Our Hernon Manufacturing case studies show you how our technology and problem-solving abilities helped clients—clients just like you—to improve the efficiency and safety of their process.
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We can help you find the same success. See what we mean by reviewing the Hernon Manufacturing case studies below. Oil seals are an integral part of rotary applications. They ensure consistent and reliable performance of mechanical equipment such as gearboxes and hydraulic cylinders as well as in other power transmission and automotive applications.
They do this by closing spaces between stationary and moving components of an engine which helps stop lubricant from leaking. They also prevent harmful contaminants, such as other fluids or dirt from entering machinery. Traditionally, solvent based, rubberized sealants and coatings were used to make oil seals. This lengthy, batch process had numerous problems. Long Drying Times — After the seal was applied, each batch would need excessive drying time for evaporation. Costly ventilation systems were also necessary to protect workers from harmful solvents.
And what did Russians do?? The Russians used a Pencil!!! So, learn to focus on solutions not on problems. Solving Customer Problems Don't look at customer problems as a necessary burden of business. Socratic Method.
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To solve a problem, brake it down into a series of questions, the answers to which gradually distill the answer you seek Prototyping at IDEO. Prototyping can help you tackle problems when you don't have the answers. Focused prototyping helps resolve little critical problems one by one. At Fidelity Investments Kaizen involves recognizing problems and needs, rather than denying them, so they can be addressed.
T — Target :: "Where do we want to be?
What Does Problem Solving Look Like?
R — Research : "What research do we need? We showed the products share of preference: within its unique market, the total client share in each market, the total competitor share in each market. We also recommended improvements that could be leveraged and used across all three markets.
After delivering recommendations and completing the simulator training, the client felt that the project was a complete success. This feedback was also delivered from business stakeholders who continue to use the simulator provided almost 1 year after completing the project. A new head of brand strategy for a large consumer electronics manufacturer needed to create a process she could use to measure current brand effectiveness in order to impact of new strategies going forward.
The company did not have any in-house research staff, so she asked us to become involved. We critically refined brand attributes to ensure that they were unbiased and concrete for respondents.
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We ensured appropriate competitive brands were included to allow for brand mapping of the entire ecosystem. We employed a methodology that could rank the attributes in terms of objective importance to purchase consideration. Anchored MaxDiff ranked the importance of attributes to purchase consideration. The client was very pleased with the process and our ability to communicate results using business language rather than research terminology. The trust our client has in us has led to multiple projects and presentations with executive leadership including the CMO and CEO.source site
We are seen as a resource with which business problems can be discussed well before the development of RFPs. Beyond the qualitative information they collect during this exercise, the company wanted to expose respondents to a trade-off exercise incorporating features and price. Optimize the price and feature set for a new vehicle. Understand price sensitivity and the incremental value associated with particular feature enhancements.
A conjoint exercise was designed and placed on computers in the clinic environment. Respondents first viewed vehicles live, then images of the vehicles, along with specific feature call-outs, and prices were designed into a choice-based conjoint exercise with conditional price adjustments. Conditional pricing was necessary to accommodate the differential price effects of similar features based on body type, trim, etc.
Hierarchical Bayes analyses allowed limited sample sizes while still producing useful models. A what-if market simulator was created to allow feature ad price optimization within the context of a likely competitive consideration set. The project success led to positive feedback from the product development team regarding the usefulness of the results, money savings due to more focused development strategies, and repetition of this project methodology for other vehicle scenarios. We determined feature preference and resonance with value proposition using an Anchored MaxDiff methodology.
We then combined the Anchored MaxDiff scores with targeting variables and likelihood to buy measures in a Reverse Segmentation analysis.