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

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May 28, 2009

Finally "Make-to-Order" Solution from Oracle for Process Manufacturer !!!

With much awaited R12.1.1, which was released in early May 2009, Oracle has finally introduced full fledged “Make-to-Order” solution for process manufacturer as part of their OPM suite enhancement.

Let’s go bit in history before we discuss about the solution. We all know, In Discrete Manufacturing “Make-to-Order (MTO)” is available for long time, but in Process Manufacturing, things are different. Process manufactures who had implemented OPM or the ones, who were impressed with other features of OPM and were looking for implementation, were surprised at non-availability of MTO solution. This was a long awaited pain point which was finally addressed, though partially, with release of 11.5.10. With this release, it was possible to reserve production against sales order, but still demand was not driving the production, the core philosophy of MTO. Same functionality continued with R12 flavors, until R12.1.1 released with significant improvement in this area.

 R12.1.1 provides the ability to create a Batch or an FPO in response to a Sales Order Line. The Batch / FPO supply can then be reserved against the driving sales order lines. It also provides the ability to send notifications to the Customer Service Representative regarding Batch Creation and its linkage with Sales Order, and hence facilitates them to relay information to the customer such as Planned / Actual start dates, Planned Completion dates, Yield lot numbers etc.

Setup to enable MTO functionality is easy. All you have to do is define “Make-to-Order” Rules for process items & Enable workflow for notification, and you are done!!

How it works? Simple.. If you are creating sales order for MTO Process item, you will have to run one Concurrent request, which will create corresponding Production Batch & link it to Sales Order Line. System will also send the notification to CSR, depending on the setup. Item reservation can also be viewed through “Item Reservation window” where Sales Order & Production Batch detail can be queried.

Oracle is also planning to introduce “Attribute Based Manufacturing”, which will allow process manufacturer to use “Oracle Configurator”, and hence provide more options to customer at the time of ordering. But, till that time, they can enjoy immediate benefit of MTO functionality.

May 18, 2009

CDI – Critical Path to Trading Community Dynamics

Mergers and Acquisitions activity is getting increasingly common and challenging in current business environment.  These dynamics in the trading community (Customers, Suppliers...etc) of an enterprise needs to be effectively managed. Any inflexibility in administering the dynamics would increase the risk exposure, loss of opportunity, lack of insight into customers, and revenue leakage. In cases where an enterprise is part of Merger or acquisition activity, lack of proper CDI strategy for any of the participant enterprises would make realization of intended ROI difficult. Read through this blog for more information.

M&A has become the invaluable business strategies for industries implementing Master Data Management (MDM for Customers, products, suppliers etc).

When a company sees an opportunity to acquire another company, it basically looks at improving the customer base and to increase its own products and services.  The result of these acquisitions is the impact on customer model. Once acquired, there should be synergy in the customer bases between the acquired company and acquiring company.

 For any company, acquisitions are challenging but are necessary for companies to improve their planning process, to provide a customer-focused experience to their customer leading to everlasting customer loyalty, trust, reaping the benefits of M&As. What is important for companies after they acquire new business is to retain their customers, their staff and also ensure they are motivated and positive.

The same is the case when a company is merged with another company, the two customer models get merged and a decision is taken which customer model survives during the merge process and which ones will be retired after the merge process.  Again, there will be lot more pressing problems during merging as well. These acquisitions and merging should be timed well enough, consolidation of disparate systems should be done but it shouldn’t disrupt the existing business processes that are critical to revenue generation.

Most Communication service provider industries fall a victim to M&A activities. These industries are moving from LOB-centric product view to Customer View. What it means is –It is quite common these days, when businesses (like the communication industries) merge together, they keep adding more products to their shelf, by doing so they need to provide support for sales and service of the product. This further leads to maintaining their customer information in one central repository and their inability to provide a single global view to the external world.

In order to provide a single blended view to the external world, enterprises need to adopt the best practices leveraging on Oracle CDH which is an effective CDI tool to manage trading community dynamics that would help them in realizing success.

