Demantra - S&OP (Sales & Operational Planning) : Integration Overview - 1

Demantra - S&OP (Sales & Operational Planning)

Sales & Operational Planning module of Demantra has got a complete makeover by Oracle, in Demantra's 7.2 release Oracle launched integrated S&OP module as Supply Chain Planning offering. S&OP module has been integrated with ASCP (Advanced Supply Chain Planning), SNO (Strategic Network Optimization) and IO (Inventory Optimization) of APS suite, along with seamless integration with Oracle EBS R12.0.4.

High Level Data Flow in S&OP:

Data flow in S&OP can vary based on whether ASCP or SNO or Both are used in the process. We will go through one of the possible scenarios here and will then later focus on integration with ASCP & SNO separately.

• Collection of Shipment & Booking history (old DM feature)
• Download History data into Demantra using seeded workflow "EBS Full Download"
• Demand Review:
  
• Generate Forecast - Shipment & Booking
• Generate Consensus Forecast
• Submit Consensus Forecast to Planning applications (SNO/ASCP/IO etc.)
  

• Supply Chain Planning
• Generate Assignment Set(sourcing rules) from SNO Plan based on Consensus Forecast
• Generate Safety Stock plan from IO, using Consensus Forecast and Accuracy
  
• Create ASCP Plan with Assignment Set from SNO, Safety Stocks from IO and Demand Schedule from Demantra - Demand Review process
  
• Make ASCP plan available for S&OP (new check box in ASCP plan options)

• Supply Plan Review
  
• Download Supply Plan names/members into Demantra S&OP using seeded workflow "Load Plan Scenarios"
• Download Supply Plan data using seeded Level Method "Load Scenario Plan Data"
• Exceptions are detected automatically as part of Load data workflow and S&OP users are intimated with Tasks/Alerts
• In case for removal of Exceptions Supply plan needs to be re-launched after making recommended changes, then Supply plan is re-run and re-downloaded into Demantra
• Once Exceptions are handled and are taken care of, then next step is taken

• S&OP Executive Review
• Review Key Performance Indicators (KPIs) as per the S&OP plan/scenarios
  
• Review Supply plan scenarios and Exceptions
  
• S&OP committee finalizes S&OP Plan
  
• Publish the Final Plan and archive it, for future references

We will talk more about Demantra's S&OP integration with EBS/ASCP/SNO in next few blogs.

You can refer to Oracle's documentation on S&OP module available on Oracle Metalink for getting into details. ( Refer to previous post for whereabouts of Demantra http://oracledemantra.blogspot.com/2008/07/demantra-documentation-on-metalink.html)

Demantra Documentation

I have been getting some queries regarding location and where abouts of Demantra documentation, so in this blog I will be putting some details about the same.

Demantra Documents in Metalink:

Oracle has nicely gathered all the user guides and implementation guides related to Demantra at one place "Oracle Demantra Documentation Library" in Metalink. (Doc Id: 443969.1)

The Library contains all the versions starting from latest Demantra 7.2.1 to older ones like Demantra 5.2.

Few of the old basic Demantra documentations are available under 7.0.1 release header:

• Demantra Spectrum 7.0.1
• Demantra Spectrum 7.0.1 Administrator's Guide
• Demantra Spectrum 7.0.1 Consultant's Guide etc..

Another important document, which can be a good starting platform for learning is "Oracle Demantra 7.1 Foundation Implementation Guide", which can be found under header of 7.1 release.


You can easily find out all the relevant documentation on Demantra published and maintained by Oracle here.


Demantra SIG:

Demantra SIG is a part of Oracle's OAUG and has been delivering various knowledge sharing sessions and conferences on regular basis. You can find interesting documents, case studies, and some advanced Demantra documentation at Demantra's SIG group website.

http://demantrasig.oaug.org/knowledgebase.php?page=knowledgebase

Oracle's Demantra Site:

In Oracle's website also some basic information on various modules and Demantra product is available.
http://www.oracle.com/demantra/index.html

R12.1: Service & Spare Parts Planning (SPP)

In this blog I would try to share my exposure on Oracle's new release Service Parts Planning, based on a recent Oracle Webcast.

