Mentoring Data: Extracting Useful Information, Pie Graphs and Bar Graphs

About two weeks ago I had a meeting with Richard Genzer. He recommended I transform the mentoring timelines into pie graphs and correlate them to the post-mentoring session follow-up I've been doing with the entrepreneurs. Once I've collected data, this type of correlation could allow me to come up with a theoretical breakdown of an optimal mentoring conversation. Also, by simplifying the data into pie graphs allows for quicker communication at a lower resolution, and will hopefully become easier to notice patterns.

The following series of images shows the transformation of the timeline into a pie graph and a bar graph. The first image is a legend that gives a greater description of the various conversational themes.

Legend

Mentoring Session 1
Mentoring Session 2

Mentoring Session 3


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Reflections on Design Research: Framing the Problem, Part 2

Re-reading my previous post about design research and how I described what it means for a human centered designer to frame a problem in the context of a community, I realized I needed to break down the different steps involved in framing a problem. Just as I did with my previous post, I'll use examples from my thesis to show the different steps, but this time I'll also reference several design texts. This will build up a language to describe design research and its role within the design process.

A theme in design research is to understand the relationships between different problems. Understanding how problems are connected by using visual mapping techniques can greatly aid in sense-making and communication. Communicating the interconnectedness of each problem, challenge, and opportunity allows for a deeper level of research that will shed light on the root of the problems you're tackling. Designers call these types of problems, wicked problems, because there is no single, simple, or straightforward solution. Instead, the solution takes on the form of a system of solutions, which tackles a system of problems. Sometimes prototyping and testing each solution within a system is a start. However, each solution for each respective problem is not enough, because a solution by itself does not anticipate the difficulties of interacting with other solutions. Thus, a systemic perspective of the interaction of solutions is necessary.

For example, after I finished my first round of interviews for my thesis, I became aware of three major challenges for the Philadelphia startup ecosystem. These three major areas included a disconnect between mentors and entrepreneurs, a lack of funding in the Philadelphia startup ecosystem, and the entrepreneur's concern with traction.

I then learned the relationship between these various themes that surfaced after I organized the data I gathered. The relationship is the following: if startups need funding, traction is usually required and having a mentor may prove to be a first point of traction. This is a valuable insight, but was not enough to justify focusing on mentors. Around the same time of these interviews, I came across a report published by the Startup Genome, which discovered two important pieces of information:

(1) "Hands-on help from investors have little or no effect on the company's operational performance. But the right mentors significantly influence a company's performance and ability to raise money."

(2) "Founders that learn are more successful. Startups that have helpful mentors, track performance metrics effectively, and learn from startup thoughts leaders raise 7x more money and have 3.5x better user growth."

These two key pieces of information pointed towards mentoring as a vital opportunity, challenge, and problem that required some sort of solution. Solving mentoring would then indirectly solve traction and funding because of these relationships between traction, mentors, and funding.

In his book, Exposing the Magic of Design, Jon Kolko presents three major steps: making meaning out of data, experience frameworking, and empathy and insight. Roger Martin, in The Design of Business, calls these same steps the knowledge funnel, when you're going from a mystery to a heuristic to an algorithm. These are all about discovering problems and solutions, and the important part of finding the problem is correctly understanding the relationships between different problems. If you take a look at the example I provided above from my thesis, the example shows the organization of data points into a heuristic, as Martin would call it, and making meaning out of data, from Kolko's perspective.

Making meaning out of data is the step you take when you've already completed a round of data collection and are working to find themes and structure to interpret the collected data.

Giving form to the data and finding patterns is messy!


Organizing and re-organizing the data reveals structures and relationships between groups of data.

From the previous example about traction, funding, and mentoring, getting to that finalized, clean, and communicable state takes time and requires an open space outside of your laptop. Kolko describes the need for using the physical format over the digital as a way to permit easy manipulation of individual pieces of data. Otherwise, hording the various pieces of collected data in a digital format imposes a file and folder hierarchy that may prevent insights to be gained.

More examples and thoughts about the design process to come in part 3 of this series.

To read the current draft of my thesis, go here.


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Social Entrepreneurship: A GoodCompany Group Discussion

A great discussion about social entrepreneurship between Fred Wilson, Jacqueline Novogratz, Roger Ehrenberg, Jacob Grey, and facilitated by Scott Edward Anderson. They delve into why VCs invest in social entrepreneurs, the role social entrepreneurship plays in our society, and the motivations of a social entrepreneur.

