1. Best Practice Report: Artificial Intelligence

    September 9, 2020 by BPIR.com Limited

    Artificial Intelligence (AI) involves using machines (i.e., computers) to do things that traditionally require human intelligence. This means creating algorithms to classify, analyse, and draw predictions from data. It also involves acting on data, learning from new data, and improving over time. Common AI applications include speech recognition, natural language processing, machine vision (which is similar to voice recognition but enables a computer to see and interpret), and expert systems, i.e., a software application using a database of expert knowledge capable of offering advice to facilitate decision making.
     
     
     
     
     
     
     
     
     
     
     
     
     
    The Stage
    The term “artificial intelligence” was first coined by John McCarthy in 1956. As one of the founders of AI, he and a group of research scientists started to clarify the role and concept of “thinking machines” at a workshop called the Dartmouth Summer Research Project. McCarthy proposed the workshop “proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.”

    Ever since, AI has been evolving and now has an impact on almost every aspect of life. It is seemingly everywhere. It is in your home (in the guise of Siri or Alexa, for example), at the train station, in public spaces (facial recognition technology), when you use your credit card, and anytime you use Google to search the internet. AI is here to stay; so, we might as well embrace it, and try to understand it better.

    There are two main types of AI: machine learning, and deep learning. Machine learning is the ability to process large amounts of data very quickly. In a manufacturing plant, for example, the machinery is hooked up to a complicated network being fed data, functionality, and production. The machine learning algorithm can rapidly analyse data and detect patterns or anomalies, notifying decision makers of non-optimised production levels or preventative maintenance issues. Deep learning is a widely used version of machine learning that involves multiple “brain-like” networks (neural networks), to engage in non-linear reasoning. Banks use it to detect fraud, and Tesla uses it for its self-driving cars. While machine learning is limited once a certain amount of data has been captured, deep learning is far more scalable. Therefore, deep learning models will be far more prolific.

    Businesses today are increasingly reliant on AI to gain an edge in sectors as diverse as banking, manufacturing, retail, health care, security, and farming. Most industry players use AI to identify, make decisions and, in some cases, predict trends and opportunities. One of the biggest advantages of the AI system is speed: it can outdo humans in processing large amounts of data, and present synthesised courses of action to human users. However, it has difficulty completing common-sense tasks, especially those that involve value-driven decisions.

    AI is increasingly affordable and accessible to businesses and the public, and there is a rapidly expanding range of ready-to-use services for all types and sizes of business. The question is, will AI take over jobs and make human input obsolete? Experts are not quite sure how or to what extent these algorithms will automate existing jobs, but they do agree that manual and managerial jobs will both be affected. New jobs, however, will also be created. Finally, the growing sophistication and ubiquity of AI systems has raised many ethical concerns such as bias, fairness, transparency, safety, and accountability. The algorithm, while being able to serve a wide variety of purposes, can never guarantee ethical decision making by a robot. After all, they have been taught by humans.

    1. What is artificial intelligence?
    2. Which organisations have been recognised for excellence in artificial intelligence?
    3. How have organisations reached high levels of excellence in artificial intelligence?
    4. What research has been undertaken into artificial intelligence?
    5. What tools and methods are used to achieve high levels of success in artificial intelligence?
    6. How can artificial intelligence be measured?
    7. What do business leaders say about artificial intelligence?
    8. Conclusion

    Access the report from here. At the bottom of the page is a PDF version of the report for easy reading. If you are a non-member, you will find some of the links in this report do not work. To join BPIR.com and support our research simply click here or to find out more about membership, email membership@bpir.com. BPIR.com publishes a new best practice every month with over 80 available to members.


  2. Best Practice Report: Strategic Foresight and Future Shaping

    July 23, 2020 by BPIR.com Limited

    Strategic foresight refers to the discipline of intelligence gathering, predicting alternative futures, and preparing for them. Today’s business world is increasingly uncontrolled and dynamic. Organisations need to have a good understanding of the overall macro-environment – i.e. the economy as a whole – so they can anticipate risks and threats, as well as explore megatrends, markets, and product and service demands. The purpose of strategic foresight is to develop a vision and cohesive, sustainable strategies to implement today, while positioning the organisation to create and maintain its preferred or alternative futures.
    The term foresight is often used in conjunction with future shaping. Future shaping refers to the influencing or recalibrating of organisational policies and processes to shape and support an envisioned future, both within and outside an organisation. The fundamental principle of future shaping is that future shaping influences the market – not the reverse.
     