Oracle's R12.1 APS suite has a new product in offering "Spare/Service Parts Planning", which is focused to answer the need of an advanced, automated, exception based planning application of Service industry. Sectors which can highly benefit from Service Parts Planning are Industrial Manufacturing, Aerospace, High Tech & OEMs. As volume of spares in these sectors is significantly large and forecasting amount of spares to be available at various stocking location in a Service industry supply chain, itself is a painful job. Besides forecasting, safety stocks calculation, and replenishment planning are two more complicated processes in this industry and the complexity of it can be easily imagined considering number of spare parts involved in Services.

Research shows that After-market sales forms more profitable part of business, as compared to profit earned by sales of original equipments. Also the amount of money involved in Service sector of business is huge and thus becomes a potential market to target for improving the current form of supply chain planning system.

Service Supply Chains are more complex as flow of material is not one way,. Spares flow from Suppliers to Warehouses to Service Technicians, while defective parts material flow backward for repair or replacements. In a standard Service supply chain, the complexity if pretty high because of various locations and spare parts volume. This needs an application which can handle forward as well as backward material flow, so that smooth material flow can be achieved.

For company's who have Service as a key contributor and part of their business and it's growing at a fast pace, SPP can be a best of breed solution for all of theirs Service Parts Planning needs.

What SPP has to offer:
1. Forecast accurately with build in Demantra's Forecasting engine
2. Replenish spares based on Single plan model
3. Distribute spares using SPP's plan
4. One single UI to carry out all 3 above processes for improved productivity
5. Forecasting based on Shipments, Spares Usage, and Returns
6. Plan based on Service parts failure rates calculations
7. Integrated with various APS modules like Demantra DM, CP, IO, and ASCP.

Benefits:

• Reduced inventory carrying cost for Spares
• Increased Spares demand fill rates
• Improved Customer Service Levels
  

SPP is available in Oracle's R12.1 APS product release and is completely integrated with EBS R12 and EBS 11i10. It can be implemented along with any APS module or can be even implemented as a stand-alone application. In a stand-alone environment, the SPP product can be easily integrated with other ERPs through APIs and legacy integration.

For more information on product offering and capabilities, review documentation available in Oracle Metalink.

Oracle R12 Online instances

For those who wants to learn and get their hands on Oracle R12 instance, you can easily do it over the Internet. You can register yourself at following portals and can access R12 environments easily.


1. OracleContractors (http://www.oraclecontractors.com/)
2. Solutionbeacon (http://www.solutionbeacon.com/tools_vision.htm)

Demantra: Data Security & User Management

Role based data asssignement and Data security has a lot of importance in Planning arena. Insuring that users have access to information only relevant to thier role, in one hand ensures efficient execution and on other hand it privdes security of information too. Eevn a compromise of a size of an ant in Planning data can lead to an impact on the Execution front of a size of an elephant. Hence the need of having a secure user management functionality is a must to have in all the Planning Solutions.

Demantra application has quite a flexible but strong user based data security system in place. It provides you control to grant access to users based on thier responsbilties and roles. The access control is not only applicable to data but can also be tailored for Menus, Programs and Applications. Using security option provided at User creation level and at Portal access levels, you can easily configure a well protected and secure collaborative planning environment.

Data Secutiry:Data in Demantra is partitioned by Components and users have access to only one Component. Each user is granted access to a part of data of a component. Ex. with two mutualy exclusive components X and Y, user defined in component X, cannt get access to data belonging to Component Y. Every component has an owner, who acts as Administrator for the component and has control on it's data access.
Components are defined to partition data, by Series, Levels, Indexes, UOMs, etc., and controls what you see as a user in the worksheets. Only entities selected in Componenet definition are visible and avaialble for the users of the respective component.

