Data Practices:

1.1 Kicking off a data project

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With Notes

Christine Doig

Data scientist

Netflix

Ian Greenleigh

Marketer

data.world

Sharon Brener

Product designer

data.world

Patrick McGarry

Community builder

data.world

Special thanks to Alexander Egorenkov. Author of “How to ask questions data science can solve” medium.com/@codefluently

Guiding Vision

Manifesto for Data Practices

Techniques

Data Teamwork Exercises

Tools

Your data toolchain + data.world

Values and Princples for Data Practices

What set of values and principles describes the most effective, ethical, and modern approach to data teamwork?

4 core values

12 principles

39 authors

1400+ signatories

datapractices.org/manifesto

Four core values

datapractices.org/manifesto

Inclusion

Maximize diversity, connectivity, and accessibility, amoung data sources, colaboration, and outputs.

Experimentation

Ephasise continuously iterative testing and data analysis.

Experimentation

Ephasise continuously iterative testing and data analysis.

Experimentation

Ephasise continuously iterative testing and data analysis.

Supported by leaders of the data community

39 authors, including:

Eric Colson, Chief Algorithms Officer, StitchFix
Amy Gershkoff, former Chief Data Scientist, Ancestry.com
Fernando Perez, creator of iPython, Assistant Professor, Statistics, UC Berkeley
Andrew Therriault, Chief Data Officer, City of Boston
Therese Couture, Human Trafficking Data Analyst, Polaris
Wes McKinney, BDFL, Pandas

1,300+ signatories, including:

DJ Patil, former Chief Data Scientist of the United States
Monica Rogati, former VP of Data Science, Jawbone
Kirk Borne, Principal Data Scientist, Booz Allen Hamilton
Tricia Wang, Fellow, Harvard Berkman Center
Jonathan Albright, Research Director, Tow Center for Digital Journalism
Gregory Piatetsky, founder, KDnuggets.com

Now what?

Guiding Vision

Manifesto for Data Practices

Techniques

Data Teamwork Exercises

Tools

Your data toolchain + data.world

Data Teamwork Exercises

How can we bring Design Thinking to data teams?

How can cross-functional teams work together to create better data projects and practices?

Design thinking dicipline

+

Data project workflow

=

Better data teamwork (profit)

Design Sprints

gv.com/sprint

IBM Design Thinking Field Guide

ibm.com/design/thinking

IDEO Method Cards

ideo.com/post/method-cards

Data project workflow

based on data.world user research

Kickoff

Start a new project with a question, problem, or dataset.

Source

Gather data sources, documentation, research, and team.

Profile

Define the data’s shape, features, and any limitations.

Prepare

Clean, munge, and wrangle the data into a usable form.

Explore

Develop a deeper understanding by querying, visualizing.

Analyze

Answer questions and build models in a reproducible way.

Deliver

Share output with stakeholders, report discoveries.

Data project workflow

based on data.world user research

Kickoff

Start a new project with a question, problem, or dataset.

Source

Gather data sources, documentation, research, and team.

Profile

Define the data’s shape, features, and any limitations.

Prepare

Clean, munge, and wrangle the data into a usable form.

Explore

Develop a deeper understanding by querying, visualizing.

Analyze

Answer questions and build models in a reproducible way.

Deliver

Share output with stakeholders, report discoveries.

Kickoff exercises

Start a project with a good question.

Consider stakeholders’ points of view.

Inclusion

Maximize diversity, connectivity, and accessibility, amoung data sources, colaboration, and outputs.

Experimentation

Ephasise continuously iterative testing and data analysis.

Experimentation

Ephasise continuously iterative testing and data analysis.

Experimentation

Ephasise continuously iterative testing and data analysis.

Exercise

Divide up into teams of 5.

Nominate a team lead.

Think about each exercise through a particular point of view (data analyst, sales/marketing lead, product owner, etc.)

