2009 Readers' Choice Survey: Trade Promotion Management

2009 Readers' Choice Survey: Trade Promotion Management Alliston Ackerman, Kara Romanow and Alarice Padilla

It is generally estimated that the average consumer goods company spends 20 percent of revenue on trade promotions, yet many companies are still unsure of their effectiveness or value. In an April 2008 article, Lora Cecere, vice president, Consumer Products, AMR Research, reported that only 54 percent of trade promotions would be evaluated in 2008. "Why? There is usually a disincentive to report and, as a result, companies do not force discipline in the process," she stated. Gartner's Research Vice President, Industry Advisory Services - Manufacturing, Dale Hagemeyer, adds that while the business case for deploying Trade Promotion Management (TPM) is strong, obstacles lie in defining new processes and change management. Findings from aCGT research report ("Trade Promotion Optimization") supported this opinion: 56 percent of those surveyed said that change management was the single largest hurdle to deploying a solution. SMB Market: Oracle "This [Oracle Demantra] gives us the beginning impetus to understand where our peaks and valleys are, where we can optimize promotions and where we can increase revenues. Several hundred people now have a single unified view into what trade promotions are doing, and this leads to better reporting, better visibility and better accountability overall." -- Mitch Margolis, CIO, NBTY Inc ............................ .................. Read complete article @http://www.consumergoods.com/ME2/dirmod.asp?sid=234FFCB1E8DF4FACBAFF60DFFD8AD37C&nm=&type=MultiPublishing&mod=PublishingTitles&mid=A533BDC6582947448BBFA37BFF6394FF&tier=4&id=7D4119A515B943B5BE2CE28DBE8F2C2F

Trade Promotions Management & Demantra's PTP module

Trade Promotions Planning & Management

Promotions and marketing ads have good impact on amount of sales happening at stores. Ads all around builds up the consumer’s buying intention towards things they want from things they need. Thus promotions heavily contribute towards an increase in sales and raising needs for stores supplies to be planned accurately and precisely. Also where about of carrying out promotions needs to be planned carefully to ensure that end consumer gets benefitted, as well as the retailer and manufacturer.
Manufactures use their marketing funds for promotions execution in collaboration with retailers. The process of planning a promotion, analyzing it’s profitability, reviewing effect on sales & spending, and settling down the promotional allowance with retailer is a complex process. Good amount of money and time is spend towards the whole process working on Legacy applications like Excel sheet. Industry experts have recognized that having a Trade Promotion management application in place can widely influence the business, by improving the profitability of promotions and synchronizing planned volume with operations.
Fig. 1.1 Example of typical promotions

Oracle Demantra PTP offering:
Oracle Demantra’s solution for Trade promotions management needs is offered in module:
- Demantra Predictive Trade Planning (PTP)
->Option: Trade Promotion Management Optimizer (TPMO)
->Option: Deduction Settlement Management (DSM) (not covered in this discussion) Trade Promotions management is carried out in top-down fashion on Financial budgeting part & bottom-top approach on promotions planning part. It involves various activities which are readily supported by Oracle Demantra’s PTP module.

What Demantra Offers specially to Promotions Planning arena:
- Manage all promotions, accounts, trade spending collaboratively
- Generate separate Incremental Forecast broken down to Lift, Cannibalization, and Pre/Post effects.
- Simulate & Optimize promotions in a sandbox environment
- Integrated with Seibel & JD Edwards application

Quotas & Fund Management:
Funds are allocated to promotions and are allocated downwards. Demantra gives you a standard set of promotion funds like, Brand Development fund, Market Development Fund and Slotting Funds. Senior management enters base rate, development rate and fixed rates for BDFs & MDFs, they also key in Quota details in the system.
Demantra provides seeded worksheet for Quotas & Fund Management, which involves providing entry sheets point for senior management and review sheets for sales reps. Sales reps can easily view funds available against their sales quota at detailed level of each brand and promotion group.

Volume Tracking:
Planned volume tracking can be done with ease, using Demantra worksheet with views to show base and incremental volume, historical shipments and current year plans. This empowers planners to monitor and track account volumes, which are finally communicated to Operations. Funds planning is an integral part of Volume tracking, as based on planned volume decisions are made on budgets and spending for allowances and deals.

Planning Promotions:
Newly created promotion has “Unplanned” status and has no impact on funds or forecast. Once this promotion’s status is changed to “Planned” for usage in forecasting, it impacts the system. Planned promotions cost is taken out from the available fund balance and Engine when run, generates baseline and lift for it. System also calculates measures like profit for manufacturer and retailers, fund balance etc. which are later used for Cost Benefit reviews.
After the review, you can approve the promotion and status changes to “Approved”. Next, once a firm agreement is reached between retailer and manufacturer, you change the status to “Committed”.
Committed promotions are recognized by a batch process and are reflected in projections.
After the execution of promotion and payment to retailer done, status is changed to “Paid” and later to “Closed.