May 11, 2009

Real Time Business Intelligence

Traditional BI deployments result in a time lag between the time data is entered in a transactional system and the time at which this data is available to the analytical systems for reporting & analysis. This time lag is dependent on the data extraction process (ETL) to extract, transform & load the data warehouse, aggregate and present the data in the form of reports, dashboards and alerts to the end user. The architecture of the BI platform deployed and the business requirements of an organization mandate the schedule of data extraction processes. For a typical manufacturing organization having an ERP system, to capture transactional data the ETL processes are generally scheduled to run on a fortnightly, weekly or daily basis. The complexity of the KPI’s measured through the reports governs the time spent on data aggregation and presentation.

However, with constantly changing market dynamics, today the decision makers and analysts want to monitor and analyze the performance of their business on the latest available data i.e. on a near-real-time basis. This means that a Real-Time BI solution should be able to deliver information just-in-time when required by the user; much faster than normal BI platforms.

Industry Requirements

Real-time Business Intelligence is required by event-driven enterprises where the action to be taken by the business user is dependent on the latest data. Some of the industries where Real-Time BI solutions are required include:

  • Financial Services - to monitor Credit Card frauds and Risk Management (market, credit, ops)        
  • Retail - for Price Optimization, stock replenishment & inventory management
  • Consumer Products - to gain insight into sales promotion effectiveness
  • Telecommunications - to report customer balances

Apart from the above mentioned niche areas there is a growing need for few metrics to be reported on a real-time basis in the traditional manufacturing and distribution organizations. These metrics include the latest updated customers, suppliers, orders, quotes etc.

Oracle's Solutions for Real-Time BI Reporting

Oracle provides Oracle Data Integrator (ODI) to integrate data from various heterogeneous data sources and perform integration in real time. ODI is an E-LT (Extract, Load & Transform) tool and part of Oracle's Fusion Middle ware product suite. Real-time data integration is possible through ODI's Changed Data Capture (CDC) feature. ODI utilizes a set of out-of-the-box Journalizing Knowledge Modules to monitor the data sources and capture any new/modified data and makes the new data available for analysis through the already defined data integration mappings. This helps in minimizing the data load time as only new/ changed records are loaded. The data integration process is started automatically once the changed records reach a predefined limit or after a predefined time limit is elapsed, and thus, provides data from different sources to be analyzed on a real-time basis.

Similarly for Oracle BI Applications, Siebel OLTP change capture techniques are embedded into DAC (Data warehouse Administration Console) which helps in providing near Real-time reporting on some of the Seibel CRM metrics.


Including Real-time Metrics in existing BI deployments

For existing BI deployments, real-time data analysis can be achieved by minimizing the time consumption in ETL processes or customizing BI platforms to efficiently query required data directly from the transactional system.

Apart from using faster processors, one of the approaches to optimize ETL process for better performance is to simplify the data transformations. However, most of the transformations cannot be simplified because of data cleansing, aggregation and reporting requirements. The analysts need to identify the specific metrics where real-time data would actually impact the business users in making decisions and carrying out their responsibilities. The transformation of data from the source system to the warehouse could be simplified by splitting the mappings affecting the identified metrics from existing complex mappings and minimizing cleansing & aggregation processes for these mappings. Incremental load through these bifurcated mappings could then be scheduled on intra-day basis to achieve near real-time BI. This approach would be most successful when there are strict guidelines which restrict the data entry at the source system to be clean.

Another approach to Real-Time BI is to query data directly from the transactional system databases. However, most of the transactional systems use fully normalized relational schema (e.g. Entity Relationship schema) in their database which are efficient in reducing data redundancy and optimizing data updates but not suitable for analytic purposes to query data for historical analysis. This presents the need for data extraction to dimensional schemas in the warehouse for analysis of data from transactional system database. To report some of the metrics on real-time basis like new customers, suppliers or orders, the BI metadata layer could source the required selective data directly from the OLTP database by-passing the ETL process . This entails very specific queries to return selective data without any historical analysis. These metrics could then be embedded as a separate set of measures along with the regular BI application leading to a near real-time BI reporting.

This blog has inputs from Sumit Sharma who is an Associate Consultant with the Oracle Business Intelligence Practice at Infosys. His areas of interest include Packaged BI Apps and Financial Analytics.

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