Diverge

Create options by brainstorming individually

Converge

Make decisions by discussing as a group

You work for a one year old startup that has built an on-demand childcare services platform.

The board has asked your team to double revenue in the next 12 months.

Where do you start?

Exercise 1: Break down your objective.

Write down ideas and questions that, if explored or answered, could help you meet your objective.

Frame questions as:“How might we…[achieve this goal]?”

How might we double revenue in the next 12 months?

Write down as many sub-questions as you can, one per post-it.

5 minute exercise

Draw a horizontal line. Label the ends (low, high) and the midpoint.Place your post-its according to their impact level, clustering as you go.

Write down as many sub-questions as you can, one per post-it.

10 minute exercise

Exercise 2: Consider your stakeholders.

Who will be affected by each question and motivated to act by its answer? Sales? Marketing? New users.

ap only the highest impact questions to a key stakeholder.

Map your three most impactful questions to their key stakeholder.

Write down a few things each stakeholder cares about.

Marketing

Cares about:

Retention
Marketing mix
Proving value of efforts

Sales

Cares about:

Healthy sales pipeline
Increasing revenue
Number of touches to purchase

10 minute exercise

Exercise 3: Refine your questions.

With your primary stakeholder in mind, clarify any ambiguities in each high impact question.

Next, we’re going to break from the group and distill the HIGH IMPACT post-its as much as possible. This is important because having shared definitions and clear questions reduces friction and back-and-forth between stakeholders, increases the number of stakeholders who can benefit and contribute to the output, and aligns result to expectation. -- When we did this workshop at South By Southwest, Christine shared a story about working with a client who kept using the acronym SQL in a way that didn’t make sense to her. Turns out, she was thinking of the query language SQL, and the client was talking about Sales Qualified Leads. And a colleague of ours came from a company that had 7 competing definitions of the word “Enterprise;” this caused major problems for internal communication and in other areas.

As a group, discuss your clarified questions and refine further.

Original

Refined

Even clearer

Nebulous! perform in what sense?

Clearer, but over what time period?

All-time data is not helpful

CPA fluctuation

Seasonality

Format changes

Winner

In this example, we start with the question “How might we determine which ad channels perform best?” “Perform” is nebulous. So we change it to Cost Per Acquisition, because it’s the primary way our fictional company measures ad performance and it’s calculated consistently. But even now we have an issue because it’s not really helpful to know what ad channels have the best CPAs for all time--things change. In the final version, we choose a timeframe that matches the time we have to meet our objective. We now have a question to which we can provide a useful, unambiguous answer, powered by readily available data. -- As a group, review each question and see if you can refine even further. Is there a way to combine into a single, even clearer version? Are there really two questions competing for attention? Remove as much ambiguity as possible for every question.

Refine your top 3 questions by asking as a group:

Can I imagine any part of this idea or question being misinterpreted by another stakeholder?

Have I defined all ambiguous terms?

Am I being concise?

Is this question really multiple questions?

Is the intent of my question clear?

Is this a question that can be answered with available data?

10 minute exercise

You should have a stack of clear, high impact questions that are relevant to your key stakeholder and your overall objective.

We’re almost ready to kick off a productive data project, we just need a vision of what our end result should look like.

How might we double revenue in the next 12 months?

Marketing

Cares about:

Retention
Marketing mix
Proving value of efforts

Exercise 4: Draw the solution.

Now that you’ve refined your questions with your primary stakeholder in mind, what’s the best way to visualize* answers and output with them.

Express results however you want.

This part is individual. Divide a sheet of paper into four sections and draw a different solution in each quadrant. You’re not actually doing the analysis--just thinking about how to represent the answer to the question. -- Don’t spend more than 30 seconds on each square. Start a new page for each HIGH IMPACT idea or question, then move on to the next stakeholder. -- Example: -- From the previous exercise, we think this stakeholder really cares about retention. So we’re going to sketch or write out 4 different ways to convey how pursuing the ad spend idea will affect retention. -- So in one square you see a chart that projects churn rate over time, and in the top right I wrote out the predicted impact in a straightforward way. The two other squares are just placeholders since this is just an example.

