Archive for the ‘Product Design’ Tag

How great design can set you apart from competitors

If I could rank all of Steve Jobs’s business lessons, the importance of design in supporting business success would top my list.

Don’t take my word for it, though. Many global market leaders, and not just in fashion, electronics or luxury brands, drive growth by continuously enhancing product design. However, companies without a design heritage or capability can also use this strategy to improve revenue and brand image.

In a simplified process, designers working in collaboration with product managers and engineers take creative ideas and marry them with a customer’s requirements and the company’s goals. The integration of this effort hopefully leads to the creation of an aesthetically pleasing, functional and profitable product. Design is the sum total of the properties of a product or service made up of the form (i.e., the aesthetics around look, feel, sounds etc.) and the function (i.e., the practical benefits delivered). Good design can help a company create or dominate a category (think iPhone); poor design can kill a brand (remember the Edsel).

Design isn’t just the purview of high-end, iconic consumer brands such as Apple, Louis Vuitton, Nike, and Bang & Olufsen. Some B2B manufacturers such as IBM (laptops), Herman Miller (office chairs) and Olivetti (calculators) have used product design leaders to dominate their categories.

Then there’s successful and well-designed brands including IKEA, Samsung and Canada’s Umbria, which have proven neither price nor a Paris, New York or Milan address are required for using design competencies as a key differentiator.

Nor do you need a large investment or a creative studio to compete on design. Take, for example, the experience of one of my clients — a manufacturer of high performance automation systems. The company, challenged to build market share without resorting to price discounting, tweaked its product designs and saw an immediate boost to revenue and brand image. Research showed buyers perceived little difference between products (not unexpected since the systems looked remarkably similar) despite the fact that system performance and warranties varied significantly. Not surprisingly, pricing was their key purchase driver. To stand out, the company had to leverage other attributes.

Management agreed to run an experiment: redesign its product demo to make it visually appealing and high end, then gauge its success through prospect and client feedback. This involved some simple design changes — repainting certain components, enclosing messy cable assemblies and enhancing the documentation and packaging. The response from the sales team and prospects was overwhelming. Sales closing rates and perceived product value jumped. Based on these results, the CEO decided to redesign the entire lineup.

Leveraging design is not for the impatient, undisciplined or risk adverse. World-class firms build internal competencies and ensure they become part of their cultural DNA.

Three best practices to achieve this are:

Learn Acquire a deep and multifaceted understanding of your customers’ needs (including sub-conscious drivers of their behaviour), as well as an understanding of emerging trends, such as mobile computing. Be mindful of Sony founder Akio Morita’s observation that consumers often fail to see the appeal of a breakthrough product on first hearing about it (the Walkman in this case). Keep the creative juices flowing by being plugged in to what is happening in complementary industries and related fields such as technology, nature, entertainment and fashion.

Build Assemble the right ingredients — talent, tools and processes — then give them the freedom to follow a vision consistent with the company’s goals. Collaboration is essential; designers should spend much of their time working directly with the product development and operational groups as well as external partners. Employing the right knowledge management systems and metrics will help ensure design excellence is institutionalized, cultivated and effectively managed long term.

Persevere Making these changes stick requires strong leadership, the pull of motivational values and goals and perseverance, not to mention a re-balancing of priorities. Internal alignment won’t always be easy especially when you are asking engineers and production managers to collaborate with designers. Finally, you need to be realistic. Not every new design, no matter how elegant, will be a hit with customers.

Mitchell Osak is managing director, strategic advisory services at Grant Thornton LLP. He can be reached at Mitchell.Osak@ca.gt.com Follow him at Twitter.com/MitchellOsak

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Choice Modeling: Polishing the Crystal Ball

When it comes to designing products that customers will buy in droves, the stakes have never been higher.  Despite billions of dollars of investment and countless hours of R&D, 90% of all new product launches will fail within 3 years of hitting the market. Furthermore, many products live as ‘walking wounded’, suffering from low market share, profitability and market differentiation.  The challenge is deceptively simple:  what is the ideal product that balances customer appeal, product profitability and supply chain fit?  The answer can be devilishly complicated, given the myriad of product combinations that could be delivered through different supply chains and sold in a range of markets.  

Fortunately, there are powerful, new analytical tools and methodologies that can help.   One of these techniques, Choice Modeling (CM), can improve new product success rates,  reduce business risk, increase customer knowledge and help define the optimal combination of features, services and prices for existing products. (Another powerful tool is CRM-driven data analytics)

Choice Modeling

As an approach, CM is part science and part art.  CM uses high-performance computer simulations and econometrics to understand and predict customer choice under various product configurations, market and environmental conditions.  In the past, marketers could only rely on simple statistical tools like regression analysis to understand a small set of cause and effect relationships between variables.  Thanks to CM, a firm can now dramatically accelerate the scope, depth and speed of their product analytical capabilities.

CM is being used to design products, services and supply chains in a wide variety of industries including consumer & industrial goods, financial services, hospitality, telecom and retail.

Using Choice Modeling

There are 3 basic steps to utilizing CM:

  1. The first step identifies the number of possible product, service or experiential features  (choices) that could influence a customer’s preference for your offering.  For a new car, the choices would include color, engine size, sales experience and options.  Information on choices can be gleaned from many sources including current product information, customer interviews, surveys and industry data.
  2. The second step is where the art comes in.  Marketers would design a series of simulations that ask customers to choose between a small number of choice options within a series of choice sets.  Using the car example, a simulation could be designed that asks customers to make choices between 2 different luxury packages (choice options) within a series of different feature collections (choice sets).
  3. The final step is where the science takes over.  Powerful econometric models are applied to a representative sample of respondents to identify empirical relationships between their selections of choice options and choice sets.  Unlike traditional tools, CM allows marketers to rapidly model and understand the relationships between hundreds of choices in hundreds of scenarios. Back to the car analogy, analysts would be able to test the impact of various option packages with different features on market share, segment profitability and customer satisfaction, before finalizing the product design and without guessing.

Poised for Growth

With the penetration of Web 2.0 technologies and higher bandwidth, it is now feasible to quickly gather key data and run simulations across multiple geographies, regulatory environments and customer segments.  Importantly, designers can now model unique and customized solutions to individual respondents or micro-segments using new advances in Bayesian statistics.

A Final Caveat

Like other analytical tools, CM is susceptible to “garbage in, garbage out” effects.  Problematic data, shaky assumptions and poorly designed simulations will inevitably lead to misleading results.  Furthermore, the most powerful CM models will not overcome incorrect findings arising from organizational effects like management bias or cultural influences.

 For more information on services and work, please visit the Quanta Consulting Inc. web site.