Before you implement TransparentChoice for project prioritization, it's a good idea to know what data you want to collect. Don't worry if you don't know everything as you can add more data fields - we call them attributes - later, but it really helps to have a clear picture before you begin... and this page is here to help you.
First things first.
Why define data? | Attributes vs Surveys | Fill in this template
Why define data up-front?
When you are prioritizing projects, you start with your strategic goals and turn them into weighted criteria. You then score all your projects against those criteria in order to create a total strategic alignment score. You can then use this score to select your portfolio of projects.
TransparentChoice gives you some great tools to help you select your portfolio, but they are all driven by data. If you don't collect the data, you can't present the analytics that will help your executive team select the best portfolio. Having a clear up-front picture of what will help the execs will help you collect all the relevant data.
In addition, TransparentChoice lets you automate bits of the data collection process through our Kanban. This means you can set up e-mails to automatically go out to request data from your subject matter experts. These e-mails will link to forms through which data is entered.
Setting up your data fields in advance need means you can then define the forms and the automated e-mails (we call then "notifications") to help streamline your process more quickly.
Why define data? | Attributes vs Surveys | Fill in this template
Criteria, Attributes and Surveys
To calculate your strategic score, you need to score each project against each criterion. There are two ways to do this, using attributes or surveys. These rules of thumb will help you decide when to use each option;
- Use attributes when
- You want to use "hard data" to score your projects against a criterion. For example, Capital Cost might be real data from vendors that you can store in TransparentChoice as an attribute and attach to the "Capital Cost" criterion.
- You want to collect data as an automated step in the Kanban. You can populate values for your attributes using forms.
- The number you want to use is the output of a model. For example, you might use net present value (NPV) to assess the financial impact of a project. You would, therefore, store the NPV of your project as an attribute as it's a "single number coming from outside the system".
- You want to include the opinion of just one subject matter expert. For example, you might have a senior project manager assess the risk of a project.
- Use surveys
- You want to capture subjective opinion from a number of people. For example, you might want to have a number of customer service representatives assess the impact of your projects on customer satisfaction. A survey will allow you to poll the opinion of these people and will also allow you to build a consensus among them - this is, after all, subjective data.
- You want to collect scores for multiple projects all at once. Surveys allow you to group together multiple projects and to score them all in one sitting / meeting.
You need to tell TransparentChoice which criteria you want to use scales for and which you want to use surveys for. First you click on "Question Types" then, for each criterion, you click on it then select "Scale" (when running a survey, you use a scale to score the projects) or "Attribute" (which then lets you select which attribute to use).
Why define data? | Attributes vs Surveys | Fill in this template
Fill in this template
This might all sound rather daunting, but it's not. The key is to create a document that you can use when building your data model. This helps keep everything clear in your mind and makes it quick and easy to build your model.
If you start by filling in the template attached to this tutorial (at the bottom of the page), you will find it much easier to build your project prioritization process.
First, fill in the list of criteria and decide whether you're going to use surveys (scales) or attributes. If you're using surveys (scales) then add in the scale you want to use (you can use a pre-defined scale or you can simple create an ad-hoc scale on the fly).
Next, create your list of attributes. The goal here is to keep track of everything in one place to make it easier to create your data model, forms and notifications.
Simply list all the attributes you want to include in your model. Some will be the ones that attach to criteria, but others might be for completeness or for analytic purposes. For example, if you create an attribute for "Department", this will not contribute to your strategic alignment score, but will be useful to help you see if any one department has too many projects (too much change can be bad) or too few projects (which can lead to unhappy stakeholders and an unbalanced portfolio.
COST IS AN ATTRIBUTE, NOT A CRITERION: The urge to make cost a criterion is often strong, but it's wrong.
People talk about cost being a criterion in all kinds of decisions, and picking projects is no different. But cost is not a criterion. Your criteria should help you measure how much "value" you expect to get from a project and "cost" is not "adding value".
Instead you should treat budget as a constraint and "Cost" is a measure of how much budget you're using up. Cost, therefore, should be an attribute that you track in TransparentChoice. Once you have your "strategic value score" you can plot it against cost to show value-for-money (or even create a calculated attribute showing value-for-money). You can bring all this information together in the project selection meeting; it will look something like this:
Why define data? | Attributes vs Surveys | Fill in this template