Feature Secutiry:Access to Menu options, programs, applications and modules is restricted based on Permission levels defined for user. It empowers administrator to control access to all the Menus avaialble in Demantra. E.g. A causal user when logs into "Business Modeler" can see only Password change menu option, while a System Manager user, can view most of the administrative options, when he logs into the same application. Menu items available in Collaborator Workbench can be controled at various levels like at USer level, at USer Group level etc.

User Managment:Users within Demantra are created in "Business Modeler" application, using Menu option:"Security > Create/Modify User". You can create user with specific permission levels based on their role. A user can be created with access to only specific set of modules, eg. A Demand Planner user needs to have access to may be only Collaborator Workbench. Unlike Oracle Demand Planning(ODP), you have to just do distribution of data only once for a user. You can grant access based on user's role by selecting only particular level members of a level. E.g. A Sales Representative would like to work only his account and might want to view other few accounts as well. In this scenario, you assign a particular account level member to him with Full Access and you assign other level members of account level, with access Read Only. You can create User Groups for ease of collaboration, alert notifications, and enabling security.

EBS-Demantra integrated environment: In an integrated environment, you can configure SSO(Single Sign On) for Demantra for easy switching to Demantra application from EBS application. Once SSO is setup, users created in Oracle EBS with Demantra responsibilities assigned to them are mirrored automatically in Demantra application. This ensures that if you while working on EBS, click on Demand Management Workbench link to open Demantra Collaborator workbench, then application will directly log you into the Demantra environment. In absence of SSO setup, users see Demantra Log In window, when they try to launch Demantra applications from EBS.

For more detailed explanation and setup understanding on this topic, you should refer to "Implementation guide" of Demantra, available in Oracle Metalink.

Demantra Predictive Trade Planning & Promotion Optimization

Demantra's PTP & TPMO module focuses on Consumer Good industry's requirement for trade promotions and account planning, sales forecasting, and promotions optimizations. The module is build on top of basic Demand Management module and utilizes various components of Demand planning function. Few of the important features can be listed as:

• Lift generation on top of Baseline forecast when engine is run in Promotion Effectiveness (PE) mode
• Promotions Planning & Analysis, with easy scenario wise comparison of expected incremental lift and trade spending
• Promotion optimization, to simulate promotional scenarios for decision making assistance on the basis of ROI, Revenue or Profit targets.

Oracle has already released seeded integration between PTP module with Enterprise One (JD Edwards) and Siebel.

PTP Integration Flow with Enterprise One(E1):

1. Load master data(product and customer hierarchy) with historical sales data from E1
2. Load history of promotions (can come from legacy TPM system)
3. Generate Baseline forecast & Lift by executing Engine in Demantra
4. Create promotion plans and scenarios in Demantra
5. Load future promotion plans/pricing information to E1
6. Process sales orders against new promotions in E1
7. Load actual trade spending from E1 to Demantra
8. Generate volume forecast in Demantra and Submit back to E1

PTP Integration Flow with Siebel: This integration supports two scenarios in which Demantra can be used by a business. First, Promotion planning done inside Siebel with Demantra being executed in back end. Baseline forecast with Lift information is fetched into Siebel on regular basis for usage during planning. Second, Promotion planning being done in either of the systems and results are synchronized on near real time basis.

1. Load data extracts for Product, Account, Promotion, Planning hierarchy with sales and promotion activity details into Demantra from Siebel
2. Generate Forecast with lift in Demantra
3. Load data extracts from Demantra for Baseline Volume Forecast, Lift and Promotions to Siebel.

The objective behind these integrations is to make Demantra's advanced Forecasting technology available to all. Using the best of breed technology for various business processes is the strategy which Oracle is following as a path towards Fusion. With PTP & TPMO module's seeded integrations, customers on JD Edwards(E1) or Siebel can benefit themselves from Demantra's offering with ease.

Forecasting Demand vs Sales

One should understand the fact that Demand forecast is not same as Sales forecast and that by utilizing demand forecast rather than sales forecast for planning inventory level can reduce the risk of losing sales by matching the stock with forecasted demand.

