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Be honest - collect, use and present your data accurately

Honesty is the hallmark of M&E data representation. Conflict of interest when not disclosed in time put a doubt on the entire data collection and analysis process. M&E personnel should indicate any personal interest at the beginning of their findings. M&E data has to be presented clearly and accurately as possible.

If the honesty information is been provided, it will allow for accurate data analysis of the information. it will also give the organisation room to work out on the mistakes that where made and avoid them in future.

Honest in M&E is not just telling the truth and not laying, but in M&E, there are other dimensions to be evaluated such as: ensuring the data is accuracy before presenting it and it should be presented accurately

Honestly report data as it is from the start.
The results must be honest no what what the outcome is.
The methods and procedures must be honest that collected the data.
It is not good to falsify or distort data.
When dealing with data avoid careless and negligent mistakes carefully and critically check your data that it corresponds.

Honesty is very key in collecting, managing, analysing and presenting your data, findings should be nothing but the truth.

Honesty as much as we try to practice it in our daily lives,it is a most do thing in M& E because the data from M&E is the bedrock of any project which determines the success and failure of the project. In as much as we know that perfection of data is almost nearly impossible atimes either at collection time or presentation time,these are errors that can be worked on to the barest minimum so we can have an honest guideline.

i want know more

Honesty deals with the dignity, wellbeing and safety of an individual. This aspect ensures that individuals do not intentionally or unintentionally cause damage be it physical, emotional or whatever it is in the workplace

Honesty in data collection and usage is a very important aspect because it gives the correct situation on the ground and it gives credibility to the data. Otherwise if any hint of dishonesty in the presentation of the data, that data will not be credible.

Indeed this ethical consideration needs to be reflected in all data presentation and donors need to be aware of the conflicts of interest within projects when presenting the data and should be at donors dispose to make decision based on all the facts that shall be presented.

M AND E REALLY NEEDS PEOPLE TO BE TRUST WORTHY. CAPTURING DATA THAT IS WRONG JUST BECAUSE YOU WANT EVERYTHING TO BE PERFECT IS NO LONGER PART OF M AND E NOW THE DATA IS NO LONGER ACCURATE AND DOESNT INTERPRET WHAT IS SAPOSE TO.

THATS WHY IT IS VERY IMPORTANT TO ENSURE THAT TRUETH IS BEING TOLD. AS M AND E WE NEED TO ENSURE THAT DATA IS PRESENTED ACCURATE, AND IT REPRESENT WHAT IT SHOULD.

How can one detach personal interests from professionalism?

It is a great aspect that as Monitoring and Evaluation professionals we need to be aware of.

Honesty is very key in collecting, managing, analysing and presenting your data, findings should be nothing but the truth.
As a data analyst the place of ethical principles with stakeholder, beneficiaries proje t team, donors et shouldntvbe over emphasis

Attitude towards your team can also improve honesty. I do hear some workers complaining about the pressure being put on them to carry out some kind of duties and if the target is not reached, they get sacked from the work.

For me, you have to be honest with the use of data if you want it to reflect reality

'Honesty is the best policy'

The only way to people's hearts is being honest and completely transparent and making sure there is no conflict of interest.

Sharing limitations and the risks involved regarding a project should be clear and informed to the people so they know what they are getting into. This way they would be comfortable participating and sharing information.

Honesty is very key in M&E processes especially data presentation. how accurately you present your data with honesty is important.

Honesty is very key in M&E processes especially data presentation. how accurately you present your data with honesty is important.

Honesty is very key in M&E processes especially data presentation. how accurately you present your data with honesty is important.

The data must be scrupulous with regards to telling the truth.
It must be upright, not frauded, unbiased, accurate, authentic, open, plain, etc

The data must be scrupulous with regards to telling the truth.
It must be upright, not frauded, unbiased, accurate, authentic, open, plain, etc

The data must be scrupulous with regards to telling the truth.
It must be upright, not frauded, unbiased, accurate, authentic, open, plain, etc

The data must be scrupulous with regards to telling the truth.
It must be upright, not frauded, unbiased, accurate, authentic, open, plain, etc

The data must be scrupulous with regards to telling the truth.
It must be upright, not frauded, unbiased, accurate, authentic, open, plain, etc

Been truthful
Honest
Pure
Clean

Speaking or doing the truth or right thing
Not fraud/ not act of fraudulent
True, no lying
Accurate
Authentic
Open/frank

Speaking or doing the truth or right thing
Not fraud/ not act of fraudulent
True, no lying
Accurate
Authentic
Open/frank

Everytime one publishes a paper about a company, self interest should be restricted. It is about the community for which the survey was conducted.

Everyone in all we do as far as data and information is concerned, we must be honest.

Many organizations have seen their funding canceled by the donor due to non-compliance with reality and the data collected. Some humanitarian organizations play their credibility in their collaboration with local partners who are not always trained in the principles of monitoring and evaluation.

Sometimes what causes dishonesty is lack of sufficient knowledge in the subject matter fe example it willl be difficult to report on clinical trails without knowdge in how to conduct clinical trails

Honesty is Key in data presentation and findings.

