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Author: Ellie Martin

  • The 5 Core Principles of Lean Management

    The 5 Core Principles of Lean Management

    Lean project management is rooted in cost-saving manufacturing methodologies. The ultimate goal of lean methodology is to reduce waste. Companies in all industries have adopted lean principles into their own processes, but lean is most suited toward physical manufacturing, engineering and related industries.

    Regardless of your company’s size or the activities of your organization, lean project management principles can be extraordinarily helpful in optimizing your everyday operations.

    Below are the five core principles that guide lean thinking for project managers.

    Identify Value

    Defining the value of a given product is crucial. Before beginning any manufacturing project, or any project for that matter, the amount of value a finished product will generate must be assessed accurately. How much customers expect from a given product must also be ironed out.

    Value questions that lean teams will ask:

    • What do customers want?
    • How will they benefit from our product?
    • How much are they willing to pay for the benefits of our product?

    Lean teams can, for example, estimate how much customers are willing to pay based on related data points, then set costs low enough to reach an agreeable price. The goal is to eliminate all waste in every process. Any area where value is not added—or worse, cost is exceeding value—must be addressed early on using lean management principles.

    Map the Value Stream

    The value is the end goal of the project. Once you’ve established value as a definite endpoint, you can begin mapping the way to get there (or value stream). Every single process and every single step involved in getting to the end product is part of the value stream. From gathering the materials needed for production to coordinating efforts with PR, every related process is represented in the value stream.

    Kanban is one of the most popular ways to map value streams. Tasks are broken down and are posted in a “just-in-time” fashion. That way, each task is taken one at a time and only done when it is absolutely necessary to complete.

    Using Kanban flowcharts and other diagrams, managers can set up visual aids for value streams, mapping every single step onto a single page. By mapping the flow of activities, lean project managers can easily identify waste and inefficiencies with the process, allowing them to ameliorate these issues swiftly.

    Create Flow

    By mapping the value stream, project managers can spot waste. Any tasks that are done too early, too late or too often creates waste. By analyzing the map and removing waste, lean project managers can create the optimal flow of activities.

    Lean project managers check for possible bottlenecks and delays. If there are any inefficiencies present, tasks may have to be reordered. Sometimes, project managers may even decide to append value-adding tasks to improve processes.

    Ideally, every step should flow into the other, beginning at the factory (or organization) and arriving smoothly as an end product to the customer.

    Employ a Pull Approach

    Many organizations use a push approach, stockpiling supplies in anticipation of demand. Lean organizations, however, employ a pull approach, wherein production increases as demand increases. Customers can “pull” directly from the manufacturer, getting what they need in an on-demand fashion.

    The pull approach requires extremely accurate market research and exceptionally efficient dissemination of information within the organization. Also, all processes must be streamlined; otherwise, it will take too long to ramp up production to meet demand.

    Seek Perfection

    At its core, lean management is about continuous improvement. Lean management requires a thoughtful approach to every action. Optimization must be part of the corporate culture itself. Every member of the organization must be working toward removing waste, adding value and delivering quality. There is always room for improvement in lean organizations.

    Conclusion

    Lean organizations are removing waste. Lean project managers ensure that activities within the organization flow properly, without interruption, delays or bottlenecks.

    Identifying value means finding out what your product will do and how much customers will pay for it. Value streams are then mapped, following every step in production. Project managers ensure that tasks flow and processes run smoothly. Market data is collected during development and these data points drive production. The most important principle that guides lean thinking is to seek perfection. The lean management philosophy demands a dedication to continual improvement.

    — Ellie Martin

  • 4 Amazing Quantum Computing Applications

    4 Amazing Quantum Computing Applications

     Researchers across the globe, from the quantum researchers at University of Maryland synthesizing time crystals, to the research team at the University of New South Wales who are embedding atoms and their electrons into silicon, are pushing quantum computers forward, attempting to arrive at the most powerful quantum computing technology.

    IBM, Google and Microsoft are racing for quantum supremacy. IBM expects to create a 50-qubit general purpose quantum computer “within the next few years.” Indeed, the next iteration in quantum computing may be near.

    Why? Quantum computing could be the best path to ultra-powerful computers, and our best bet to solve unimaginably difficult problems. As our need for powerful processors continues to increase, and problems become larger in scope and complexity, we’ll need more complex computational systems to power solutions.

    Quantum Computers in Use

    Here are four amazing applications of quantum computers:

    Machine Learning

    Artificial intelligence needs to be able to pull from large datasets of image, video and text. Thankfully, there doesn’t seem to be a shortage of content. In fact, there may be an overabundance. Big data is out there to be analyzed, but we need more powerful computers to process the petabytes of unanalyzed data.

    Quantum computers could empower machine learning by enabling AI programs to search through these gigantic datasets concerning medical research, consumer behavior and financial markets—and make sense of them.

    Optimization

    Imagine, say, you are a traveling salesman. You wish to visit a handful of cities and want to know what the most optimal routes would be. This would be an example of an optimization problem. It sounds simple enough, but, in reality, the process can get quite involved as you up the number of variables. With only 270 destinations, for example, there are more combinations of travel than atoms in the universe.

    With quantum computers, however, we could expect a machine to be able to handle almost innumerable permutations and combinations, which could advance system design and analysis in massive ways.

    Biomedical Simulations

    With quantum computers, we can create, simulate and model molecular structures. Researchers at Harvard University used a D-Wave One quantum computer to solve the puzzle of how some proteins fold in 2012.

    “The model consisted of mathematical representations of amino acids in a lattice, connected by different interaction strengths,” writes Geoffrey Brumfiel in a news article for Nature about the Harvard researchers’ protein folding models. “The D-Wave computer found the lowest configurations of amino acids and interactions, which corresponds to the most economical folding of the proteins.”

    While the technology was nowhere near perfect—as the researchers cited that “10,000 measurements using an 81-qubit version of the experiment gave the correct answer just 13 times”—it was able to accomplish an amazing feat by modeling the behavior of protein folding with some degree of accuracy.

    Financial Services

    Quantum computing is already on its way. D-wave, a company backed by Goldman Sachs and Bezos Expeditions, among others, deployed its first commercial quantum computer: the D-Wave 2000Q, a quantum annealing system with 2000 qubits and advanced feature controls.

    Despite their prohibitive price, these computers are being utilized by a small niche, as illustrated by Harvard’s use of D-wave’s first model back in 2012. The systems could be used for complex financial modeling and risk management within the financial industry as well. Quantum computing could be used to find “new ways to model financial data” and isolate “key global risk factors,” according to IBM.

    “It would be great to build systems to help Wall Street better manage risk using this type of technology,” D-Wave Systems President and CEO Vern Brownell told Bloomberg. “They spend a lot on computing power [to manage risk].”

    Conclusion

    From managing money to massive datasets, quantum computing’s applications are seemingly endless. Advances in machine learning and optimization could boost efficiency dramatically. Biomedical and chemical simulations could help us land more drug discoveries and uncover new medical treatments in record time. Advanced computing power could lead to more than just innovation; it also could lead to lessened risk. Indeed, enhanced financial services could fundamentally change how we invest.

    As tech companies, computer scientists, and theoretical physicists help to perfect this technology, these truly amazing applications of quantum computing could become ubiquitous—and drive us further into a quantum age.

    — Ellie Martin