Fig. 1.2 Promotion Life cycle: Status Changes

Promotion Planning Environment:
Promotion planning environment empowers you to analyze historical and new planned promotions. You can create new promotions, see their impact on sales, spending and profitability, while reviewing corresponding sales quota.
Demantra provides standard worksheets like “Planning Environment” & “Promotion Comparison”, which serves as the platform for various activities:
- Create new promotion
- Modify existing promotion
- Compare promotions
- Delete promotions
Activity browser in the worksheets gives you a visual of events calendar, showing events hierarchy and their planned execution period.

Promotion Optimization:
Planning environment worksheet offers optimization feature, using which you can optimize your planned promotions. You can select optimization rules from Maximizing Revenue, Maximizing Profit or Maximizing Units for getting an optimized promotion suggestion. After running optimization you can review the optimized promotions proposed in “Optimization Comparison” worksheet. Later, you can accept the optimization results, which will in turn copy the optimized promotion definition into the original promotion.
Next you change the promotion status to Planned, so that it can be used in your current plan.

Post Promotion Review:
Once the promotion is executed by the retailer and actual sales figure arrive, you can evaluate promotion’s effect. You can review the planned vs. actual for promotions using worksheet “Promotion Evaluation”. This worksheet has multiple views, Event Projection, Event Actuals, Projected sales vs. Actuals, Projected Profit vs. Actuals and Lift decomposition. Lift decomposition breaks down the Lift calculated by engine into promotional effects like cannibalization, pre and post effects.
This review helps you in evaluating the performance of the executed promotion and reveals true profitability of promotion.
Demantra also provides more detailed review worksheets for your past promotions, “Promotion Evaluation – Details” and “Scenario Evaluation”

Typical high level Promotion Flow in Demantra:
1. Load historical promotions
2. Run Engine in Promotion Effectiveness mode
3. Create new promotions in Demantra Promotion Planning environment
4. Run Simulation for newly created promotion
5. Analyze promotion details and it’s impact
6. Approve promotion

.............will be putting details of the promotions planning flow in upcoming blogs soon.

"Forecasting accurately in Uncertain Times"

How to Forecast Accurately in Uncertain Times

Publish at Scribd or explore others: Business Planning Business & Legal marketing planning

Supply Demand Chain Exec: Article on Next-Generation Sales and Operations Planning

Next-Generation Sales and Operations Planning: Tracking the Evolution from Tactical to Strategic Operational Excellence

A look at how progressive companies are taking a strategic, best practices-based approach to S&OP to enhance operations with increased visibility, reduction of costs andNext-Generation Sales and Operations Planning: Tracking the Evolution from Tactical to Strategic Operational Excellence improved business performance.

By Fred Baumann

The concept of sales and operations planning (S&OP) has been around for decades, primarily as a collaborative supply chain planning process designed to drive more accurate demand forecasts and align that demand with production capabilities to ensure timely fulfillment of customer orders. Many manufacturers still adhere to that view. Today, however, as companies face increased global competition and supply chain challenges, along with rising transportation costs and volatile economic and market conditions, a transformation of S&OP is occurring. Many industry-leading manufacturers — as well as consumer goods distributors and their retail partners — have been working towards elevating their S&OP processes to an enterprise-wide global scale in order to enhance supply chain visibility, reduce costs and achieve more integrated business planning and management. As a result, businesses of all types and sizes are now discovering how this next generation of S&OP can actually become a mission-critical element of an integrated business management strategy.

.................... Read the complete article @ "http://www.sdcexec.com/web/online/Demand-Management-Trends/Next-Generation-Sales-and-Operations-Planning--Tracking-the-Evolution-from-Tactical-to-Strategic-Operational-Excellence/22$10881 "

IT SHOW CASE Article on Next Generation demand planning

Next generation demand planning

"A strategic approach to profitability explained by Infor's Andrew Kinder, director, product marketing SCM

Monday, 22 December 2008

A decade ago, thanks to the increase in computing power, companies began to improve the efficiency of their supply chain by identifying trends in data. The concept of Demand Planning and Forecasting enabled retailers, distributors, and manufacturers to accurately forecast the demand for a particular product during a given time period. Retailers could tell manufacturers (and often the other way around) who could then tell suppliers how much of a product was required to meet anticipated demand. This improved service levels, while reducing unused inventory and ensured stock was kept to a minimum.