On one hand where sales forecast is critical for any retailer for running their business, to make buying decisions and planning operations, it is also important for financial planning. But when retailers follow sales forecast they are not able to meet the actual demand of their merchandise, since they didn’t had the right inventory to meet the consumer demand resulting in lost sales. Also excess inventory for not required item increases the inventory carrying cost and hence eating out your profit.

Planning done based on sales forecast doesn’t capture effects of stocking, where in case of stock out the incoming demand is not converted into sales. Demand of item also decreases due of improper positioning/display of item in shelf; say a particular model of mobile not displayed in shelf might result in low sales of that model. Also in an instance where a competitor launches a new product with similar attributes or in case where there is an event planned to occur for promoting your market, the demand of your item will be impacted. Hence these factors need to be considered when planning is done and should be reflected in forecasted demand.

Forecasting Demand
Demand forecast is more than sales as it not merely represents relation between product and quantity, but also represents effects of pricing, merchandising, promotions, competitor events and other casual factors. Demand forecast includes input from partners, customers and other stakeholders to consider the effect of events and operations outside your territory of planning.

Promotional events effects the demand to a great extent and thus demand planners must take it’s effect on sales while planning. Also various market scenarios impact the demand curve and hence the product sale, proactive response is required for being prepared with proper inventory to exploit the market conditions.

Forecasting Methodology
-Market response based
Business decisions impact in form of market response should be simulated and studied before actual implementations. Ex effect of price change on demand should be analyzed considering price and demand elasticity. Also the impact of market conditions such as display arrangement, competitive offerings and seasonal demand need to be observed and absorbed in demand forecasting methodology.
-Time series based
Time series methods utilize historic happenings and events for future predictions. Based on business conditions suitable method is selected.
Example:
- Holt’s Method : fmcg or basic or staple merchandise
- Winter’s Method : seasonal merchandise
-Croston’s Method : merchandise with lesser turnover
………… ………..
There are more than ten such methods which best suit a particular condition. All these methods learn from historic similar events and model seasonal variation, trend growth or decay, and lifecycle flow.

Sensing Demand
Since time series uses demand history the best pick for gathering this data is from Point Of Sale which is the best source of actual sales information. Adjustments on sales data should be made for full-filing the effect of loss of sales, by adding those extra quantities which would have got sold if it was in stock. Historical demand and related information should be collected from various reliable sources.

Shaping Demand
With knowledge of impact of various promotional and pricing strategies, you will be able to better make decisions in selecting price and promotions. You can align your business objectives with tactical planning options such as what promotions should be launched, when to launch them, in what price band product should be sold etc. Also with information of promotions plan the inventory stocking should be planned to meet that extra demand of right product, thus minimizing over stocks and stock out conditions.

Demand Driven Planning & Execution
The forecasted demand should be utilized by various stakeholders for further planning and execution purpose, to practically operate the demand plan. Business rules and operations should be enacted on for executing the plan so that the forecasted demand is actually converted into sales. Demand intelligence when not executed into the business will not see any fruits too. On the other hand when the same demand intelligence is utilized by the marketing, manufacturing, suppliers and partners for pricing decisions, promotion tactics, inventory planning and stocking purposes, then this all drives to result into intelligent Sales plan.

Sales & Operational Planning (S&OP)

Sales & Operational Planning

Sales & Operational Planning (in sort S&OP) stands for business process of integrating all the planning entities of an enterprise, an evolved version of it is also termed by industry experts as Integrated Business Planning (IBP) process. IBP process compromises of complete planning cycle in following order, Sales Revenue Planning, Demand Planning, Supply Planning, Profit based Supply/Demand balancing, Management Review. S&OP focuses on balancing of demand & supply with the financial plan supporting it and is a monthly reviewing process. Stakeholders in this process review the data at aggregated level in quantity as well as in amount and it facilitate the in putting the strategic decision plans to execution.