Brainstorm how best to communicate the results.

What’s the best medium for communicating with this audience?

Is the result best conveyed as a chart? A single number? A new process? A story?

What level of detail do they want/need? How technical is your audience? How busy?

What’s the single most important metric? How do we define success (and failure)?

What comparisons make sense?

Do you need to see changes over time?

5 minute exercise

This part is individual. Divide a sheet of paper into four sections and draw a different solution in each quadrant. You’re not actually doing the analysis--just thinking about how to represent the answer to the question. -- Don’t spend more than 30 seconds on each square. Start a new page for each HIGH IMPACT idea or question, then move on to the next stakeholder. -- Example: From the previous exercise, we think this stakeholder really cares about retention. So we’re going to sketch or write out 4 different ways to convey how pursuing the ad spend idea will affect retention. -- So in one square you see a chart that projects churn rate over time, and in the top right I wrote out the predicted impact in a straightforward way. The two other squares are just placeholders since this is just an example.

Present and discuss solutions within your group.

What similarities do you see?

What are the strengths of each representation? What are the shortcomings?

What additional context will the stakeholders need to understand the representations?

What do the stakeholders expect?

What representations would be best for the largest number of stakeholders?

10 minute exercise

Present one “solution stack” to the rest of the room.

Original question

Key stakeholder + concerns

Refined question

Proposed representation

Data project workflow

based on data.world user research

Kickoff

Start a new project with a question, problem, or dataset.

Source

Gather data sources, documentation, research, and team.

Profile

Define the data’s shape, features, and any limitations.

Prepare

Clean, munge, and wrangle the data into a usable form.

Explore

Develop a deeper understanding by querying, visualizing.

Analyze

Answer questions and build models in a reproducible way.

Deliver

Share output with stakeholders, report discoveries.

Guiding Vision

Read and share the Manifesto for Data Practices

datapractices.org/manifesto

Techniques

Kick off a data project using these exercises

community@data.world

Tools

Collaborate with data team and document the process

datapractices.org/data.world

Want to run a workshop like this at your company?

community@data.world

Data Practices:

1.1 Kicking off a data project

Guiding Vision

Techniques

Tools

Values and Princples for Data Practices

4 core values

12 principles

39 authors

1400+ signatories

datapractices.org/manifesto

Four core values

Supported by leaders of the data community

Now what?

Guiding Vision

Techniques

Tools

Data Teamwork Exercises

Design thinking dicipline

+

Data project workflow

=

Better data teamwork (profit)

Design Sprints

IBM Design Thinking Field Guide

IDEO Method Cards

Data project workflow

based on data.world user research

Data project workflow

based on data.world user research

Kickoff exercises

Exercise

Divide up into teams of 5.

Diverge

Converge

You work for a one year old startup that has built an on-demand childcare services platform.

Exercise 1: Break down your objective.

How might we double revenue in the next 12 months?

Draw a horizontal line. Label the ends (low, high) and the midpoint.Place your post-its according to their impact level, clustering as you go.

Exercise 2: Consider your stakeholders.

Map your three most impactful questions to their key stakeholder.

Marketing

Sales

Exercise 3: Refine your questions.

As a group, discuss your clarified questions and refine further.

Original

Refined

Even clearer

Refine your top 3 questions by asking as a group:

You should have a stack of clear, high impact questions that are relevant to your key stakeholder and your overall objective.

How might we double revenue in the next 12 months?

Marketing

Exercise 4: Draw the solution.

Express results however you want.

Brainstorm how best to communicate the results.

Present and discuss solutions within your group.

Present one “solution stack” to the rest of the room.

Data project workflow

based on data.world user research

Guiding Vision

Techniques

Tools

Want to run a workshop like this at your company?

Don't forget to sign the values and principles! https://datapractices.org/manifesto