Observations of Mentor-Entrepreneur Interactions

I've noticed two types of interactions between mentors and entrepreneurs: serendipitous and planned. Serendipitous meetings between mentor and entrepreneur tend to occur at networking events, events like Startup Weekend or Philly TechMeetup, or even at coffee shops. Just as the word implies, serendipitous is unplanned, and even though neither party knows they are going to be in the same space at the same time, they discuss business and the mentor provides advice. Planned meetings between mentor and entrepreneur tends to occur over the phone, Skype, or face-to-face in office space or even a coffee shop. Planned meetings are more secluded and are set for a specified amount of time when compared to serendipitous meetings. When performing these observations, I asked myself what is required for learning to occur? I conjectured that it must be a safe mental space. To answer this question and test the validity of this statement, I looked for evidence of the emotional states during the interaction between mentor and entrepreneur to see if I could determine whether the entrepreneur was receiving business feedback in a safe mental space. Even though this statement helped guide my observations, in the end, the observations were useful in designing the prototypes for serendipitous and planned interactions.

Serendipitous Interactions:
One of the major patterns observed amongst serendipitous mentoring is a reflection of affect between the mentor and entrepreneur. If one individual was laughing the other did as well, if one individual was serious as was the other. 

I’ve learned from observing several unstructured and spontaneous mentoring in action, that a similarity in affect creates a social lubricant creating a safe mental space. Once this safe mental space is created, the feedback provided by the mentor was usually better received. At it’s most basic, this observation is simply a factor of how humans interact and communicate. Let me provide two examples of the same entrepreneur. In the picture below from Startup Weekend, both the entrepreneur and mentor were relaxed when the entrepreneur was receiving feedback on marketing and marketing strategies. After the meeting, the entrepreneur felt confident, calm, and had a sense of self-efficacy.

During the follow interaction depicted in the picture below, the mentor and entrepreneur were both tense. The mentor was providing feedback on the entrepreneur's product, and what channels of distribution they're using to reach their customers. After this interaction, the entrepreneur felt confused and frustrated. He was unsure about what channel of distribution to incorporate into his business model and presentation to the judges at Startup Weekend.

Planned Interactions:
While observing planned mentor interactions, I discovered four distinct steps that the interaction followed – an in-depth analysis of these four steps can be readabout in the next section because it lays the foundation for the Request for Mentoring Form. The part that I will discuss here are the emotional states I observed when the mentor began probing the entrepreneur about his business.

I'll pull data from one of the interactions I observed to serve as an example. The entrepreneur was asking about when he should raise funds and the terms associated with raising investment funds. To answer the question about when he should raise funds, the mentor then began asking questions about how the entrepreneur had acquired a hospital as a customer. The startup is building an app for doctors. The mentor followed up with how quickly the entrepreneur can acquire new hospitals as customers. The mentor then walked the entrepreneur through a set of scenarios based on assumptions of how quickly the entrepreneur can acquire new customers. When the meeting was over, the mentor was telling the entrepreneur that the business he's starting is valuable and the business has potential.

There are three distinct emotional states I noticed in the interaction between the entrepreneur and mentor. The first emotional state is calm because the entrepreneur is bringing the mentor up to speed on the current state of his business. The second emotional state is anxiety because the mentor is pulling out of the entrepreneur, the information she sees relevant to answering the question, to provide feedback, and to give strategic advice. The third emotional state is encouragement because the mentor provides encouragement to the entrepreneur about the business he's starting and the problem he's solving. However, there's a limitation to what I've observed about the third emotional state. During serendipitous mentoring interactions, the third emotional state went one of two ways: either no encouragement or encouragement. Since I've only observed four of these planned meetings, it's possible that it can also end with no encouragement, and I conjecture that there would be no closure to the anxiety that surfaces during the second emotional state.

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What is Entrepreneurial Learning?