Honesty is a component of moral character that connotes positive and virtuous attributes, such as integrity, truthfulness, and openness — including clarity of conduct, along with the absence of lying, cheating, theft, etc. Honesty also involves being reliable, trustworthy, loyal, fair, and sincere

Collect, use and present your data accurately. Be clear about how your M&E processes work and be honest about any limitations to your work.
should not present data that you know is inaccurate. However, it also means that you will need to constantly check the accuracy of your data. In Module 3, you will learn about data quality assessments, one technique for ensuring that your data is accurate.
Be honest about these limitations with donors, beneficiaries or anyone else who might be interested in your work. Ideally, share these limitations before your project starts, so that people do not develop unrealistic expectations.

honest provides the true picture of the data at hand without any selfish interest. this should be done in such a way that whether there is a benefit or not, when it comes to information delivery; it should not be controlled by what should be gained if one answered in a certain way. it should be known that any unhonest information can bring damage to the image the person and the company or organisation

How can they ,donor side, know/measure the presented data has honesty?

Am enjoying what am learning so far

Interesting,
Simply not lying is not enough. True. Accuracy in data collection, conclusion, sharing of limitations and conflict of interest in your presentation. I just hoped I could get more...

We need to make sure that the data we present is accurate and be honest about the limitations of the M& E strategies.

It is very hard to maintain the values you have while analyzing data. However, honestly makes the data reliable. hence we should focus on what is valid and reliable as we want smooth and authentic output.

The most important thing always to put at the back of your mind when gathering data in HONESTY, because that will be the basis in which people will accept your research or the analysis of your data.

The most important thing always to put at the back of your mind when gathering data in HONESTY, because that will be the basis in which people will accept your research or the analysis of your data.

Absolutely, true.

honest is a principle for the data, which it's important to led the monitoring and evaluation be in the correct and truth process

Quite insightful, its quite interesting to note that "honesty"as a principle is quite broad in scope

M&E means measuring the truth about what we are trying to learn about. Therefore, we need to make sure to collect the data accurately and in order to come close to accuracy we need to constantly check it, after collecting the data we need to represent it accurately as well, we should be clear about the findings and not too strongly word it if we are not 100 % of the results. If, for whatever reasons, we had limitations on data gathering, we need to share it with the donors, stakeholders etc. Conflict of interest should be out of our M&E process.

Honesty is an important ethical principle that cannot be overemphasized time and again..

Honest as another ethical principle for Monitoring and Evaluation professionals as it ensure that the data collected is honestly and transparently collected, managed, analyzed and presented.

HONESTY-THE DATA YOU COLLECT SHOULD BE A REFLECTION OF WHAT IS HAPPENING ON THE GROUND.ACCURATE DATA WILL HELP MAKE INFORMED DECISIONS

In summary, the principle of honesty requires us to ensure that

• the data we present is accurate
• the findings of our M&E are accurately represented
• the limitations of our M&E strategy are known;
• And that any conflicts of interest regarding the project are publicly known.

Honesty in all sectors of professionalism is important. IN order to present accurate data, honesty has to be applied.
Being explicit with information is also a good thing.

It is obvious that often times you are honest i your every day life either at home, work or community which is moral, however, the standard of that is even higher for M&E professionals than it is for other people this is because data from M&E processes are expected to be as close as possible to truth. ways to ensure that your is abiding to the honesty principle includes:
Ensure the date you present is accurate
Ensure that findings from your M&E are accurately presented
Share the limitations of your M&E strategies
Share any areas your or organization may have conflict of interest

Honesty is indeed one of the ethical principles that must be truly applied in all the M&E processes. this makes decisions to be made using the data to be real and honest decisions as well.

Honesty is very key as a M&L professional. This is enhanced through ensuring that the data you present is accurate, ensuring that findings from your M&E are accurately represented, share the limitations of your M&E strategies, share any areas where you might have a personal or professional interest in a certain outcome.

Conflict of interest is a regular bias that can be encountered in data presentation and analysis. Most of time organization are motivated by political benefits

Any donation for data collection, analysis or presentation should be recorded in the organizations data base.
Should be used in the organization development and all members should be taken into concedration

Honesty: When we collect the data, we must honest to communities.

Honesty is one key aspect in data that must be observed. This is because of the purple of data, which is mainly for informing decision making.

conflict of interest truly should be shared because some people go into a project to get certain results which may not be in tandem with whats obtainable thereby making them alter data and data looses credibility.

Honesty is the best way to go in M&E, ensuring the audience your data is being presented to, have a holistic context with which to interpret the data.

