There are times when our clients require specific and or temporary use of technology infrastructures to address a specific project need. When these circumstances arise, we leverage our infrastructure investments so that our clients will not have to purchase computer servers, buy software and install software, map to avariety of data sources, and ulitimately train and configure their newly purchased solutions. The client benefits from leveraging our infrastructure and expertise so that they can focus on accelerating value realization of their projects quickly and effectively.
We support of customers on a varuety of projects spanning their organization from top-to-bottom and from supplier-to-customer. Our project support usually fall into three categories:
- Supply Chain Management
- Supply Chain Network Analysis
- Strategic Sourcing (Spend Analysis & Category Management)
- Supplier Performance Management
- Manufacturing Operations Management
- Overall Equipement Effectiveness
- Predictive Maintenance
- Reliability Centered Maintenance
- Total Cost of Quality
- Scheudle Adherence
- Daily Variable Cost Management
- Supplier Relationship Management
- Marketing Intelligence
- Customer Lifetime Analysis
- Customer Segmentation
- Call Center
- Warranty & Repair
- New Product Introduction & cannibalization
Typically, these project-based events are provided when a company needs to conduct a scenarios that need a robuts analysis quickly. A robust decision analysis capability formally models a strategic decision(s) or a tactical decisions impacting substantial investments or having significant consequences.
Decision modeling helps the (individual or group) decision maker understand the alternatives, uncertainties, and possible outcomes in depth, to support the most rational decision possible, given the decision maker’s attitude towards risk. The model also helps identify uncertainties that should be reduced before making the decision, and indicates how to reduce them.
Project-based decision analysis better positions the decision(s) maker to make an important decision confidently. The decision maker knows they have explored every aspect of the decision as thoroughly as is practical, given time and budget constraints. They understand which options are most rational, given the information available to them. And the modeling process has helped the decision maker gain the understanding and support of other stakeholders.
Examples of decisions benefitting from formal analysis include Whether to enter a given market, Whether to acquire a business, and Where to locate a facility. Decision analysis routinely discovers aspects of a decision about which the decision maker faces unacceptably high uncertainty. Rigorous analysis determines when it is prudent to incur a small expense to reduce an important uncertainty affecting a decision’s outcome, and how to do so.
Decision analysis can account explicitly for the decision maker’s risk tolerance. And it can include sensitivity analysis, which explores whether and how the optimal decision changes with variations in risk tolerance, perceived likelihoods, and possible outcomes.
In summary, a project-based decision analysis generally includes:
- A model of the decision that quantifies alternatives
- Risk tolerance, uncertainties, and possible outcomes
- Volume of analyses and their results; and sensitivity analysis
The analytical process emphasizes active participation, to cultivate stakeholder support for the decision models and their recommendations.