# data[].attributes.body
I'd like to explore a data viz tool to resolve some of these data fidelity issues across all our survey tools and offerings

# data[].attributes.body
Idk that we're scoping for the level of data analysis that's happening. Good insights require spending time with the data, discussing it, referencing the stats, and iterating in the meaning making. Our current scope is designed to outsource and quickly report it out without the level of team engagement with it.

# data[].attributes.body
Naomi & team was not sufficient internal contact. Coordination mtgs were more transactional and they were terribly unhelpful for a lot of the dynamics we had to wade thru. Would reconsider having someone with broader latitude be part of this (just as Vini and board members were for Solidaire)

# data[].attributes.body
The capacity needed on this was steady for a couple months before the work really kicked in. We ate into our time with addl coordination, pushing back the 360, and then adding more deliverables (coaching addendum and exec report). We never recouped that time and the level of dysfunction increased the effort going into delivering a more impactful client experience and product.

# data[].attributes.body
maia is held a lot of responsibility on this project, and in general, on data focused work. the lack of direct communication with the client team feels like a challenge that presented issues that could have taken this whole engagement sideways

# data[].attributes.body
360s seem to be a really high value offering, what is needed to crystalize our approach

# data[].attributes.body
How do we ensure there's cohesion and alignment across other projects and consultants as well that the client has partnered with?

# data[].attributes.body
Great opportunity to weave this into the 360s that regardless of whatever tool/platform we use we need raw data to cross check numbers and easily find data mishaps

also helpful to begin to create deliverables that we're proud of to reference as templates

# data[].attributes.body
We shared a lot more data this time around than prior, which really pressure tested our data handling practices. We also made a lot of continuous improvement decisions to bolster the reports with addl insight and data leading to unplanned analysis, review, and production time

# data[].attributes.body
Extending coaching sessions to at least 4. I liked typing coaching sessions to the 360s, but 2 sessions was just too few.

# data[].attributes.body
We made a strategic pivot toward creating a 2nd group report which costs us a lot of additional production, review, and coordination time

# data[].attributes.body
we started naming scope creep pretty early with this client, and I'm curious if we attribute struggling with hours later on to early discovery stuff taking longer, were we working too much out of scope, or did we just under-scope it a bit? it would be interesting to compare these hours once they're final to Solidaire's and do a comparison

# data[].attributes.body
Generally questions on how impactful this work was for that team. With the level of mistrust present among the group, it almost feels like they are not ready to receive or act on the information provided

# data[].attributes.body
Clients have remarked consistently that they've found value in the engagement (coaching, willingness to hear feedback, appreciation of practical nature of the work)

# data[].attributes.body
Are we using the right tool? Or do we just need to figure out the CV file piece sooner?

# data[].attributes.body
this is more a question, but do we have reflections on our relationship with Naomi? I know there were some difficult points and I wonder whether in hindsight we might have done anything differently/intervened differently to mitigate that

# data[].attributes.body
They are an enjoyable client to work with, easy to keep work moving + solid collaboration

# data[].attributes.body
Individual reports were last minute & there were issues with data integrity

# data[].attributes.body
Do we want to test another tool or further hone our use of panoramic?

# data[].attributes.body
we only know so much about our clients, they are bringing in so much data without a desire to change or clear plan for action. not sure this was the right tool for them but it was rec'd by the board. anything we could have done differently to have the right people in the room? while Naomi and people ops are lovely, they aren't the changemakers needed for this work.

# data[].attributes.body
pairing coaching w/ 360s seems like a best practice. would we consider a package/something similar?

# data[].attributes.body
Given the level of dysfunction and broken trust internally, staff respondents completed their assignments at nearly 100%. We were able to build trust in our process and uphold the safety needed for folks to respond honestly.

# data[].attributes.body
Final group report was clear and actionable

# data[].attributes.body
do we like panoramic? are there other tools out there worth exploring?

# data[].attributes.body
The data issues caused a lot of extra hours and could have really undermined trust with the client. I'm interested to hear more about whether it was the timing, maia's process, our overall process, the tool, or what we attribute the data issues to. I know this has come up before with maia and want to make sure we address it

# data[].attributes.body
opp to strengthen our data management and review process

# data[].attributes.body
felt rushed due to changes in scope timeline from the client

# data[].attributes.body
lack of clarity on the data review and report production process

# data[].attributes.body
The coaching approach & coordination (although difficult w/ 3 different coaches) seemed to go really smoothly, and it seemed like you got good insights out of the coaching portion.

# data[].attributes.body
From my vantage point it seemed like the deliverable didn't match what ended up being their needs. The deliverable was documentation-driven, but they already had that and really needed trustbuilding/comms support.

# data[].attributes.headline
What questions do we have that should be explored before we execute on the offering again, or as we build the 360 SOP? Consider (1) Deliverables & Tools (2) Internal & External Communication (3) Scope, profit margin and hours (4) Project management (internal, external) and (5) Impact and value to client

# data[].attributes.subject
What questions do we have that should be explored before we execute on the offering again, or as we build the 360 SOP? Consider (1) Deliverables & Tools (2) Internal & External Communication (3) Scope, profit margin and hours (4) Project management (internal, external) and (5) Impact and value to client

# data[].attributes.headline
Where are there opportunities for improvement in the future - for client or consultant experience? Consider (1) Deliverables & Tools (2) Internal & External Communication (3) Scope, profit margin and hours (4) Project management (internal, external) and (5) Impact and value to client

# data[].attributes.subject
Where are there opportunities for improvement in the future - for client or consultant experience? Consider (1) Deliverables & Tools (2) Internal & External Communication (3) Scope, profit margin and hours (4) Project management (internal, external) and (5) Impact and value to client

# data[].attributes.headline
What threats might exist to future success in successful execution? Consider (1) Deliverables & Tools (2) Internal & External Communication (3) Scope, profit margin and hours (4) Project management (internal, external) and (5) Impact and value to client

# data[].attributes.subject
What threats might exist to future success in successful execution? Consider (1) Deliverables & Tools (2) Internal & External Communication (3) Scope, profit margin and hours (4) Project management (internal, external) and (5) Impact and value to client

# data[].attributes.headline
What proved challenging, for the client or the consulting team? Consider (1) Deliverables & Tools (2) Internal & External Communication (3) Scope, profit margin and hours (4) Project management (internal, external) and (5) Impact and value to client

# data[].attributes.subject
What proved challenging, for the client or the consulting team? Consider (1) Deliverables & Tools (2) Internal & External Communication (3) Scope, profit margin and hours (4) Project management (internal, external) and (5) Impact and value to client

# data[].attributes.headline
What went particularly well in this category? What are we proud of? Consider (1) Deliverables & Tools (2) Internal & External Communication (3) Scope, profit margin and hours (4) Project management (internal, external) and (5) Impact and value to client

# data[].attributes.subject
What went particularly well in this category? What are we proud of? Consider (1) Deliverables & Tools (2) Internal & External Communication (3) Scope, profit margin and hours (4) Project management (internal, external) and (5) Impact and value to client