In the previous section, I concluded that an entrepreneur is the role a person fills to create and manage a business to generate value for a customer. This implies that entrepreneurial learning is the learning that occurs while filling the entrepreneur's role. Since this thesis is studying and designing around the learning mentors provide for entrepreneurs, a definition needs to be developed that serves the purpose of guiding this thesis around the learning mentors provide for entrepreneurs. I will begin with an overview of various definitions of entrepreneurial learning, I'll then take what can be used from them, and finally, I will end with a discussion on why entrepreneurial learning matters for mentors.

In “Entrepreneurial Learning: a narrative-based conceptual model,” David Rae identifies three major areas that play a factor in the entrepreneur's learning: personal and social emergence, contextual learning, and negotiated enterprise. Personal and social emergence is the creation of the individual's self-perception as an entrepreneur. Essentially, believing that one's person can turn an idea into reality. Contextual learning is the use of one's knowledge and experience within an industry or community to recognize opportunities that ventures can be formed around. Negotiated enterprise is the process of engaging with other people to exchange labor, ideas, learned strategies, or capital (2).

Peter Erdelyi argues that entrepreneurial learning has two branches: one that involves personal learning and another that involves collective learning. Personal learning is focuses on the individual and her experiences, and is the process of “opportunity recognition” and constitutes the “cognitive mechanisms for identifying entrepreneurial business opportunities and making decisions about them” (3). Collective learning arises from the interaction of individuals within a firm or within an ecosystem. Both modes of learning give rise to behaviors that encourages the entrepreneur to acquire and use resources available within her network (3)

Berglund, Hellstrom, and Sjolander propose a model of entrepreneurial learning as a forward oscillation between two modes: hypothesis testing and hermeneutic learning. Hypothesis testing is coming up with an hypothesis and then preparing an experiment that allows to test the validity and soundness of the hypothesis, thus leading to learning. Hermeneutic learning, in contrast to hypothesis testing, occurs experientially and is tacit to the actions the entrepreneur makes. The entrepreneurs and the collection of individuals that comprise a startup, then fluctuate between these two states as they accumulate incremental knowledge about the product they're building, the customer's they're building it for, the market they're operating in, etc (1). Even though Berglund et al propose this model of entrepreneurial learning as a way to explain how venture capitalists influence entrepreneurial behavior, I think taking this model can be used within the context of a mentoring relationship to make obvious the entrepreneur's learning behaviors.

These researchers all hit upon a dichotomy between the individual and the networks they're a part of. The relationships the entrepreneur has with those internal to the startup and those external to the startup seems to determine the behaviors she learns, the opportunities she can recognize, and the opportunities she can act upon. What I mean is that entrepreneurial activity is inherently social in nature – it's both limited and enabled by the network the entrepreneur is a part of. It's limited by the size of the network and those she can learn from, and enabled by the people she's in contact with because she can learn new business strategies from her fellow entrepreneurs. This means that for the context of this thesis, mentors with business experience existing in the entrepreneur's network enable the learning of new strategies, behaviors, and can increase the size of the entrepreneur's network via introductions to new contacts. Entrepreneurial learning, from a mentoring perspective, is a feedback process to develop new strategies the entrepreneur can execute upon to continue managing her business.

The next section will go into a discussion of the different ways a mentor enables entrepreneurial learning.

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  1. Berglund, Henrik, Tomas Hellstrom, Soren Sjolander. "Entrepreneurial Learning and the Role of Venture Capitalists." Venture Capital July 2007: Vol. 9, No. 3, 165 - 181.
  2. Rae, David. "Entrepreneurial learning: a narrative-based conceptual model." Journal of Small Business and Enterprise Development 2005. Vol. 12 No. 3, 323 - 335.
  3. Erdelyi, Peter. "The Matter of Entrepreneurial Learning: A Literature Review."