Discussion was hosted by GoodCompany Group.

Where's my Robot?

Interesting talk between Rodney Brooks, John Markoff, and Andrew McAfee about robots taking people's jobs and the role of robots in society and economy.



Transcript of the talk is here, or a wordle of its transcript:

Wordle: Wheres my Robot at Techonomy

Mentoring System, Iteration 4

I met with Garrett Melby a few weeks ago to receive feedback on the third iteration of the mentoring system. Some of the crucial pieces of information that I needed to better understand includes the business readiness intake, how mentors would sign-up for the service, how mentors and entrepreneurs would follow-up once they had an advising session, and how best to communicate the entrepreneurs request for mentoring.

The diagram below shows the next iteration of the mentoring network with feedback incorporated into it, and I've also been wrestling with a possible logo, brand, and mission statement for this thesis project. The current name is talKIN (it's a play on 'kin' referring to community). The mission statement is a conversation focused mentoring and advising community for entrepreneurs. The rest of this blog post will cover the different areas I received feedback on and various other details that have shed insight into better designing a mentoring network.

The business readiness intake is a two step process. First, the entrepreneurs from the original candidate group funnel themselves into idea stage, launch stage or operating business. This first part of the business readiness intake also asks for the elevator pitch and contact information. The second part of the filter has two components. The first component takes the idea and launch stage entrepreneurs and has them meet with an early stage strategist. The purpose of meeting with an early stage strategist is to help the idea and launch stage entrepreneur discover their problem areas, understand where to they need to focus, and where they need the most help. The second component takes the operating business and has it self-diagnose where its problem areas. The reason the idea and launch stage entrepreneurs meet with an early stage strategist is because entrepreneurs at this stage, do not yet know how best to focus their efforts or even the order of actionable steps to start a business.

When mentors from the different local mentoring organizations sign-up for this service, they choose based upon a sliding scale, their expertise and interests. Some of these areas include business development, customer development, finance, fundraising, legal, marketing, operations, product development, sales, and team. The mentor also chooses the industries they've worked in, provides their schedule, and how long they would like to have a mentoring session. Finally, the mentor chooses whether they would like to meet early stage, launch stage, and/or operating businesses.

Communicating to the various mentors on the network about the entrepreneur's problem areas is a delicate matter. To prevent mentors and advisers from fishing and to make sure that the entrepreneur feels safe about communicating the problems they're experiencing, the request for mentoring becomes a request review. The request review is less detailed and only presents the different areas the entrepreneur needs help without describing the problem the entrepreneur is experiencing. The request review is then sent out to mentors that match based upon industry, schedule, meeting duration, expertise, idea stage, launch stage, or operating business. Once a mentor agrees to meet, the mentor receives an email with a greater description of the problems the entrepreneur is having. Another detail is that a mentor can see whether another mentor has already agreed to meet, so they don't double book a session with the entrepreneur. This will prevent a waste of resources.

After the mentoring session comes follow-up. At this time, we ask the entrepreneur to give feedback on whether they found the conversation useful based upon the ideas discussed with the entrepreneur. For example, we would the entrepreneur whether they conversation moved him or her to action, or whether the ideas seem like good ideas when they acted on them. Furthermore, it seems vital that feedback is incorporated from both the entrepreneur and mentor about each other, but figuring out whether these will be positive or negative screens has not yet been determined.

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The Scientific Method of the Mind: What Sherlock Holmes can teach us about decision making

Maria Konnikova gives a great talk about decision making; and the process covers curiosity, self-reflection, mindfulness, creativity, logic and perception.

My Reading List through Design Grad School


These are some books and articles I've found to be useful in figuring out what design used to be, where design is going, and how ideas from other fields are mingling with design. If you have any questions, feel free to ask.


Online Articles, Papers, and Essays:

Cognitive Science/Neuroscience:

Interactive and Digital Design:

Social Dynamics:

Fundamental Concepts in Design:
Visualizing information/conversations/etc:

GoodCompany Group Summer Lecture Series

Just came across GoodCompany Group's summer lecture series on Vimeo. GoodCompany Group is an incubator and accelerator located in Philadelphia focused on social entrepreneurship. They seem to have valuable insight for social entrepreneurs on various topics like revenue and margin model, market analysis, go to market strategy, sales strategy, team building, and capital strategies. Enjoy!

 Revenue and Margin Model:

Market Analysis:

Go To Market Strategy:

Sales Strategy:

Team Building:

Capital Strategies: