Rapid Planning, an addition to Value Chain Planning products suite

In May 2009, during Collaborate 2009 event Oracle provided a preview of it’s new product “Rapid Planning” and they made a timely release of the product by announcing it’s availability on 16th Nov 2009. Rapid planning will benefit customers with it’s quicker, real-time, event driven planning and simulation abilities.

Extending the Information-Driven Value Chain

Leveraging its unique web services and open, standards-based architecture, Oracle Rapid Planning customers can enable reduced supply chain decision-making time with the following capabilities:

Fast, event-driven simultaneous material and capacity planning for rapid scenario analysis and real-time evaluation of supply chain events.

Fast sales and operations planning scenario simulation, integrated with Oracle’s Demantra.

Compatible and complementary capabilities to Oracle Advanced Supply Chain Planning.

Mass edit of supply chain data, enabling customers to conduct ad-hoc, rapid scenario modeling without the need to make changes to the ERP data or transactions.

Predictive and actionable insight via embedded analytics, a spreadsheet-style flexible user-interface, and embedded exceptions and scenario comparisons.

Comprehensive constraint modeling to mimic real-life planner decision making such as alternate bills of material, routings, sources and shipping methods, substitution and lead times.

Multi-enterprise visibility and planning, spanning internal facilities and contract manufacturers.

Multi-planner collaboration and simulation to help speed up the analysis and decision-making process.

Integration with ERP to help quickly translate decisions into actions and release planning recommendations directly to execution without latency.

For complete details about product read the complete release article on Oracle’s site @ http://www.oracle.com/us/corporate/press/040402

Demantra 7.3 comes clean

Oracle’s latest release 7.3 of Demantra Suite comes with an empty schema, unlike previous versions which had demo data. This surely would be a good news for those who have faced problems while cleaning up the demo data in older versions.

DB issue: Business modeler/Engine Admin cannt connect to database

Problem: When trying to open Demantra Business modeler on my local install, started getting error “ORA-01033 ORACLE initialization or shutdown in progress “. Also found that while connecting to Engine Administrator I started getting error “Cann’t connect to database”.

Analysis: Found that even while tnsping to database works, even SQLplus connection to database using Oralce SQLPLUS wouldn’t work. It happens at times when the last DB shutdown didnt happen properly. Database needs to be re-started after shutting down explicitly by using SQL PLUS.

Solution:

Using command prompt,

Login as:
> sqlplus /nolog

Once logged in, use following commands:

SQL> connect / as sysdba
ConnectÚ.
SQL> shutdown abort
Instance ORACLE arrÛtÚe.
SQL> startup nomount
Instance ORACLE lancÚe.

While executing this, I got below error:

Database mounted.

ORA-00600: internal error code, arguments: [kcratr1_lastbwr], [], [], [], [],[], [], []

To further fix this issue, used following commands to re-start database:

SQL> startup mount
ORACLE instance started.

Total System Global Area 1073741824 bytes
Fixed Size 1264916 bytes
Variable Size 264241900 bytes
Database Buffers 801112064 bytes
Redo Buffers 7122944 bytes
Database mounted.
SQL> recover database
Media recovery complete.
SQL> alter database open;

Database altered.

Verify that you are able to login into Database and then into Demantra applications. All set and we are back to action.

Demand Management Process & Demantra’s Solution

Sensing Demand

Demand data should be collected from various possible sources and which can be treated as “BIBLE” for basing your forecast on. Not only actual sales data but other attributes of sales data like promotional causals, holidays, events etc. should be brought in, which justify the variations in demand data. E.g. Sales data collected from various Retailers’ store varies with days on which store is open, promotions which were launched at the store and competition activities near store’s location. So while predicting sales at these stores we should consider all these factors as well.

Demantra implementation offer real-time Demand sensing capabilities, collect demand data and information from various sources like sales orders, shipments, POS data, distribution center data, customer data and marketing data. Demand can be collected inside Demantra on daily or weekly basis as per the requirements.

Shaping Demand

There are items & locations for which sometime sales data is not available, in that case Demand Planners based on their instincts & experience should be able to enter or edit the sales history. Not only history of sales but forecast numbers generated by engine is likely to be edited to consider inputs which have not been captured by the Analytical Engine.

Oracle Demantra Demand Management provides user ability to define override series for each of collected series and also for forecast series. Demantra provides flexibility to create unlimited number of Causal Factors to capture the information which can describe the demand variance and events which occurred. Causal Factors are created and used to ensure that impacts of these factors are taken into consideration by Engine to generate the Forecast numbers.

Collaboration

For any organization the problem of keeping all the stakeholders who represent various verticals like Manufacturing, Marketing, Sales, Retailers, etc. is very common. Today most of the firms are into global markets and have operations and sales happening in various corners of world. Also to become a demand driven supply chain network, the need of having collaboration with all the demand nodes (e.g., customer’s stores) and supply nodes (e.g., raw material supplier’s factory) becomes vital for most of the industries.

The Demantra application provides an easy to use tool for collaborating with all the stake holders using a web based platform. Users can easily collaborate with their internal stakeholders & customers to better predict their forecast. Also all the stakeholders can be informed and kept in loop to reach to final Consensus Forecast number.

Alerts, Exceptions & Notifications

In most of industrial scenarios it becomes difficult to analyze and to figure out the issues like Demand plan crossing the budget limits, import data failures etc. Thus the automated notifications can assist the planners and managers to take up remedy actions. Alerts can be created within Demantra for notifying stakeholders and concerned group of users on Real-time basis. Automated workflows keep all the users notified and updated if there are any exceptions meeting defined conditions.

Value Chain Planning R12.1.1

Oracle released following new set of advanced planning applications under “Value Chain Planning” category in R12.1.1 :

- Oracle Manufacturing Operations Center (MOC)
- Oracle Demand Signal Repository (DSR)
- Oracle Service Parts Planning (SPP)
- Oracle Advanced Planning Command Center (APCC)

Demantra has it’s own set of role to play in above applications, where it is directly integrated with DSR, SPP and APCC. SPP has it’s own inbuild Demantra engine for spare parts forecasting too, while APCC and DSR have an outbound integration from Demantra for forecast and other information.

Demantra 7.3 release – Features Part2 – NPI

7.3 simplifies New Product Introduction cycle, by providing following abilities on worksheet application itself:

- create new product based on existing product
- manage product launch and life cycle end
- cannibalization of existing product

Instead of using Demand Planner > Member/Chaining Management application which was quite complex for end users. This new functionality gives end users a simple and faster way of managing new products introduction.

This function has been provided as a level method on worksheet application. New level method “Create similar product” is context based and is called from existing SKU from which the history shall be copied over to NEW product. Filters of worksheet are used for managing combinations and target location members. The option of setting a launch date and cannibalization% is also provided.

Overall this functionality eases out end users life, who have been using sophisticated Demand planner>Member/chaining management till date.

Demantra 7.3 release – Features Part1

Demantra’s much awaited 7.3 release happened as promised by Oracle in mid of august09. The current release has lot of new functionality changes and enhancements, from simple ones like UI changes to complex ones like CTO offering.

Complete list of documentation is available in Metalink Demantra document library.

(http://oracledemantra.blogspot.com/2008/07/demantra-documentation-on-metalink.html)

Internationalization:

Open the CWB login screen and you would see the first change, which appears as “Language” button at bottom of logon screen.

This release has internationalized the product by supporting, 8 languages (Russian, Japanese, Canadian French, Korean, Spanish, Chinese and Portuguese), by making web based applications available in these languages for end users.

You need to pick the language at time of installation and only one language per install is supported.

Remember that, the language support is targeted for business users and not for implementers, so don’t be surprised when you see your good old Business modeler menu options still showing up in English.

more on 7.3 release features will be posted soon…..

The S&OP Sweet Spot on Manufacturing Executive

The S&OP Sweet Spot on Manufacturing Executive

Abstract: In order to respond quickly to rapidly changing markets, manufacturers are striving to find tools that help them easily link financial plans with operational plans.