A Mentoring Pattern Discovered

A pattern surfaced while observing mentoring sessions. Irregardless of the strategic area being discussed, I discovered that the flow of conversations between mentor and entrepreneur unfolded the same way. The conversation followed a four step process: strategic area, known facts and data, tried and tested strategies, and possible scenarios. For example, one mentoring session I observed, the entrepreneur was asking about when to raise funds. The mentor then narrowed in on how the entrepreneur had acquired their current customers - that the entrepreneur's father was a doctor at a certain hospital, and they leveraged his connections to beta test an app. After discussing strategies and data they had acquired while beta testing the app, the mentor walked the entrepreneur through a series of possible outcomes based on assumptions of how quickly they can acquire customers.
This newly discovered pattern can be leveraged to save time for both mentors and entrepreneurs. One application of this pattern is to prefill some of the information ahead of time so that the mentor can quickly aid the entrepreneur in building possible scenarios.

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What is a Startup?

The Kauffman Foundation in the study, The Importance of Startups in Job Creation and Job Destruction, defined a startup as any firm that's younger than one year (1). However, this umbrella term covers all types of startups irregardless of industry, and is too broad to use for this thesis. The working definition for this thesis is similar to the Startup Genome. They define a startup as “a developmental organism that evolves along five interdependent dimensions: Customer, Product, Team, Business Model and Financials" (2). This means that a startup is either an individual or a small group of people working on solving a problem by starting a business. The differences in my definition is that I add five more dimensions that I've surveyed and observed entrepreneurs managing in order to grow their startup. These ten areas are business development, customer development, finance, fundraising, legal, marketing, operations, product development, sales, and team.

Eric Ries in The Lean Startup defines a startup as “a human institution designed to create a new product or service under conditions of extreme uncertainty” (3). His definition is along similar lines as the Startup Genome's except that he includes the startup's environment: "conditions of extreme uncertainty." The "uncertainty" is an important aspect to the definition because it captures the fact that a startup lives or dies by how well it acquires and retains customers. The definition of a startup for this thesis combines both the Startup Genome's and Ries' definition with the aforementioned survey and observations.

A startup is a human institution that evolves under conditions of extreme uncertainty along ten interdependent dimensions (business development, customer development, finance, fundraising, legal, marketing, operations, product development, sales, and team) to create a new product or service for a specific customer/user group.

I think this is a useful definition for mentoring because it reveals the strategic areas that mentors can provide business advice.

The types of startups studied and entrepreneurs interviewed for this thesis have all been within the information technology industry.

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  1. The Importance of Startups in Job Creation and Job Destruction, Kauffman Foundation
  2. Startup Genome Report Extra on Premature Scaling, August 29th, 2011
  3. The Lean Startup, Eric Ries

The Information Technology Startup's Lifecycle & When Mentors First Get Involved

Steve Blank's Perspective:
In The Four Steps to the Epiphany, Steve Blank identifies four major stages for a startup, and they all revolve around how well the startup knows the customer. The four stages he discusses are customer discovery, customer validation, customer creation, and company building (1). Each of these stages are nonlinear. They are iterative, and are used to make sure the startup doesn't overextend itself.  Blank is teaching that it's most important to know the customer, their needs and wants, and finally developing a product or service that doesn't outpace the learning that's associated with knowing the customer.

“The goal of customer discovery is just what the name implies: finding out who the customers for your product are and whether the problem you believe you are solving is important to them” (1).

Customer validation is the stage where the startup builds “a repeatable sales road map for the sales and marketing teams … customer validation proves that you have found a set of customers and a market who react positively to the product: By relieving those customers of some of their money” (1).

Customer creation is the step where the company is building on previous successes of acquiring its first few customers. The goal of customer creation “is to create end-user demand and drive that demand into the company's sales channel” (1).

“Company building is where the company transitions from its informal, learning and discovery-oriented Customer Development team into formal departments with Vps of Sales, Marketing and Business Development” (1).

