Infosys’ blog on industry solutions, trends, business process transformation and global implementation in Oracle.

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August 29, 2012

Whether to use 'Oracle Project Resource Management'

Gust post by
Rajan Gupta, Senior Consultant, Infosys


Oracle Project Resource Management (PJRM) is a self-service application in Oracle Enterprise applications and provides a solution to effectively manage resource allocation on projects in project centric organizations.  PJRM has been a buzz word in PPM when Oracle started rolling out PPM solutions to its customers. The effective goal of implementing PJRM application is to find the right people for the right projects at the right time which is ultimately achieved by streamlining the demand and supply of resources in an organization. Project Resource Management considers only labor resources and assignment of those resources at the Project level only (not at task level) and is a not time based application.

Key Features include-

  • Central Resource Repository integrated with HRMS.
    HR resources that are maintained in resource pool of PJRM are only those resources which are eligible based on certain validations defined in Job setup, Org Hierarchy etc. This helps in segregating the resources in an organization based on staffing and scheduling needs.
  • Project Staffing and Scheduling.
    PJRM allows Project Managers (Demand side) to create resource requirements based on Project needs. Staffing Manager (Supply side) can nominate candidate as well as assign candidate by matching resources based on resource availability, job levels and skills set required.
  • Utilization reporting. Utilization reports which include actual and forecast utilization can be built based on resources allocation and capacity. Those can be generated at the organization level as well as resource manager level.

Key Considerations while implementing Project Resource Management

  • PJR should be used in very process centric organizations.  Value out of the application is made out only when processes are followed and data is properly maintained. Resource search of candidates relies on 3 parameters- Resource availability, Skills Set and Job levels.
    • Resource availability is automatically calculated based on calendar setup and resource allocation. However Project Manager should very diligently define hours to be required while creating a resource requirement on the project. Project Resource Management consists of 2 types of resource allocation on projects that are Delivery Assignment and Administrative assignment. Delivery assignments are scheduled allocations on projects however administrative assignment are non-billable and non-work assignment such as Vacation, Sick leave. Maintaining administrative assignments creates an overhead for the stakeholders of the application and stake holders should decide the granularity of information that is useful to them.
    • Job levels define the seniority of users in an organization and skills are pre-defined for each role. Skills set can be added while creating a resource requirement as well as searching resources. Skills set should be an ongoing process and can be accrued quarterly or bi-annually.
  • Segregation of resources eligible for Staffing - Project Resource Management maintains central resource pool that maintains data about resources availability, skill set, resume, address, job, email, work information, location etc. All the resources in an HR organization need not to be defined in resource pool.  This refines the resource search and improve performance of the application.
    Selection of resources based on jobs and organization hierarchy has to be made to refine the structure.
  • Integration between Project Resource Management and Project Management - Out of box functionality in Projects module allows integration between Project resource management and Project Management. Integration can be achieved either by Bottom-up approach as well as Top-down approach. In a top-down approach, resources are allocated on Projects by creating resource assignments on the projects and then assigning those resources at tasks in Project Management. However in a bottom-up approach team roles are created based on task assignments and then are rolled up to a project level role. Though the bottom up approach has been provided, but it is highly recommended not to use bottom up approach. It can be only be used if resource availability and capacity data does not matter to project stakeholders as it create the work schedule based on allocation method (viz. spread curve) and therefore spoils the works schedule while creating a team role based on task assignment  and does not exactly reflects the project or task role required hours. Creating a role from top-down approach is a much cleaner way of resource assignments and provides more flexibility of creating a resource request by assigning resource for either percentage of capacity of calendar or by defining different work pattern for a certain period of time.
  • Integration between Oracle Time and Labor and Project Resource Management - Objectives of the Project resource Management and Oracle time and labor totally different as one captures resource planning and other calculates actual. There is no out of box functionality available which integrates these two modules.
  • Non project centric and small organization - Project Resource Management is not that beneficial for small organizations where there are few projects, non skills based organizations, not much movement of resources across projects or where there are few resources. It is generally used for mid-sized and large-sized organizations.

August 28, 2012

Oracle Big Data Series - Part 1

Relational databases have been the backbone for decades, on which Enterprises have been taking business decisions and basing their strategies. For some that data set's been growing leaps and bounds with their business, and global footprint.Careful examination reveals that we are still talking about strucutred data thus far, while there's been a revolutionary change in the unstructured, semi-structured world of Information management.

To counter this we have seen significant changes in the way traditional relational databases have aligned their services, offering and features bringing transactional processing, Data Warehousing specific functionalities, Clustering approaches to handle the increasing loads and a lot to offer for BI initiatives. Careful examination reveals that we are still talking about strucutred data thus far, while there's been a revolutionary change in the unstructured, semi-structured world of Information management. Data is coming from weblogs, social media, emails, smart meters, sensors, videos, images, machine logs in addition to the increase in volumes of traditional relational databases.

Interesting to note that volumes have gone up by multi-fold encompassing those data sources, the expectations on the cost of ownership, building solutions, and the speed of analytics is inversely proportional:
High Volumes -> Lower Cost of ownership
High Volumes and Variety of Data Sources -> Low Cost and faster solution implementations
High Volumes, frequency and # of data sources -> Higher the speed of analytics expectations (this was quite opposite prior to current times of Big Data)
High Velocity of Data -> Reduced Latency of Analysis/Analytics

The next question can be broken into 2 broad categories:
Q1.1 -> As a business do we understand what data sources are critical, relevant and has the most business value that can be un-earthed?
Q1.2 -> What toolsets do i require/invest that optimizes cost and yet provides me a comprehensive solution to achieve my Enterprise goals from Analytics?

The answer to those questions really boils down to defining the right use-cases as a starting point e.g. as a Automobile Manufacturing organization one would be keen to achieve following:
1. Predict faults during manufacturing to reduce the downstream impacts in assembly, and actionize the resolutions at the point of fault occurences - by trending and analyzing the sensor/shop floor logs
2. Analyzing customer service logs, complaints during vehicle services - identifying patterns of common problems in vehicle components by make/model and co-relating them with Manufacturing log analysis
3. Gauging customer sentiments online - Leveraging Web logs, Twitter, Facebook, Blogs etc to bring out sentiments, dis-satisfaction with vehicle, product, services that can be handled before it spreads among the customer network
4. Post sale analyzing the sensor data that's recevied from the vehicle in operations to predict and warn of faults likely to occur - therby reducing service costs, customer satisfaction and vehicle design improvement during manufacture

Are those 4 the only use-cases that Automobile Manufacturer may think of? Certainly not, however this can be start with high impact on overall revenues and customer satisfaction for the manufacturer if those can be converted into a real solution. One needs a comprehensive solution and portfolio of products that can help achive the end goals here. The key buckets for such a solution must have:
1. Acquire - Diverse set of data types
2. Organize
3. Analyze - Provide Insights, Visualization and Dig out hidden relationships

Oracle's Big Data Appliance, and Oracle Big Data Connectors is one such solution and portfolio of products bundled together to provide an integrated solution. The beauty of Oracle Big Data Appliance comes with fact that the process of Acquire, Organize and Analyze work quite closely with their proven Oracle RDBMS technology and thus gives Enterprises flexibility to cover SQL and NoSQL (Key-Value store databases for unstructured, semi-structured data) within the horizon of their analytical needs.

Next blog in the series will have a closer look at Oracle's Big Data Appliance architecture, and key components built for providing a comprehensive Big Data solution.

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