# data[].attributes.body
Abandon the MVP terminology and create phases for projects. (get to market more quickly)

# data[].attributes.body
We know a decent amount about our own students, but with an increased emphasis on driving new enrollments, I don't know if we have great data on potential students not yet in our system. I'd like to see more externally focused data to help make these decisions.

# data[].attributes.body
Spend more time on the discovery phase of projects.

# data[].attributes.headline
agree on new language and terminology that will allow for quick pilots or proofs of concept to be developed without expectation that they will be perfect

# data[].attributes.subject
agree on new language and terminology that will allow for quick pilots or proofs of concept to be developed without expectation that they will be perfect

# data[].attributes.body
Start small and iterate. Be agile!

# data[].attributes.body
Make RACI a best practice so not everyone has to be involved in every project. Clear decision makers.

# data[].attributes.body
continue to build our capacity to change processes, not just systems.  It is hard and there's no common method or vocabulary.

# data[].attributes.headline
assign teams to a project on a full-time or near full-time basis so that resources are devoted to the project and prioritized - similar to the GE "workout" model

# data[].attributes.subject
assign teams to a project on a full-time or near full-time basis so that resources are devoted to the project and prioritized - similar to the GE "workout" model

# data[].attributes.headline
Need to identify KPIs and metrics for each area as well as DCE as a whole in order to help with resource planning

# data[].attributes.subject
Need to identify KPIs and metrics for each area as well as DCE as a whole in order to help with resource planning

# data[].attributes.body
Scope Freeze

# data[].attributes.headline
More robust discovery should happen before a project is proposed. And/or if during that discovery things come up that show a reason not to continue with a project, we should stop it. 

# data[].attributes.subject
More robust discovery should happen before a project is proposed. And/or if during that discovery things come up that show a reason not to continue with a project, we should stop it. 

# data[].attributes.body
Clear, in-depth submission forms divided into step levels. Complete step one, submit. If approved moved to step two. This way the submitter/requester isn't inventing the process each time and the process is broken into smaller chunks that move through the system smoother.

# data[].attributes.body
Think about how a project might be useful to multiple units/programs

# data[].attributes.body
Do we need a better bank of project managers perhaps at the enterprise level vs. the local level

# data[].attributes.headline
Avoid recreating the wheel by building on prior strategies, tools, etc. that have worked for a project that's similar.

# data[].attributes.subject
Avoid recreating the wheel by building on prior strategies, tools, etc. that have worked for a project that's similar.

# data[].attributes.body
Consider two types of projects: on-going/upkeep vs. innovation. Perhaps a % of sprint is split for both.

# data[].attributes.body
Include benchmarking data from peers in our decision making. Don't just look at internal numbers (enrollments, revenue) rather consider impact on other Harvard departments and the market (our peer institutions).

# data[].attributes.headline
Do we need to be more disciplined about how we use the word critical?

# data[].attributes.subject
Do we need to be more disciplined about how we use the word critical?

# data[].attributes.headline
what data do we have to support the need for the project in the firstplace?

# data[].attributes.subject
what data do we have to support the need for the project in the firstplace?

# data[].attributes.body
How do we define "continue business?"

# data[].attributes.body
1. Compliance or functional tickets that need to be completed in this sprint to continue business.

2. Projects moved forward via the PPG with the minimum points to keep the project on time/task.

3. Tickets advocated for at the planning meeting (this will soon come from Kerry).

# data[].attributes.headline
Should there be a certain percentage of time that gets allocated to project work vs. operational work?

# data[].attributes.subject
Should there be a certain percentage of time that gets allocated to project work vs. operational work?

# data[].attributes.headline
Scope out the project first before bringing it to the committee.

# data[].attributes.subject
Scope out the project first before bringing it to the committee.

# data[].attributes.body
"Hard coding" percentages to allocate toward each bucket is clean way to divide this, but I don't think necessarily it results in a better use of resources. Certain projects will carry more weight or have an oversized impact on our operations and should be prioritized accordingly. I think a manual review of all tickets is necessary.

# data[].attributes.body
DCE staff tends to agree to do things even if they are stretched thin. We need a concrete way to manage the additional work projects put on people.

# data[].attributes.headline
Identify KPIs that demonstrate value. Track and measure these metrics.

# data[].attributes.subject
Identify KPIs that demonstrate value. Track and measure these metrics.

# data[].attributes.headline
Collect and cross-share data from multiple areas to get a more holistic picture of opportunities and challenges

# data[].attributes.subject
Collect and cross-share data from multiple areas to get a more holistic picture of opportunities and challenges

# data[].attributes.headline
Talk to Chris Campion & team. Synthesizing data needs into a clear and concise project plan can be tough. Our data experts can help at the beginning, middle, and end of projects.

# data[].attributes.subject
Talk to Chris Campion & team. Synthesizing data needs into a clear and concise project plan can be tough. Our data experts can help at the beginning, middle, and end of projects.

# data[].attributes.body
Sprint planning exists in Salesforce world and while not perfect, at least we know how it works.  I'm not aware of similar processes for Banner (Jeff L's team) or Analytics (Chris' team).  We do tickets but have no idea about capacity or how important our reqeust is relative to everything else. How to remedy?

# data[].attributes.headline
Identify what we're trying to measure first. Is there a way to extract that data, if no data, then identify what are we using to measure the success of the project.

# data[].attributes.subject
Identify what we're trying to measure first. Is there a way to extract that data, if no data, then identify what are we using to measure the success of the project.

# data[].attributes.headline
Do we need to move toward a more structured tracking of time and resources spent on projects, tasks, etc.?  This has not been part of DCE culture in the past

# data[].attributes.subject
Do we need to move toward a more structured tracking of time and resources spent on projects, tasks, etc.?  This has not been part of DCE culture in the past

# data[].attributes.headline
Possibly create a brief survey to get at this question that goes out twice a year.

# data[].attributes.subject
Possibly create a brief survey to get at this question that goes out twice a year.

# data[].attributes.body
Determine what data is necessary to evaluate the success of a new project

# data[].attributes.headline
Find a way to quantify the number of hours a project might need to better allocate resources. 

# data[].attributes.subject
Find a way to quantify the number of hours a project might need to better allocate resources. 

# data[].attributes.body
Proposed projects should have a revenue or enrollment projection.

# data[].attributes.headline
be more clear at the beginning of a project what the definition of success is and how it will be measured

# data[].attributes.subject
be more clear at the beginning of a project what the definition of success is and how it will be measured

# data[].attributes.body
What gets measured gets managed - Drucker

# data[].attributes.body
should we track time on a given project?

# data[].attributes.headline
assemble a team that is focuses on innovation along with a budget and resources

# data[].attributes.subject
assemble a team that is focuses on innovation along with a budget and resources

# data[].attributes.body
Set X% on innovation, and X% on continuous improvement and operations for the year.

# data[].attributes.body
should we allocate points each sprint to project, innovation, operational work.