The Startup Genome's Perspective:
The startup genome defines the startup's life cycle in a similar fashion to Steve Blank. There are two major subdivisions: early and late stage. Early stage is the period of startup life where the team is working on figuring out how their product or service may best solve the problem of their target audience. A phrase often used to describe the product or service solving the problem is product-market fit. It means exactly what it says, product-market fit is the point where the startup has discovered how their product best meets the needs of their target audience. Product-market fit seems to be the same term as Blank's customer validation. Late stage is the period of startup life where the team is focused on making their early stage successes repeatable and scalable (2). From early to late stage, the startup life cycle is more nuanced, and the Startup Genome mentions six stages. Their report provides data and analysis on four of the stages: discovery, validation, efficiency, and scale. These stages are similar to Blanks definitions, and relate to the four types of information technology (IT) startups they discovered: the automator, the social transformer, the integrator, and the challenger.

During the discovery stage, the purpose of the startup is to figure out whether or not they're solving a problem that anyone is interested in. There are some key events that are typical for this stage, but not all have to occur: “founding team is formed, many customer interviews are conducted, value proposition is found, minimally viable products are created, team joins an accelerator or incubator, Friends and Family financing round, first mentors & advisors come on board” (2). For all four types of IT startups, the average amount of time to push through the discovery stage is between five to seven months.

During the validation stage, the startup is getting feedback on their product or service by means of money or attention. Essentially, they have proof that people are interested in their product or service. Some of the key events that are typical for this stage: “refinement of core features, initial user growth, metrics and analytics implementation, seed funding, first key hires, pivots (if necessary), first paying customers, product market fit” (2). For all four types of IT startups, the average amount of time to push through the validation stage is between three to five months.

During the efficiency stage, the startup is focused on making sure the business model works like a well oiled machine and they're efficiently acquiring customers based upon the research and customer knowledge they've built up during the previous two stages. Some of the key events typical for this stage include: “value proposition refined, user experience overhauled, conversion funnel optimized, viral growth achieved, repeatable sales process and/or scalable customer acquisition channels found” (2). For all four types of IT startups, the average amount of time to push through the efficiency stage is between 5 and 6 months.

During the scale stage, the startup is focused on aggressively growing the company and is typically defined by: “Large A Round, massive customer acquisition, back-end scalability improvements, first executive hires, process implementation, establishment of departments” (2). For all four types of IT startups, the average amount of time to push through the scale stage is seven to nine months.

Each of the four types of startups identified in the previous section all go through the same startup life cycle. However, the amount of time on average based upon the type of startup can vary significantly and can also vary based upon the size of the founding team. The automater takes an average of about 21 months to reach scale stage. The social transformer takes an average of 32 months to reach scale stage. The integrator takes an average of 16 months to reach scale stage. The challenger takes an average of 64 months to reach scale stage.

Application of this lifecycle discussion on mentorship:
This discussion on the lifecycle of the startup applies to this thesis in the context of when mentors become involved in the startup's life. The Startup Genome report has shown that mentors and advisers first come on board at the discovery stage, which is the first few months of a startup's life. So in the context of this thesis, it is most valuable to the startup if a mentor is involved in the discovery stage because "the right mentors influence a company's performance and ability to raise money" (2).

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  1. The Four Steps to the Epiphany by Steve Blank
  2. Startup Genome Report Extra on Premature Scaling, August 29th, 2011

Serendipity, Trust, and Identification: Three Areas that Greatly Influence Mentor-Entrepreneur Interactions

Imagine yourself at a networking event, and you’re looking for a person with an expertise in retail marketing in this crowd of people to mentor you and provide advice about what retailers your business should partner with. Instead, you get stuck talking to the lawyer for thirty minutes, and completely miss the person you should of been talking to on the other side of the room.

From my research, I've learned that finding the right business mentor is a three-pronged problem: it's rooted in serendipity, trust, and identification.

From interviews, I learned that serendipity means two things to the entrepreneurial community, a missed connection and how relationships form. The example of the networking event I had you imagine two paragraphs earlier - the entrepreneur getting stuck in a conversation with the lawyer - that's an example of a missed connection. In an interview with a local mentor explaining how he's met and formed relationships with young entrepreneurs, he said, "... most of it is very serendipitous ... that's how real relationships form. It's pretty hard to find your soul mate at a speed-dating session. Mentorship is a highly personal experience."