     
     
     
     
    In This Report

    1. What is “strategic foresight and future shaping”?
    2. Which organisations have received recognition for excellent strategic foresight and future shaping?
    3. How have organisations reached high levels of success through strategic foresight and future shaping?
    4. What research has been undertaken into strategic foresight and future shaping?
    5. What tools and methods are used to achieve high levels of success in strategic foresight and future shaping?
    6. How can strategic foresight and future shaping be measured?
    7. What do business leaders say about strategic foresight and future shaping?
    8. Conclusion

    Access the report from here. At the bottom of the page is a PDF version of the report for easy reading. If you are a non-member, you will find some of the links in this report do not work. To join BPIR.com and support our research simply click here or to find out more about membership, email membership@bpir.com. BPIR.com publishes a new best practice every month with over 80 available to members.


  3. Best Practice Report: Information & Knowledge Management: Big Data

    June 20, 2020 by BPIR.com Limited

    The term “big data” refers to data that is too large or complex—or is changing too rapidly—to process using traditional methods. Instead, organisations use more advanced computational methods to reveal patterns, trends, and associations – particularly in terms of how people interact with each other and with their surroundings. These insights enable organisations to improve strategies and make better decisions. Big data is characterised by the “5 Vs”: volume, velocity, variety, veracity, and value.

    • Volume refers to the massive amounts of data.
    • Velocity refers to the high speed at which data is accumulated.
    • Variety refers to the nature of data which may be structured, semi-structured or unstructured.
    • Veracity refers to the inconsistencies and uncertainty in the data, as well as to disparate data types and sources.
    • Value refers to the importance of being able to convert all of this data into something useful.

     
     
     
    In This Report

    1. What is “big data”?
    2. Which organisations have been recognised for excellence in big data?
    3. How have organisations reached high levels of excellence in big data?
    4. What research has been undertaken into big data?
    5. What tools and methods are used to achieve high levels of success using big data?
    6. How can the use of big data be measured?
    7. What do business leaders say about big data?
    8. Conclusion

    Access the report from here. At the bottom of the page is a PDF version of the report for easy reading. If you are a non-member, you will find some of the links in this report do not work. To join BPIR.com and support our research simply click here or to find out more about membership, email membership@bpir.com. BPIR.com publishes a new best practice every month with over 80 available to members.


  4. Best Practice Report: Corporate Social Responsibility (CSR)

    April 15, 2020 by BPIR.com Limited

    Corporate social responsibility (CSR) is when an organisation takes responsibility for the impact of its decisions and operations on society and the environment. It is when an organisation achieves a balance between economic, environmental and social imperatives, and the expectations of stakeholders for the long term.
     
     
     
     
     
     
     
     
     
     
     
     
     
     
     
    In This Report:

    1. What is corporate social responsibility?
    2. Which organisations have received recognition for corporate social responsibility?
    3. How have organisations reached high levels of corporate social responsibility?
    4. What research has been undertaken in corporate social responsibility?
    5. What tools and methods are used to achieve high levels of success in corporate social responsibility?
    6. How can corporate social responsibility be measured?
    7. What do business leaders say about corporate social responsibility?
    8. Conclusion

    Access the report from here. At the bottom of the page is a PDF version of the report for easy reading. If you are a non-member, you will find some of the links in this report do not work. To join BPIR.com and support our research simply click here or to find out more about membership, email membership@bpir.com. BPIR.com publishes a new best practice every month with over 80 available to members.


  5. Best Practice Report: Strategy: Strategic Planning Process

    February 9, 2020 by BPIR.com Limited

    Strategic planning is a systemic process through which an organisation assesses where it is at the present time, communicates where it wants to be in the future (through its mission and vision), and makes the necessary decisions to reach its goals. The process includes making sure that monitoring, control and improvement mechanisms are in place, which help to ensure the smooth implementation of the plan and mitigate any interruptions.
     
     
     
     
     
     
     
     
     
     
     
     
     
     
    In This Report:

    1. What is a “strategic planning process”?
    2. Which organisations have been recognised for their strong strategic planning processes?
    3. How have organisations been successful with their strategic planning process?
    4. What research has been undertaken into strategic planning processes?
    5. What tools and methods are used to achieve high levels of success in a strategic planning process?
    6. How can the success of strategic planning processes be measured?
    7. What do business leaders say about the strategic planning process?
    8. Conclusion.

    Access the report from here. At the bottom of the page is a PDF version of the report for easy reading. If you are a non-member, you will find some of the links in this report do not work. To join BPIR.com and support our research simply click here or to find out more about membership, email membership@bpir.com. BPIR.com publishes a new best practice every month with over 80 available to members.