I have observed that many organisations represent wrong information/findings in the sense that it's they are generised. This is usually committed as a way to entice donors or stakeholders. With this all the stakeholders need to be alert and establish checks that would satisfy whether the title ry present whats on the ground

Honesty in data collection and presentation is very important. I look at a situation where my organization working to get the rural folk to earn more from their dairy ventures actually provide me with information that informs a gap in the market. This is one that i can benefit from hugely but again ethically wrong not to disclose this. There is a lot that still needs to be done to handle this successfully

Honesty uprightness · honorableness · honor · integrity · morals · morality · ethics · principle · (high) principles · nobility · righteousness · rectitude · right-mindedness · upstandingness · virtue · goodness · probity · worthiness · high-mindedness · justness · fairness · incorruptibility · truthfulness · truth · veracity · trustworthiness · reliability · conscientiousness · scrupulousness · reputability · dependability · loyalty · faithfulness · fidelity · sincerity · candor · frankness · directness · forthrightness · openness · straightforwardness · plainness · genuineness · bluntness.

honesty means that clear and real picture should be presented. Transparency should be adhere. and risk need to be identify at early stage and more plans need to be developed to respond to the early alarming situations.

This is very important aspect in M&E (Honesty) the indicators we are choosing should be Honesty and presented well

The key take away if the need to ensure that what is told to participants as the purpose, data required and intended use be truthful to avoid issues around incorrect information due to dishonesty.

Honestly can not be over-emphasized. This is one of the first things I learned about research.

Honesty should be the important aspects during the presenting the data of organization

Truth wins the world. In M&E data tools and processes must accurate to ensure quality data collection.

The need for Honesty in data analysis can not be overemphasized. It has become pertinent to ensure that data reported is done with utmost honesty this is because a dishonest data will lead to an inaccurate evaluation that could affect the very people interventions are intended to help.

Every researcher should thrive to collect and present accurate data regardless of their own personal hindrances. They opt to know that a very wide society depends on their research and findings foe education, good management and governance and even health researches.

For me, honesty in data is a major thing to consider. because it show and defines the integrity of your data and results at the end of the day. The data will not be misleading and the out come can be reliable anywhere.
Honesty pay always in the end.

Hi.everyone.good course

Data collection to data use .importants to archaving

Honesty is a phenomenon that entails dessimination of accurate and validated data with no conflict of interest.

Honesty will give accurate data and will bring determined change in the results

The ethical principle of honesty is very crucial in data collection, management,analysis, use and presentation. M&E personnel should as a matter of responsibility ensure complete compliance to all aspect honesty principles.

My take home from "Honesty" is that honesty for M & E Professionals is not optional

Integrity is key in data, ensure accurate data is collected and presented. Identity your limitations.

This is true.

Sharing the honesty part of what the data will be used and ensuring the data quality, helps create a balance and give a clear indication in the communities or among participants how the information shared or collected can be of importance to there communities or lives.

Honesty is simply collecting, using and presenting your data accurately hence, requires one to be open and clear about how his/her monitoring and evaluation processes work and further provide some of the limitations to his or her M&E work.
However, the standard of honesty is higher for M&E professionals than it is for other people. Honesty is all that matters in obtaining the best and good quality i their work.
Data accuracy basically rely on the honesty virtue and if dishonesty is encouraged they will be obtain wrong information leading to poor quality work.

Any organization that becomes lifted up due to honesty as a principle of ethical behaviour is resulted when data is collected,manipulated and analyzed before presentation to the donors and even to the individuals.The information from the organization must be clearly reliable and efficient for a smooth use when placed for a reason,

It means that the researcher or the person evaluating the samples
Should have some responsibility for the data collected and not comply with the organization's directives
If it causes problems for society?

Of course, accuracy is required in collecting data, and this is a trust on the researcher and on organizations

But I think that state-funded research seeks to polish the image of governments, especially in the countries of the Middle East

Honesty principle in M&E is crucial and should be seriously considered

Absolutely

Good observation

I have seen in the past an organization working on the HIV project that falsified its data and this caused the project to stop for this NGO because the donor no longer has confidence and its data is no longer reliable or credible.

As an old adage states-- "Honesty is the best policy."
This reflects that an honest team is a successful team because it tries its best to work for excellence by recognizing its flaws and improving its functionalities for the benefit of the society.

Being honest is being true to oneself.

What if the honesty would mean harm to the reputation of leaders, who are could be responsible for what the organisation advocates against?

Honest is positive character which makes you trusted to the people and accept the result of the data you collect

Data collected should not cause any harm to people who were directly involved or participated in the collection of data, this includes the stakeholders. This means, as M&E we should consider the experience of the people we are collected data from. This module emphasized that, we should honor the dignity, well being and self worth of the individuals. Therefore, in this scenario the data released cannot be used by the politicians because it will harm the people who participated in gathering the data. This data will not serve the purpose, because the politicians will view it based on the history of the participants. So, in this case the data is suppose to be kept anonymous and confidential, to protect the participants dignity, and their wellbeing.

It is evident that honesty is a key, therefore, we need to be transparent on the data is collected, and limitations should be discussed upfront. This includes consent of the people participating, to ensure confidentiality. This means, we should discuss the processes to be used to collect data, the manner in which the data will be analyzed and managed and presented.

i think its very interesting

i think its very interesting

Of course transparency and honesty is important to any study, but it is valuable to stress its importance in M&E. The advice of sharing the limitation of your M&E strategies was helpful because I feel as if most people would not share their limitations; it may downplay the work they had did. But in fact it can strengthen your work because it shows the truth. The truth being that data collection won't be perfect so erasing that expectation can allow for people to get more in-depth data analysis.