Trust is the second pillar governing mentor-entrepreneur interactions. In an interview with a local angel investor and organizer of community tech startup events, he recounted his experiences of organizing exclusive groups and meetings. He argued that the people in the group, even if they don't know each other, trust each other because it's exclusive to the degree that the people within the group know each others value. After my interviewee pointed this out, I began noticing it with the groups people all are a part of - i.e. universities, incubators and accelerators, etc. I think this is why an introduction from a friend proves to be effective.

Learning about trust as one of the underpinnings governing the interactions and meetings of entrepreneurs and mentors makes sense because it lowers the transaction cost on the exchange of information. The Rainforest by Hwang and Horowitt argue that the amount of distrust increases the transaction cost between people that want to exchange ideas, labor, and capital - the life and blood of any startup ecosystem. If there's a higher distrust in a startup ecosystem, then there are fewer transactions occurring between the various denizens of that ecosystem. In other words, people are not willing to seek a return on involvement, because there's a certain amount of risk associated with each transaction. If the risk is too high, and there isn't enough trust to make up for that risk, then the transaction will not occur. For example, an engineer and a business person, both with a similar idea for a product, will be unlikely to work together for a period of time because they do not trust each other.

Identification is simply the mentor identifying the entrepreneur, and the entrepreneur identifying the mentor. I've learned that it's normal for entrepreneurs to seek several strategic experts to advise on various areas of weakness. One entrepreneur summed it up quite well, "I tend to look for weaknesses of core competencies of specific aspects of the business model in the team." This means, a startup may feel comfortable with their product development, but needs advice on customer acquisition or on financial projections. So the entrepreneur will seek out a person who's an expert in customer acquisition or financial projections. This means that the entrepreneur identifies the right business mentor based upon their area of expertise.

The second part, the mentor identifying the entrepreneur has been a bit trickier to find a consistent answer across from mentors. It's also the part I've found to be new and intriguing, because the mentor is looking for an entrepreneur that is coachable. The question now posed is, how does one know if an entrepreneur is coachable? Two of the mentors I had interviewed and observed said they identify a teachable entrepreneur by the questions they ask. I imagine a solution to the problem of coachability will allow for non-mentors hoping to bring entrepreneurs and mentors together, to be able to screen for coachability. This is a vital part to understand if a mentoring system is to be designed.

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Revisiting Design's Value to Business

About two years ago, when I first started studying human centered design, I began articulating the value design adds to business. Re-reading my old blog post reminded me of my own inexperience with the matter, and now with two years of graduate design experience and a year's worth of experience in the internet startup world, I'd like to provide another round of analysis about design and business. These views are bound to change again in the future as I apply the design process to more business related problems.

When working as a human centered designer with a company, either as a consultant or an employee, the work the designer does begins and ends with people - their needs, their wants, their problems and challenges. The designer observes, interviews, and documents people to discover their needs and challenges. From there, the designer prototypes in response to what they've learned in order to test assumptions and iterate as needed. At the end of the day, it's about understanding people and creating meaningful services, systems, and products that meet the needs of the company's end user.

Now what that means for the internet startup (the community I've been a part of for the past year in Philadelphia) is that the human centered designer can help to understand, communicate, and refine the systems the startup's a part of, the people they're reaching out to, the services or products they're creating, and conveying how they all fit together. The role I've begun to fill is that of a thinker, a researcher, and a maker - and collaboration is the at the root of everything I just said.

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Eye Tracking Interactive - Iteration 2

The eye tracking interactive teaches kids and adults that their brain is hardwired to look for faces, motion, and changes in color. It accomplishes this experience by showing them a short video followed by the same video with an overlay of where they were looking.

