jump to navigation

Industry Recognition Received for Intelligent Operations Management February 22, 2008

Posted by Jeff in Business, collaboration, enterprise 2.0.
Tags: , , , , , , , ,
add a comment

We’ve reported on our conversations on the concepts, derivation, and terminology regarding Intelligent Operations Management in several earlier postings, including “Collaborative Decision Environments“, “Notes on Enterprise Software“, “Shorter Time to Volume is the New Goal“, and “Defining the Category: Intelligent Operations Management“.

In addition to the discussions with Bob Parker of Manufacturing Insights mentioned in many of the above postings, Serus has also made presentations to Gartner Group, AMR, Aberdeen, ChainLink, Ventana, and CIMData.

One of the first external validations of Serus’ concept of Intelligent Operations Management has now been written and released by Manufacturing Insights.  Their recent white paper, describes all layers and concepts of IOM, and provides examples of its use.

The term Intelligent Operations Management can be broken down its three terms:

  • “Operations” defines the scope of our solutions.  We address all parts of operations, including forecasting, planning, work in progress tracking, basically all the way from the manufacturing product specification (including ECO’s) and order placement through the fulfillment activities, WIP at your outsourced organizations, and finally interface with your financial systems for invoicing and reconciliation.  Not surprisingly, most of our sales are to the VP of Operations, though we have gained traction recently with the VP’s of Finance, and are starting to gain traction with the sales functions in our customers, these being on each end of manufacturing in the full lifecycle.
    We use this word because there are few systems that directly address the challenges within Operations.  Hence we provide unique tools that are based on real-world experience in operations, rather than trying to coble something together with a spreadsheet.
  • “Management” defines what we enable our customers to do within that scope.  Our definition of management means first solving visibility challenges so that you understand the situation, in terms of inventory levels, backlog, etc., but most importantly allowing control of the situation, by making decisions regarding actions, orders, and instructions that are fed back to the organizations in the supply chain.
    This concept of management is most clearly thought of in terms of “feedback loops” which are a combination of visibility and control with the idea that corrective action is being taken, and new insights or information is being gained each time through the loop.
    Our product has dashboards that allow you to access information at the visibility, or raw content level.  A related concept is that the content has come from multiple sources, and hence has had to be collected and cleansed, meaning resolving errors or inconsistencies, such as inconsistent naming and organization.
  • “Intelligent” defines the next level above Management, which adds the ability to define business goals and operational constraints within with the system’s operation.  A typical example of a goal is to “keep service levels above 98%”, or “Reduce stockouts to no more than 5%”, or “reduce inventory”, etc.  Adding goals into the decision making allows the system to suggest solutions or possible decisions that are biased toward the goal, again enabling the feedback loops to run more efficiently.  Another goal may be to carry out or advance a business process, as business processes act as the foundation for many feedback loops.
    Examples of operational goals within which decisions are carried out occur in often in finance, where for example a trading organization makes trading decisions but within a corporate goal of maximizing profit, and other goals that limit credit risk or cash utilization.

A classic example of a goal driven planning system is a supply chain planner, which has an engine that generates plans given a set of operational goals and thresholds.  However, many supply chain engines run overnight, and the plans that they produce are often out of date by 10 or 11AM the next morning, due to some unexpected change.  For this reason. Serus focuses on rapid tactical replanning, such as handling a supplier outage through a local replan, with a goal being to assure that this outage and plan does not affect other production activities.

Two important terms that don’t appear in the IOM term per se, are “collaboration” and “ecosystem”.

“Collaboration” defines the nature of the interactions between the different members of the supply chain.  It holds that no decision can be made in isolation, but instead have a context or state that defines them.  Typical examples are one of agreeing on an inventory stocking level by first communicating several different what-ifs or scenarios.  Or proposing different dates or product specifications between one organization and other, until agreement is reached.  Information can be changed, shared, retracted, committed, etc.

“Ecosystem” defines the set of participants within the collaboration, which can be all members from suppliers to customers, but also extends the definition of the information used in the decision process to include content from public and private sources, as well as content that is feedback, evaluations, and lessons learned within the ecosystem, in the same way that eBay or Amazon provide content about the members, books, and products that is created within the site augmenting the public information such as book descriptions.  In our case, ecosystems provide benefit when performing collaborative actions and decisions toward meeting a goal.

The Role of Master Data Management in Operations November 16, 2007

Posted by Mike Lazich in Business, Technology.
Tags: , , ,
1 comment so far


Master Data Management (MDM) is a discipline for providing consistent content of your key reference data across different parts of your organization.  Examples include:

  • Standard customer data
  • Standard part data
  • Standard pricing data

MDM has emerged in the last several years as a separate enterprise software architecture category as the requirement for consistently defined and maintained enterprise data has become more apparent.  (more…)