• Want to build a start up company that lasts? Think three-layer cake

    , ,

    https://www.fastcompany.com/91131427/want-to-build-a-company-that-lasts-think-three-layer-cake

     

    Building a successful business requires a focus on three key elements: product excellence, go-to-market strategy, and operational excellence. Neglecting any of these areas can lead to failure, as evidenced by the high percentage of startups that don’t make it past the five-year mark. Founders and CEOs must ensure a solid product foundation while also integrating effective sales, marketing, and management strategies to achieve sustainable growth and scale.

     

     

    • Foundation: Product Excellence, Core Values and Mission
      • Core Values: These are the guiding principles that dictate behavior and action within the company. They form the ethical foundation and are crucial for maintaining consistency in decision-making.
      • Mission: This defines the company’s purpose and goals. A clear and compelling mission helps align the team and provides a sense of direction.
      • Efficiency and Scalability: This layer focuses on creating efficient processes that can scale as the company grows. Streamlined operations reduce costs and increase productivity.

     

    • Structure: Operational Excellence and Innovation
      • Operational Excellence: Efficient processes, quality control, and continuous improvement fall into this layer. Ensuring that the company operates smoothly and effectively is crucial for sustainability.
      • Innovation: Staying competitive requires innovation. This involves developing new products, services, or processes that add value and keep the company relevant in the market.
      • Quality Control and Continuous Improvement: Ensuring that operational processes are of high quality and constantly improving helps maintain product excellence and customer satisfaction.
      • Technology and Infrastructure: Investing in the right technology and infrastructure to support business operations is vital. This includes everything from manufacturing equipment to software systems that enhance operational efficiency.

     

    • Strategy: Go-to-Market Strategy, Vision and Long-Term Planning
      • Vision: A forward-looking vision inspires and motivates the team. It outlines where the company aims to be in the future and helps in setting long-term goals.
      • Strategic Planning: This involves setting long-term goals and determining the actions and resources needed to achieve them. It includes market analysis, competitive strategy, and growth planning.
      • Market Understanding: A deep understanding of the target market, including customer segments, competitors, and market trends, is essential. This knowledge helps in positioning the product effectively.
      • Marketing and Sales Execution: This involves creating a robust marketing plan that includes branding, messaging, and advertising strategies to attract and retain customers. Additionally, building a strong sales strategy ensures that the product reaches the right customers through the right channels.
      • Customer Acquisition and Retention: Effective strategies for acquiring new customers and retaining existing ones are critical. This includes loyalty programs, customer service excellence, and engagement initiatives.

     

     

  • What the Boeing 737 MAX’s crashes can teach us about production business – the effects of commoditisation

    , ,

    newrepublic.com/article/154944/boeing-737-max-investigation-indonesia-lion-air-ethiopian-airlines-managerial-revolution

     

     

    Airplane manufacturing is no different from mortgage lending or insulin distribution or make-believe blood analyzing software (or VFX?) —another cash cow for the one percent, bound inexorably for the slaughterhouse.

     

    The beginning of the end was “Boeing’s 1997 acquisition of McDonnell Douglas, a dysfunctional firm with a dilapidated aircraft plant in Long Beach and a CEO (Harry Stonecipher) who liked to use what he called the “Hollywood model” for dealing with engineers: Hire them for a few months when project deadlines are nigh, fire them when you need to make numbers.” And all that came with it. “Stonecipher’s team had driven the last nail in the coffin of McDonnell’s flailing commercial jet business by trying to outsource everything but design, final assembly, and flight testing and sales.”

     

    It is understood, now more than ever, that capitalism does half-assed things like that, especially in concert with computer software and oblivious regulators.

     

    There was something unsettlingly familiar when the world first learned of MCAS in November, about two weeks after the system’s unthinkable stupidity drove the two-month-old plane and all 189 people on it to a horrific death. It smacked of the sort of screwup a 23-year-old intern might have made—and indeed, much of the software on the MAX had been engineered by recent grads of Indian software-coding academies making as little as $9 an hour, part of Boeing management’s endless war on the unions that once represented more than half its employees.

     

    Down in South Carolina, a nonunion Boeing assembly line that opened in 2011 had for years churned out scores of whistle-blower complaints and wrongful termination lawsuits packed with scenes wherein quality-control documents were regularly forged, employees who enforced standards were sabotaged, and planes were routinely delivered to airlines with loose screws, scratched windows, and random debris everywhere.

     

    Shockingly, another piece of the quality failure is Boeing securing investments from all airliners, starting with SouthWest above all, to guarantee Boeing’s production lines support in exchange for fair market prices and favorite treatments. Basically giving Boeing financial stability independently on the quality of their product. “Those partnerships were but one numbers-smoothing mechanism in a diversified tool kit Boeing had assembled over the previous generation for making its complex and volatile business more palatable to Wall Street.”

    (more…)

  • Photography Basics : Spectral Sensitivity Estimation Without a Camera

    , ,

    https://color-lab-eilat.github.io/Spectral-sensitivity-estimation-web/

     

    A number of problems in computer vision and related fields would be mitigated if camera spectral sensitivities were known. As consumer cameras are not designed for high-precision visual tasks, manufacturers do not disclose spectral sensitivities. Their estimation requires a costly optical setup, which triggered researchers to come up with numerous indirect methods that aim to lower cost and complexity by using color targets. However, the use of color targets gives rise to new complications that make the estimation more difficult, and consequently, there currently exists no simple, low-cost, robust go-to method for spectral sensitivity estimation that non-specialized research labs can adopt. Furthermore, even if not limited by hardware or cost, researchers frequently work with imagery from multiple cameras that they do not have in their possession.

     

    To provide a practical solution to this problem, we propose a framework for spectral sensitivity estimation that not only does not require any hardware (including a color target), but also does not require physical access to the camera itself. Similar to other work, we formulate an optimization problem that minimizes a two-term objective function: a camera-specific term from a system of equations, and a universal term that bounds the solution space.

     

    Different than other work, we utilize publicly available high-quality calibration data to construct both terms. We use the colorimetric mapping matrices provided by the Adobe DNG Converter to formulate the camera-specific system of equations, and constrain the solutions using an autoencoder trained on a database of ground-truth curves. On average, we achieve reconstruction errors as low as those that can arise due to manufacturing imperfections between two copies of the same camera. We provide predicted sensitivities for more than 1,000 cameras that the Adobe DNG Converter currently supports, and discuss which tasks can become trivial when camera responses are available.