The first version of the eye tracking interactive went through user testing and a few changes had to be made to help the user calibrate with the eye tracker. A problem I was facing with the eye tracker is to make it accessible for children and adults - dealing with their various heights. The first version was using face tracking to estimate where the persons face was in three-dimensional space, but this proved to be tricky since people continued to move after they calibrated. The removal of the face tracking system and an addition of a pair of eye-glass frames proved to be an easier way to keep people's head still while they were watching the video. Furthermore, the eye-glass frames conveyed the information that the user's eyes are being used to interact with the interactive. The following images and video show the changes made to the interactive.

Lie to Me

Lie to Me is an experience that teaches kids and adults about micro-expressions. When lying, the brain reveals its inner state through micro-expressions that cannot be controlled. I prototyped Lie to Me while working for the Franklin Institute. This digital interactive involves two players, one interrogator and one liar, facing each other across a table. They interact face-to-face and with two touch screens. A webcam is recording the liar every time the interrogator asks a question. The interrogator's objective is to analyze three video recordings of the liar and look for micro-expressions, and finally, choose the answer that contains the lie. This experience was developed using processing.

GoodCompany Group at Philly Tech Meetup

psGive, PhilanTrack, and Desmo presented their business and demoed their service two nights ago at Philly Tech Meetup. The evening was dedicated to social impact startups and all three were from GoodCompany Group, Philadelphia's social impact startup accelerator and incubator. The room was filled with entrepreneurs, developers, designers, investors, and two folks from the mayor's office. The feedback they provide is invaluable - Philly Tech Meetup is a space that allows the startup community to see what everyone else in the community is doing.
Stefan checking his notes. Sean practicing his presentation. Stefan (left), Sean (back), and
Dahna (right) preparing
for their presentations.
The first presentation of the evening was by Sean Steinmarc, founder of psGive. As he explained it, "psGive drives fan engagement through contests fueled by charity partnerships." Their platform brings together three audiences: brands that want to improve their image, social network users, and nonprofits. psGive is solving two major pain points: regulations and engagement. If a brand or nonprofit wants to run a cause driven campaign, there's a mountain of regulations they need climb over. And both nonprofits and brands want to be able to engage with their audience, psGive amplifies that opportunity.

Sean presenting PSGive.
Dahna Goldstein, founder of PhilanTrack, has created a service that sits between foundations and nonprofits, providing streamlined access to filling and submitting grant applications.

Dahna presenting PhilanTrack.
Stefan Portay, director of business development at Desmo, was the last presentation of the evening. Desmo is a platform that allows online shoppers to receive discounts and donate to the charity of their choice.
Stefan presenting Desmo.
The evening winded down with happy hour at City Tap House.

To see more pictures of this event, check out this flickr set.

Analysis of Second Round of Interviews

After completing the tangible interviews, I came back to my studio and put up the research all over the walls. I looked at the differences, similarities, and even refined the ecosystem map.

These interviews were set up to find out where people in the ecosystem believe they may find mentors in order to discover challenges that the entrepreneur may face while finding and accessing a mentor.

Main Takeaway:
I learned there’s a misperception about where entrepreneurs may find mentors. Entrepreneurs on the outside of accelerator and incubator programs believed that the majority of mentors could be found and accessed in incubators and accelerators. However, those on the inside of incubators and accelerators revealed that they find their mentors from previous founders of startups that have either had successful or failed exits. Essentially, they find experienced entrepreneurs who have enough available time on their hands and are at a place in their life where they want to give back to the rest of the startup community.

Second Takeaway:
While asking entrepreneurs to point out where they find mentors and how many mentors are closely or loosely tied with their startup, I learned that it's the norm for entrepreneurs to have many mentors. Each mentor plays a specific role, providing feedback and strategic advice on a specific part of the business. Their mentors would provide strategic advice on areas such as customer acquisition, refining the business model, hiring team members, product development, financial related tasks, etc. For example, a particular entrepreneur I interviewed explained that he had formed a relationship with one of his customers, and this customer has mentored them by providing strategic advice and feedback on how the product should be developed.