S&OP process involves and/or interacts with following processes:
- Sales Planning
o New Product Planning
o Revenue, Margin & Profitability planning
o Enterprise Goals
- Demand Planning
o Sensing Demand
o Forecasting Demand
o Demand Collaboration(sales, marketing and operations)
o Shaping Demand(events, promotions, causal factors etc)
o Consensus Forecasting
- Supply Planning
o Capacity Planning(supplier, resource)
o Inventory Planning(Safety stocks, postponements)
o Material Planning
- Demand/Supply Balancing
o What if Analysis - simulations
o Collaboration(internal as well as external)
o Constraint based planning
- Review
o Key Performance Indicators(KPI) measurements
o Plan vs Actual
o Margins
o Inventory Turn
o Forecast Accuracy
o Exceptions & Alerts

Dashboards in SCM

Got bored of running into summary details of each and every report to get a high level picture ? Ever thought of having a platform where you can have all the information at your finger tips(literally at finger tips), if yes then you should not ignore the power of Dashboards.

The importance of having dashboards in today's growing supply chain is quite clear, as the need of having visibility of data across the chain is required to move towards being a demand driven network. Dashboards can be utilised to provide an accurate high level picture of how well are the components of supply chain performing. It provides a manager a wonderful tool for reviewing the statuses and for remainging updated with execution statstics. Managers can easily grasp the information by just looking at the various graphs and tables, which can be also utilized in thier meetings with higher management.

A well customized dashboard application inline with the user's requirement and role can serve as a daily cutom newspaper for all the updates and happenings.

Importance of Collaborative Planning (CP)

Most of the industries have their various departments managing their shows on their own and for themselves. Manufacturing crew works for a production plan which utilises the available resources to most, with more number of longer batch runs and try to achieve new production records every month. Working in a motor manufacturing industry I have seen closely how one used to focus on efficiently producing maximum numbers and achieving targets set by manufacturing team, which were not most of the time exactly in line with organisation's targets. In similar fashion we used to see around us other departments like marketing, sales, supply chain working in their own island of comfort, remaining untouched from other

Going solo is not a workable solution in today's work environment, one need to have proper communication channel and portal for sharing information, exchanging point of views and reaching to a consensus plan. All the latest application providers today have this agenda in mind and thus most of them support collaboration.

An online collaborative work environment can be utilised for communication, alerts management and in decision makings. It in one hand where brings visibility to the organization, on the other hand the results of such an environment returns in form of increased profits, sales and service level.

Oracle's Oracle Collaborative planning module which is part of their APS offerings, has capabilities for internal as well as external collaboration. Internal collaboration provides multiple enterprise planning environment, where planning time can be reduced and pro-active actions can be taken during plans execution. External collaboration with suppliers provide information regarding incoming supplies plan, utilising which supply chain plans can be created. Two-way collaboration is beneficial to both the parties, as they with empowering information are in better state of managing operations.

http://www.oracle.com/applications/planning/SCC.html

Oracle's APS product offering R12.1

Oracle's APS product offering R12.1

Oracle unveiled recently set of new products/modules under it's Advanced Planning Suite portfolio. The list now compromises of following modules:
Existing:
1. Advanced Supply Chain Planning (ASCP)
2. Demand Planning- Demantra
3. Collaborative Planning (CP)
4. Global Order Promising (GOP)
5. Inventory Optimization (IO)
New:
6. Manufacturing Operations Centre
7. Advanced Planning Command Center
8. Service Parts Planning (SRP)
9. Demand Signal Repository (DSR)

We will get into details of each of them in later blogs, keep watching this space. :)

Demantra 7.2.1 Release

Oracle released another major Demantra release recently, integrating the Israeli product more with existing acquisitions and new product releases. This release clearly indicates that going forward Demantra will be a core part of APS suite in Fusion, with quite a few major integrations already in market. Demantra's first integration release was with Demantra Demand Management module, Oracle EBS 11i suite and Enterprise One, this was followed up with Demantra's 7.2 release which was Demantra's S&OP module integration with EBS R12.

