rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Improving Forecasts with Integrated Business Planning
    sub title: From Short-Term to Long-Term Demand Planning Enabled by SAP IBP
  name:
    name part: Sankaran, Ganesh.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Sasso, Federico.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Kepczynski, Robert.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Chiaraviglio, Alessandro.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVI, 421 p. online resource.
  abstract: This book provides both a broad overview of the forecasting process, covering technological and human aspects alike, and deep insights into algorithms and platform functionalities in the IBP toolbox required to maximize forecast accuracy. Rich in technical and business explanations, it addresses short-, medium- and long-term forecasting processes using functionalities available in demand planning and demand sensing. There are also several theoretical concepts underpinning the algorithms discussed; these are explained with numerical examples to help demystify the IBP forecasting toolbox. Beyond standard procedures, the book also discusses custom approaches (e.g. new segmentation criteria, new outlier detection and correction methods) and new methods (e.g. the use of Markov chains for forecasting sporadic demands), etc. It subsequently benchmarks common practices using these innovative approaches and discusses the results. As measurement is an important precondition for improvement, an entire chapter is devoted to discussing process improvement and value using the Six Sigma methodology. In closing, the book provides several useful tips and tricks that should come in handy during project implementation. .
  table of contents: Introduction -- Building Demand Planning Organization and Competencies -- Efficient and Effective Usage of Out of the Box Statistical Forecasting -- Custom Method to Forecast Seasonal Products -- Custom Method to Forecast Intermittent Products -- Value of Forecasting with Custom Methods -- Improving Short Term Forecast with Demand Sensing -- How to Measure and Improve Forecasting.
  note: by Ganesh Sankaran, Federico Sasso, Robert Kepczynski, Alessandro Chiaraviglio.
  subject:
    topic: Management information systems
  subject:
    topic: Industrial management
  subject:
    topic: Application software
  subject:
    topic: Sales management
  subject:
    topic: Business logistics
  subject:
    topic: Business Process Management
  subject:
    topic: Information Systems Applications (incl. Internet)
  subject:
    topic: Sales/Distribution
  subject:
    topic: Supply Chain Management
  subject:
    topic: Business Information Systems
  classification: HD30.2
  classification: 658.4038
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Management for Professionals
  identifier: 9783030053819
  identifier: https://doi.org/10.1007/978-3-030-05381-9
  record info:
    record creation date: 190305
    record change date: 20191025231515.0
    record identifier: 978-3-030-05381-9