During the holidays, cookies are in high demand. Elementary school students are selling baked goods as part of their school fundraisers, and supermarkets and restaurants are upping their orders.

That’s a good thing for Otis Spunkmeyer, a San Leandro, CA-based cookie manufacturer that has seen its revenue nearly double over the past five years. But all of this holiday season activity puts pressure on the company to reconcile sales forecasts with inventory and production operations.

Until about a year ago, Otis Spunkmeyer was using Excel spreadsheets to summarize sales forecasts for the annual budgeting process. That approach limited the number of people who could access the information. In addition, it did not always accurately reflect what the sales force was seeing and could not tie financial forecasts with production. The company was often at risk of making too few or too many cookies.

Complete article ………………..Posted using ShareThis

Waiting for Demantra 7.3 release……

Demantra 7.3 is being expected to be released in a month or two, and we are looking forward for some most sought after features availability in it. While previous few releases were mainly focused on integrating Demantra application with various Oracle products, this release is going to provide more features within Demantra product.

Few key features to look out for could be:

1. Support for CTO (Configure To Order) to derive dependent demand within Demantra. This feature existed in ODP and thus with this feature being available in Demantra, it would surely cut down a major missing functionality

2. Integration with Hyperion for importing Budget data into Demantra, which might come handy in S&OP process.

3. Support for Engine run on Linux will mean you no more need to have Demantra Engine on windows server, but still for Administrative tools like Business modeler etc, you would need windows box.

4. Improved NPI capabilities and worksheet performance

……am waiting to see how 7.3 release would impact product’s demand in market.

S&OP Process – Post1 – New Product Planning process

Step1: New Product planning process

Planning process for new product launch forms the first step of the larger S&OP process. This sub process shall support forecasting demand for the new product being launched. Statistical Quantitative forecast most of the times is based on the fact that future demand will resemble the historical sales. For improved forecast accuracy, qualitative information shall be incorporated into quantitative forecast numbers and a combination of it shall be used as Baseline forecast.

But for a new product with no historical sales data present, one needs to look at their product list for items with similar attributes and characteristics. Once identified historical sales of these existing product shall be mapped as history of the new product. Later a quantitative forecast can be generated out for this new product.

Picture: Product Launch Flow ***

A new product launch can affect the sales of existing products under same product line. Say the recent launch of Apple’s “3G S Iphone” will surely impact the sales of it’s existing old 3G model. (Well in this particular example with Apple reducing the price of old 8 GB model by half might shadow down the effect to some extent). But usually in such cases old product faces lower demand with consumers trying to grab the latest model release. This effect of reduction in the sales volume, sales revenue, or market share of one product as a result of the introduction of a new product by the same produce, is referred as Cannibalization.

Another commonly seen effect is phase out of an existing product, which is getting replaced by a new one. Effect of this process should be incorporated into the baseline forecast calculation.

Setting up New Product Planning process in Demantra:

Oracle Demantra and it’s integration with EBS provides the features required to build the new product planning process on it. Collect new product codes from EBS into Demantra by using NPI setup form on DM system administrator responsibility. Once the new product is visible in Demantra, use the Member Management feature under Demand planner application to create combinations where this new product shall be sold. zero history can also be created for this new product and selected location level member’s combination. This will allow users to pull up these combinations into worksheet and manually enter or adjust the historical sales information. Next step in the process is to map the historical sales from existing combination to new combination, which can be achieved using Chaining Management feature. A Chain is created and executed to copy sales history from existing combinations into the new combination. Once done, the new product at selected locations will have historical sales data, which is utilized by the Analytical Engine for calculating future demand of this new product.

It can be ensured that new product’s demand prediction follows the shape of previous product launches, using Shape modeling feature of Demantra. As many as 8 distinct shapes can be saved and used under this functionality.

………………………next step in S&OP process “Demand Planning/Review”………………………………………

*** picture reference: http://www.winningware.com/images/LaunchFlow.jpg