open ended format in different classification such as house to house survey, key informant interview and focal group discussion to cover different views.

  • data driven decisions help us to avoid the effects of our biases. the process of making data based decisions is as follows:

    1. Start with findings
    2. draw conclusions
    3. Make recommendations
    4. Implement your conclusions
  • Finding,Conclusion ,Recommendation and Action should the role in deciding the goals of the organization

  • it is data definition and analysis

  • Decisions should not be biased, biased decision will affect running of projects results from findings of a research on a decision will help to make sound decision as in Dora's case. What she was favouring is what was dropped.

  • It is evident that data must inform any impactful decision. From the case study, it is clear that without the data, it was easy to drop the most impactful and cost efficient program. Tus, data must be considerate for any meaningful conclusion.

  • Hi.everyone.helpe us How I to get this sistem

  • Start with findings, draw conclusion from findings, make recommendations and schedule actions

  • Draw conclusions depending on your findings and take appropriate actions based on your decision.

  • hello familly

  • Understanding your data is key to decision making

  • This module really do help in the drawing of the final conclusions. As it gives a detailed information on the approach in getting to make the final conclusions.

  • Findings, conclusions, recommendations and actions are steps to be used in having an appropriate decision made at any point of an organization. Any proposed ideas from data collected turn up to be of required number leading to conclusion before actions are set ready.

  • Having valid and reliable data will finally lead to very logic decision rather than biased intuition.

  • In the table presented about, I would prefer the technology skills program over the others for two reasons-- practicality and beneficiality.

  • Using data for decision making is not easy, however. Data-driven decision making requires an open mind. You cannot simply use the data to support what you already believe or to make your project look good

  • After looking at the results of the analyzes, it is difficult to close a program directly, so the idea of ​​gradual closure gives opportunities to review the results again and make a decision after several months

  • To make decisions with data
    First you need to look at the findings which are the facts that you pull out from the data.
    Second draw conclusion.
    You need to interpret the findings.
    Third making recommendations
    Based on your conclusion what should your organization do.
    This is where the decision is made.
    Fouth Action
    Once you made a recommendation, implement the decisions by proposing action plan.

  • Of course these 4 steps are very important to have a good decision making but we forgot also that the neutrality part on the judgment to be made and also being meticulous can improve also what really pushes us to decide according to the evidence in the data.

  • Making decisions based on data eliminate bias and personal inclination that might intrude on the decision making process

  • Making decision with data Is an important tools in decision making
    Mostly when the following step are taking
    Start with findings. Findings are facts that you pull from the data. One of Dora’s findings was that only 8% of mentorship program participants found new jobs after six months.
    Draw conclusions. Interpret the findings. For this step, you might rely on the analysis skills that you learned in the last module. One of Dora’s conclusions was that the mentorship program was less effective than other programs. You may find, at this step, that you do not actually have enough information to draw a strong conclusion. In this case, you should decide whether it is feasible to gather more information from other sources.
    Make recommendations. Based on your conclusions, what should your organization do? This is where the decision actually gets made. Dora made the difficult recommendation to shut down the mentorship program.
    Schedule actions. Once you have made a recommendation, implement that decision by proposing actions. Dora asked her program manager to propose a schedule and project closeout plan.

  • We can make good decisions with the data because this reflects what's on the ground.

  • Here, you need to follow the four steps in making decision with data that is start with findings, draw conclusion, make recommendation and scheduled action.

  • When you're about to make decision using data, there are few steps to follow.
    Start with finding.
    Use the finding to draw conclusion
    Recommend from the conclusion
    Then finally schedule an action.

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