With the release of 7.2.1 version, Demantra product under Oracle umbrella has been integrated tightly with various best-of-breed technologies. As of today following integrations are available:

Oracle Demantra Release 7.1.1
1. Inbound integration of Demand Management module(+AFDM module) with EBS 11i & Enterprise One
2. Outbound integration of DM (+AFDM) with ASCP, IO, SNO & PS

Oracle Demantra Release 7.2.0
1. Inbound integration of Demand Management module(+AFDM module) with EBS R12
2. Inbound integration of S&OP module(+AFDM module) with EBS R12
3. Outbound integration of S&OP with ASCP, IO & SNO.
4. Integration of PTP module with Enterprise One (JD Edwards)

Oracle Demantra Release 7.2.1
1. Integration of Demantra PTP and TPMO with Siebel TPM

This Oracle release(Demantra 7.2.1) empowers Siebel's Trade Promotion Management offering with Demantra's Promotion intelligence and optimization capabilities. The packaged integration comes with set of seeded hierarchy/levels, interfaces, worksheets and workflows to support the data load from/into Siebel/Demantra.

Besides above, Demantra has been integrated with Demand Signal Repository(DSR), one of the latest release of Oracle's Advanced Planning Suite product. Also Demantra product features for forecasting the demand of spare parts in another new APS release called Service Parts Planning module (SRP).

Demantra 7.2 New Features

Oracle Demantra 7.2 release from Demantra product prospective came up with few new features to empower the application users with more robust demand planning platform. Following features are new in Demantra 7.2 for all the existing customers:
1. Support for multiple forecast streams: With this release Oracle has overcomed the missing ability of support for generating and managing multiple forecast in Demantra product. This has been developed using Engine profile options and system of forecast versioning. You can now create more than one forecast based on different historical data, like Forecast based on Shipment history, Forecast based on Booking history, Forecast based on Customer POS, etc.
Setting up multiple forecast generation is pretty straight forward, one just needs to define separate engine profiles with "Quantity from" parameter pointing to different history data. One can view and analyse these multiple forecasts generated by the engine, in worksheet as usual and can utilise forecasted booking trends to compare with forecasted shipment trends. This feature has for sure added a missing card into the pack of capabilities offered by Demantra product.
2. Enhanced Engine Performance: Demantra's Analytical engine, often referred as heart of the Demantra Suite has been improved by cutting down the processing time. Unlike older version, for combinations which have been forecasted already in previous runs existing branch allocation will be used now on. This cuts down the engine run time, as there are only few new combinations and thus allocation of branch happens only for them. Besides this, with few other changes has been done on engine side, to enhance Engine performance.
3. Enahnced Worksheet usability: You can now create series with "No Summary" option, thus users don't see any irrelevant numbers as Summary for each of the series. This takes off the compulsion of having a summary function even for Series with data, which doesn't have any significance at Summary level, e.g. Date type series, Approval series etc.

Oracle Demantra: Seeded EBS-DM integration data flow

Oracle's seeded Demantra integration with Demantra's Demand Management module can be utilized with ease to empower an organization with a collaborative, web based, integrated demand planning environment.

In EBS-DM integrated environment, one can start the process of demand planning, with responsibility "Demand Management System Administrator" .

The process starts with Collection of master/transactional data (item, location & sales) from EBS and ends with publishing back consensus forecast to Oracle supply chain planning application. Demand Administrator logs into the Demantra responsibility and starts the Collection program, downloads the master and historical data into Demantra application using seeded workflows, kicks off a workflow to execute the analytical engine in batch mode, makes manual adjustments/overrides on forecast with information like causal factors and promotions and finally runs another workflow to upload the forecast back into APS/MRP.

Demand planning using Demantra Demand Management application compromises of following high level process steps:

• Collection of Dimensional, historical, pricing, costing and other reference data
• Validate & Modify data
• Generate Baseline Forecast
• Consolidate Baseline, Simulation and manual forecasts
• Upload Final Forecast to ASCP/SNO/IO/MRP
• Archive Monthly Forecast