Part 8 (1/2)

Why not? No raphical representation is, you can't afford to risk a ned the ht question You cannot allow the viewer of the metric to misinterpret the story that you've worked so hard to tell

The narrative is your chance to ensure the viewer sees what you see, the way you see it They will hopefully hear what you are trying to tell theular basis, but the narrative requires frequent documentation Since the narrative explains what the e to es The narration which accompanies the picture and documents what the metric ure 3-6 shohen the narration is docuure 3-6 Narrative

Docu the Metric Development Plan More Than a Plan

In the end, the metric development plan should document the why (purpose statement), what (metric), when (schedule), who (customers), and how (analysis, hoill and hoon't be used)

Docu all of the details into one place This will help you in the following three ways: It will help you think out the metric in a comprehensive manner

It will help you if you need to improve your processes

It will help you if you need to replicate the steps

Figure 3-7 shows the the ure 3-7 The Developth or specific format, I want to stress the readability of the final plan You ant it for reference and at tireements made I find it extremely useful when the metrics are reported infrequently The more infrequently the et the steps I followed The collection can be very co the data can be complex, and the analysis can require even more detailed steps The more complex and the more infrequent the process, the more likely I'll need the plan documented

Of course, even if I perfor to do is to document the plan so others can carry it out in hout the life of the n and creation of the reements made around theactions (it becomes a contract between the metric analyst and the data providers and the end custo expectations Finally it is also critical to long-term success It provides a historical vieell as a ”how to” guide Without repeatability you can't improve

Without repeatability, you can't improve

The components of the development plan need to be documented in aaccuracy isit easy to access We discussed differentdata and ways to ood news is that many times, the e make it more accurate also makes it easy to access Less human interaction moves us toward more confidence in the accuracy of the data, and automation makes it easier to collect

When you document the components, don't be afraid to be verbose This isn't a time for brevity We need to build confidence in the metric and the components We need to document as much information around each co: Accuracy of the raw data You will be challenged on this, and rightfully so People have their own expectations of what the answer to your root question should be They will also have expectations regarding what the data should say about that question Regardless of the answer, so and check your data Thus, you have to be accurate when you share the data This requires that you perform quality checks of the data It doesn't matter if the errors are due to your sources, your forlitch If your data is proven to be wrong, your metrics won't be trusted or used Most examples of inaccurate raw data can be found as a result of human error but even automated tools are prone to errors, particularly in the interpretation of the data Errors can be found in anything fro data incorrectly, ories to inforories are not defined properly, an autoht be reporting the wrong data If you are tracking time to resolve trouble calls, is the time equal to the time between the start and stop dates? Or is it the time from the call to the resolution (which may occur well before the day/ti calendar days to track ti on availability, what is considered an outage? How do you deter? The simple rule of thumb is to double (and triple) check your data I find the best way to check my data is to have someone else look at it I'm too close to the work to see the errors others see i more important than accuracy of your raw data

Accuracy of your analysis We'll get into methods of analysis later, but for now, it is important for you to document the processes and steps you take to analyze the data This will enable you to repeat the process-a necessity for consistency A sirarams because they are easy, user-friendly, and powerful I use for froe over time Whateverover your work should be able to replicate your work by hand (using pen, paper, and a calculator) This documentation is tedious but necessary Your process must be repeatable Your process must produce zero defects in the data, analysis, and results Your process and the resulting information must be error free

Repeatability of your process Yes, I already mentioned this in the accuracy of your analysis But I it is worth e that repeatability is critical not only for the analysis, but throughout the process to design the metric The collection of the data must be repeatable-in a strict sense The analysis of the data raphical representation must also be a repeatable step in the process Each time, you should collect, analyze, and report the data in the same way If you don't document the process and ensure it is repeatable, you will lose the all-important trust of your audience This repeatability is necessary throughout the process It's e develop schedules We want to do it the sa the same tools Consistency is critical

Without repeatability you don't really have a process

To adhere to the tenants of good docu versions of your data, analysis, and reports You'll need to store your information with backups All of the docu You have to ensure the accuracy of the components and you can't do this if you don't control access to the information

First, you'll have to ensure the sources of your data are producing accurate information When you have checked the data for quality and have attained a high level of confidence in the accuracy, you'll have to repeat the processes you used to gather that information Once you have accurate data, you have to ensure it stays that way

People are the greatest risk to having accurate data

You will need a safe and secure location to store your data, your analysis, and your reports You will need to safeguard it from others who may innocently tamper with it You will also need to keep it safe fro well past your bedti data? When was the last tiot to save regularly?

You will ate this reality as ate the inevitable mistakes you will undoubtedly make? Save early, save often, and save your work in more than one place It won't hurt to have a hard copy of your work as a final safeguard Along with backing up your data, it's important to have the processes docu mistakes is to use variables in all of your for software to perform equations, avoid any raw data in the formulas Put any values that you will reuse in a separate location (worksheet, table, or file) Not only does it allow you to avoidthe formulas easier

Reference all values and keep raw data out of the equation

The following are a few other pointers to help you as you document your plan: Don't hen tired Seriously You should know yourself well enough to knohen you're tired Put the work down and cos you can do when tired-metrics is not one of them

Stick to your process Don't allow short deadlines to force you to deviate froet the h to meet an unexpected deadline Resist this Resist the person requesting the data before the agreed-upon schedule Whenever you deviate fro mistakes Start with ”no” Refuse to rush

Use version control It doesn't have to be extensive-just effective As long as you can track the work you've done and any changes you've es you've made and return to an earlier version you have faith in

Create and use templates whenever possible Templates allow you to make your process more repeatable and to ensure you collect the same data, the same way I use templates for surveys, interviews, and questionnaires I use theraphs and charts One caution-double-check the tereat! Why re-create the wheel? Just double-check that the wheel isn't riddled with broken spokes

A Note on Process Byproducts

When you worked on the root question, you identified byproducts like goals, objectives, tasks, and measures of success, which were not essential to the n As you worked on the abstract picture of your hts came to mind When you captured possible measures you'd need to fill out the picture, you identified more than as required The excess items you parked or stored in a to-do list All of these byproducts have potential to help you ianization and could be very valuable They should be captured and shared Don't waste the! Your intellectual property is valuable-treat it with respect

Recap

I have introduced a taxonomy so that we can communicate clearly around the subject of metrics In the second chapter, I covered the theory and concept of designing a , and reporting the data,up that metric In this chapter, I covered the basics of how and where to begin I have purposefully kept the inforh level so that you can feel co into the weeds In this chapter we covered: A metric development plan is not a luxury It's a necessity

The plan not only helps in the creation of the uidance for the maintenance and final disposition

Thecomponents: A purpose statement An explanation of hoill be used An explanation of hoon't be used A list of the customers of the metrics Schedules analysis Visuals or ”a picture for the rest of us”

A narrative Accuracy is critical I stressed the importance of accuracy in your data (source dependent), your collection (process dependent) and your analysis (process and tool dependent) I also offered the benefits ofyour processes repeatable

Conclusion