Assumptions and Validations
Introduction:
Assumptions were ideated as a team, and a long list compiled. The larger assumption list was cut down to a list of 7 core assumptions by voting as a team based on the Impact and Uncertainty score. The results of the final 7 can be viewed on Figure 1
In order to guarantee we hit enough types of assumption, they were categorised into: Market, Customer, User, Team, Access, Features, Technology, Financial*
*Financial Assumptions are covered in Business Model and CAC page
Competitor Adoption Reasons
Company Profile is Correct
User Profile is Correct
DFM is Target DFMA Issue
There is an Expertise Gap
Desired Analysis Level is Correct
We can Access DFM Expertise
Contents:
Assumptions and Experiment Plan
Competitor Adoption Reasons
Assumptions
There is an Expertise Gap
Desired Analysis Level is Feasible
DFM reduces cost
DFM is Target DFMA Issue
Company Profile is Correct
User Profile is Correct
Interviews
1.a Customer and
User Interviews
2.a Customer Interviews
3.a User Interviews
4.a Customer and User Interviews
5.a Customer Interviews
Other
1.f Survey
4.f DFMA Survey test
5.g User Part Test
6.g Customer and User Part Test
Secondary Research
1.b Sentiment Analysis
2.c Route to Market Research
4.b Sentiment Analysis
5.d DFM Course Research
6.d DFM Course Research
7.e Manufacture Study
Competitor Adoption Reasons
“If it’s expensive and doesn’t give me the depth of analysis I need it’s hard to justify”
Jake Moll, Mechanical Engineer at Innovia Technology
Anarug Chaudhary, Senior Engineer at Denso International
“High skills required. Not easy to learn for beginners. High cost.”
Callum Reynolds, Mechanical Engineer at Sagentia
“Most people in the team had never heard of them”
Customers are dissatisfied with and therefore not adopting competing products primarily because:
· They don't show the necessary time savings
· They are expensive
· They don’t satisfy the required level of analysis
· They have not heard of them
100%
of quotes mentioned one of the above concepts
1.a Customer and User Interviews
Input:
Interviews with 13 users and 13 customers:
Results:
Passed - 100% mentioned one of the concepts
Failed - All concepts were mentioned in at least 20% of quotes other than “they are expensive”, which was not mentioned
Users are dissatisfied with and therefore not adopting the competition primarily due to:
· A lack of integration into the engineer's workflow
· Effort to input excessive parameters
· They have a poor UI/UX
· A lack of real-time design feedback
· Steep learning curve to use the software
52%
of quotes mentioned one of the above concepts
1.b Sentiment Analysis
Input:
Quotes from 56 negative online customer reviews / complaints
Results:
Passed - 52% mentioned one of the concepts
Failed - All concepts are mentioned in at least 10% of quotes except “They don't show the necessary time savings” wasn’t mentioned
Minimal number of reviews suggests a lack of adoption
Company Profile is Correct
“I can see a programme like that being incredibly beneficial”
Calum Reynolds, Mechanical Engineer at Sagentia
Lionel Gousset, General Manager at CMR surgical
“There’s clearly room for a more robust, automated solution that gives precise, actionable
insights right when you need them.”
“If you manage to develop a solution ... would be useful, yes”
Dave Fustino, Product Development Lead at ETHO
The customers are those with software purchasing power in hardware engineering firms (typically business owners / managers), and we can access them in sufficient quantity. Hardware centred startups are a disproportionately good target for our route-to-market due to:
Utilisation of CNC machining & injection moulding
Typical Products are suitably sized with reasonable xo
Cost sensitivity & Quality constraints/requirements
Input:
Strict 1 hour search for 20 possible start-ups that match above criteria on google / chatgpt.
Results:
Passed - 25 start-ups were found that match the criteria
2.c Sentiment Analysis
52%
startups found in an hour that match the criteria
Input:
Interviews with 13 customers with explanation of effio product offering, whilst walking through them effio UI
Results:
Passed - 100% of customers asked had positive feedback
Interviewed 13 customers, indicating good access
1.a Customer and User Interviews
100%
shared positive feedback on the proposed tool
13
customer interviews, indicating good accessibility
User Profile is Correct
Kartal Cagatay, System Engineer at Olser Diagnostics
“If there’s a tool that from the CAD stage saves you from reworking the CAD, that would be quite nice. If it worked, it would be a multi‑million successful business.”
"If you can introduce a tool where even from the beginning engineers don't have to spend extra effort thinking about manufacturability... it adds real value."
Rizwan Qureshi, Mechanical Engineer at CMR surgical
The target users are mechanical design engineers in hardware engineering firms, and we can access them in sufficient quantity.
Input:
Interviews with 13 users with explanation of effio product offering, whilst walking through them effio UI
Results:
Passed - 85% of users had positive feedback
13 interviews with users conducted, indicating they can be accessed on mass
3.a User Interviews
100%
showed positive feedback to the proposed tool
13
user interviews, indicating good accessibility
DFM is Target DFMA Issue
"Manufacturability ... trips us up most, so that’s where we focus our energy."