An important distinction:
These two takeaways revealed an important distinction: the generalist mentor and specialist mentor. The experienced entrepreneur brought in by accelerator and incubator programs seem to fit the profile of a generalist mentor because they have experience dealing with more than a single area (product, team, financials, customer, business model). The specialist mentor, as the word implies, has a single specialty and is providing strategic advice and feedback on that area. As stated before in the second takeaway, the norm for entrepreneurs is to be in contact with several specialist mentors.

Finally, I learned about four barriers to accessing mentors. Read Barriers to Accessing Mentors.

I later learned about how entrepreneurs identify a mentor for their business, and specifically that it's to the benefit of the entrepreneur to focus on finding and pursuing specific mentors.

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Barriers to Accessing Mentors

Barriers to accessing mentors can mean several things and arises from several underlying problems. In the graphic below, you can see the four areas that prevent entrepreneurs from accessing mentors.

I’ve learned from interviews and observations that having busy schedules act as a hinderance to permitting entrepreneurs and mentors from meeting face-to-face. 

Next, being geographically separated literally creates a disconnect between the experienced and novice entrepreneurs. 

The need for serendipity to take place, even though that’s the natural way relationships are built and begin, can also be seen as a barrier to connect the experienced and novice entrepreneur. For example, at a networking event where a novice entrepreneur has the intention of finding an experienced entrepreneur to discuss her business, might get stuck in a conversation with a software developer and not have enough time to find that experienced entrepreneur on the other side of the room. 

A very important piece of information that took me a while to discover, which also contributes to a lack of access to mentors, is that people with the right experience, whether their entrepreneurs, lawyers, investors, etc, don’t always self-identify as mentors. Even though these individuals could provide the same value as a mentor, the title mentor tends to have a burdensome connotation connected to it.

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Second Round of Interviews: Tangible Interviews

Having created a map of the ecosystem, I then went on to capture the deeper perspectives of individuals within the ecosystem. Borrowing concepts from cognitive science and its role in structuring effective interactions, a strategy I developed for creating an engaging interview is the tangible interview.

The concept behind the tangible interview is to enable the interviewee to physically represent information. The interviewee not only talks about the information, but can also see it and feel it. The tangible interview permits a better “grasp” of the information being communicated.

I think the effectiveness of the tangible interviews lies in its ability to create an existing structure for the information. Thinking about a question and answer survey of a typical interview is one way to structure the output of information; however, verbal communication limits the bandwidth of information that may be transfered. Furthermore, verbal communication also limits the types of individuals that may effectively convey what they actually mean by certain words.

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Mapping Philadelphia's IT Startup Ecosystem

To understand the varied perspectives from my first round of interviews, I grouped the different interviewees into categories that define the role they play within the ecosystem. These different categories include: service providers, coworking spaces, startups, incubators and accelerators, investors, community organizations, and universities. Once I grouped them, I realized there's an exchange of "stuff" that allows each group to continue to operate within the ecosystem. This "stuff" included funds, equity, labor, experience, etc. At its simplest, it's the ebb and flow of human interactions. It gives rise to organism-like structures that can be identified from how the people within the startup ecosystem group together. Furthermore, grouping people and the organizations they're a part of into these quasi-defined structures allows for one to analyze the interactions between those groups.

Having finished grouping them together, I realized I could use the map as a tool to further discover where certain resources may be located within the ecosystem. The resource I'm concerned with finding are mentors and the experience they provide. The current version of the map can be found here. The first version of the map is below:

I now had an interviewing tool to engage the interviewee in a way that uses more than speaking and listening, it uses touching and playing, an interviewing strategy I've coined tangible interviews.

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Atomic Sprocket Applet

Since the previous post, I've added a bit more pizzazz to the atomic sprocket. And if you want to play with it, I've embedded the applet here. If your computer has a microphone input, play a song and watch the atomic sprocket visualize the audio. If you want to get the script to embed this anywhere else, you can find it and its source code here.