Kpi Data Integrity Depends On 5 Rs
You depend on the quality of data and information to provide a stable foundation for your decision making. Decision making often involves responding to something,Hogan Scuro Uomo Interactive Scuro, so you need your data to validly describe what you are responding to so that you choose the right responses.
Whether your data is quantitative (based on numbers) or qualitative (based on perceptions),Nike Air Max 2011 Mesh Sort Lilla Sko, it's integrity depends on 5 widely recognised qualities.
Relevant
Make sure the data you have selected is directly appropriate to the purpose of the performance measure you selected it for. Be careful of data that seems interesting: it doesn't mean it is relevant. Trying to gather more data than you really need, especially in surveys,MBT Sini Schuhe, can negatively impact on the other dimensions of data integrity (below).
--> Be ruthless and collect only the data you have a use for in monitoring and diagnosing performance.
Reliable
Collect enough data and collect it carefully to ensure that it is precise enough (especially if it is an estimate based on a sample) and continues to be precise enough as you collect it over time. Would you rely on one day's rainfall to draw conclusions about annual rainfall? What about five days' rainfall? How many days rainfall would you need to get a precise enough estimate of annual rainfall? And what would this depend on?
--> Design your sample sizes to give the reliability you need. Don't guess.
Representative
It is important that the data you collect are observable events or characteristics that describe the full scope of what your performance measure is supposed to be measuring. This means that it is unbiased,Grigio Bianco Oro Hi-sprint Hogan Uomo Scarpe on sale, or accurate enough. The last thing you need is for your data to tell you only what the "squeaky wheels" have to say,MBT Kaya Schuhe, drowning out the valid and important and balancing views of the "well oiled wheels". Squeaky wheels,Wholesale Online Dame Nike Free Run 2 RoyalBlue Sort Hvid Sko, volunteer surveys and easiest-ones-to-measure are examples of data sources unlikely to give you accurate enough data.
--> Define your population carefully,Mens Nike Free Run 3, and select random samples to avoid bias.
Readable
Unless the data you collect is clearly defined, legibly presented,Christian Louboutin en satin Fifi 100mm et des chaussures en dentellevente au rabais, easy to organise for analysis,Nike Lunar Max Sort Grøn Sko, makes sense to its users and can be easily interpreted and understood by them, it won't matter how relevant, representative or reliable it is. It just won't be usable. The numbers need to be in a format you can use.
--> Design your data collection forms and questionnaires carefully to give you the data in the format your analysis needs.
Realistic
Trade off the degree to which your data is relevant,MBT Changa Schuhe, representative, reliable and readable with the level of resources you will need to invest to make it so. Make sure the value you get from using your data is greater than the effort you invested in getting it. Beware of the temptation to invest in sophisticated automatic data capture systems (such as bar-coding and voice recognition software) - if you haven't got a simple manual system working well first, then these systems are likely to cost you much, much more than the savings they appear to promise.
--> Pilot test your data collection processes to be sure they will deliver cost-effective data.
TAKING ACTION:
If you have a performance measure or KPI that triggers more debate about data quality than it does about performance levels, then use the 5 Rs of data integrity to work out where the data collection process can be improved. 相关的主题文章：
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