Hania Mohiuddin, Founder of Mars Jets
James Adamson, Manufacturing Engineer at APPH
“Assembly rarely gives us big headaches. It’s really about manufacturability”
“I would say DFM is generally more important”
Design for Manufacturing or Design for Assembly?:
r/MechanicalEngineering
Design for Manufacture (DFM) is the most critical Design for Manufacture and Assembly (DFMA) issue (or a necessary prerequisite) that the users and customers want to see developed.
Input:
Interviews with 13 users and 13 customers, and 4 manufacturers
Results:
Passed - 67% of interviewees stated that they prioritised DFM over DFA
Users were more likely than customers to prioritise DFA over DFM, but were still more in favour of DFM
4.a Customer and User Interviews
67%
prioritised DFM as most critical DFMA issue
Input:
15 DFMA resources gathered using online platforms e.g. Reddit & Youtube
Results:
Failed - Of the 15 resources analysed, 7 favoured DFM and 8 favoured DFA
Test likely failed owing to traditional DFMA approaches beginning with DFA. This does necessarily mean DFA is the priority for users and customers
4.b Sentiment Analysis
20%
higher ranking on average DFM tasks
Input:
Asked respondents to rank which of these activities (DFM or DFA) is best to improve their or their teams skills
Results:
Passed:
Users: DFM ranked 14% higher
Customers: DFM ranked 30% higher
4.f DFMA Survey Test
There is an Expertise Gap
“There’s no easy place to pick up that real manufacturing intuition. Instead, you have to live it.”
Matt Stedman, Co-founder at Hard Stuff
Gregory Sale, Mechanical Engineer at PA Consulting
“The intuition, the expertise, the skill is locked up in engineers who spent decades engaging with these problems”
“A lot of the grads and the younger guys who are doing the CAD ... have no idea how it relates to the production line.”
James Adamson, Manufacturing Engineer at CMR Surgical
Ben Thorpe, Design & Manufacturer Manager at Naiad Aqua Systems
They [manufacturers] don’t care about the development up front, so you end up in this no man’s land…they’re just pointing out the obvious to you, you’re making the changes, going back—‘Is this right, can you check my homework?’—and yeah…”
“If you can’t plug that gap internally, you’ll hire it in. If you don’t have the time to upskill or the internal resources, you contract it out. That’s not always great, though, because you risk losing control. So it’s situational.”
Koushiic Durai, Founder at WowFactories
There is a clear gap in Design for Manufacture (DFM) expertise with the user, current methods for bridging the gap (upskilling, diverting internal resources, hiring expertise and contracting), are insufficient, and this is explicitly recognised by the customer.
85%
agreed there is a skills gap
Input:
Strict 2 hour search into as many commercially focused DFM courses as possible as a proxy for users requiring DFM education
Results:
Gathered a list of 16 online / in person courses / tutorials
Mix of 3 day in-person programmes and 3 hour online courses
5.d DFM Course Research
29%
of problematic features were identified by users
Input:
All of the manufacturability issues that users could spot in the sample part
Results:
Passed - Of the 14 problematic features, only 29% were identified on average
Detailed Results - Features and Validation Page
5.g Customer and User Part Test
Input:
Conducted interviews with 13 customers
Results:
Passed - 85% of interviewees agreed that there is an expertise gap
Passed - 73% of interviewees agreed that Current methods are insufficient
5.a Customer and User Interviews
73%
agreed current methods are insufficient
DFM Reduces Cost
The reduction of cost of DFM optimised parts is clear and of significant value to the customer
Input:
Sent part with problematic features to CNC manufacturer and asked to manufacture, on the assumption they will flag manufacturability issues
Results:
Passed - 25% reduction of cost from £326 to £260 through 2 proposed minor manufacturability improvements
3.a User Interviews
25%
reduction of cost from the 2 proposed modifications compared to original part
Interviews
Gathered a list of suitable companies to interview people from, based on the key criteria:
Utilisation of CNC machining & injection moulding
Products have appropriate scale and complexity
Cost sensitivity & Quality constraints/requirements
Used LinkedIn to find potential Customers and Users at each identified company and connected with them. Messaged them to request an interview, with the attached landing page / website.
In addition, contacted adjacent stakeholders, such as manufacturers and accelerator heads.
Role Breakdown of Interviewees
We interviewed 13 users and 13 customers
Manufacturing Engineers
Manufacturers
Accelerator
Heads
Founders
Mechanical / Design Engineers
Senior Engineers
Figure 2: DFM Part Test, Highlighting faces of problematic features
Figure 1: Collage of some of our Interviewees
Figure 3: Collage of some of the companies we have enagaged with
Survey Structure
20 people filled in the survey, enough for good DFMA data, but not enough for good Competitor adopotion data