This was fine ten years ago, when margins were healthier and the pressure of competition from half way around the globe was not as intense. Times have changed and competition is heating up.  Pricing pressures are now eroding margins and companies are looking for efficiencies throughout their organisations...................................................Read the complete article "http://www.itshowcase.co.uk/News/2008-12-22/Next-generation-demand-planning"

Basics of Demand Forecasting

SK's Chpt 04 Demand Forecasting

Publish at Scribd or explore others: Academic Work demand Methods

Demantra: Analyical Engine - A deeper look - Part2

Analytical Engine's Demand planning(DP) mode run comprises of Prepossessing stage, followed by model application & testing stage. In Promotion Effectiveness(PE) mode run of engine, various promotional CFs are prepared and used before Forecast phase starts. 

Forecast Phase of Engine Run:

Pre-processing Stage:

1. Treatment of missing values.

2. Detection of intermittency.

3. Preliminary outlier and regime change detection.

4. Removal of obvious (gross) outliers.

5. Data transformation for use in specific models.

Model application & Testing Stage:

1. Checking that the number of data points exceeds at least by two the number of causal factors. This is done to ensure that, No over-fitting occurs and coefficients for all causal factors can be determined.

2. Estimation. Statistical algorithms, are implemented to data and their parameters are calculated.

3. Fit and Residuals calculation. Fit is calculated by applying an estimated model to the historical period. It reflects the ability of the model to reproduce the actual series. The deviation of fit from the actual forms the residual series. The variance of residual, along with complexity (number of estimated parameters) is utilized to compute the weights for model averaging.

4. To check the ability of a model to mimic the actual series, a Fit validation is performed, provided the nableFitValidation flag is on.In Fit validation the residuals undergo a battery of statistical tests.Forecast performs identical calculation to Fit, only for the future period, lead.

5. To perform Forecast validation, both the parameter EnableForecastValidation and the variable ValidFit have to be “True”. This is because if a model reached this stage with invalid fit, it must be running at the highest forecast level, and at this level forecast validation is disabled, allowing a somewhat more liberal treatment of models. In Forecast validation models undergo three tests:

• A test for an unusual zigzag-type jump

more details on Demantra's Engine can be found in Oracle Metalink's Documentation library for Demantra.

Demantra: Analytical Engine - A deeper look - Part1

Through this post, I would like to share some of findings about how Demantra's analytical engine works. The post is based on Demantra's documents created by Oracle and are available in Oracle Metalink for a detailed study. 

 What is Forecasting

Forecasting empowers one to predict the futuristic tendencies of supply chain, influenced by seasonal and other predictable factors. The result of forecast is a projected curve that has been smoothed to show tendencies and de-emphasize the exceptional variations.

Demantra engine is capable of multidimensional forecasting with mixed modeling techniques. It has been designed to be robust enough for handling large scale installations. It is capable of modeling hundreds of thousands of data sets with various data patterns.

Modeling is performed according to forecast tree, in which each node in the tree is defined by an item-location combination in the Enterprise Data model. Engine tries to generate forecast at lowest level of item-location combination, but in situations where due of data insufficiency's , it is unable to generate a good forecast, then it traverses the Forecast tree to higher level for generation of forecast at an aggregated level. Forecast generated at higher level is split down to lowest level, using a splitting mechanism called “proport”.

Batch verses Simulation

Engine can be executed in two modes, Batch or Simulation.

Batch Run:

• Traverses a large forecast tress, described in database. Each node in tress represents a time based data series that is subjected to forecast.

• Performs model calculation on a large subset of data series (each node of forecast tree)

• Writes the processed data series to a new forecast table in database.

• Executes a post-process procedure which updates new forecast table

Simulation Run:

• Same steps as above are performed but on a selective subset of data, as chosen by user for “what-if” kind of simulation run.

  
  

  Engine Components

  
  

  Engine consists to two components, Engine manager and Engine server. There is one instance of Engine manager and one or more instances of engine server. The engine server scans a portion of the forecast tree according to the traversal rules, and sends the output to the split mechanism. 
  The engine server receives IDs of tasks from Engine manager, which divides the forecast tree into sub-trees (tasks). The engine manager is responsible for the engine run as a whole.  

  
  

  Based on Engine settings done via Engine Administrator application, Engine managers tries to initiate an engine server on list of machines on network having engine registered and server component installed.

  
  

  Reference “Details of Engine Manager & Server”. (source: Oracle Demantra Engine Guide v.5.2.6)

  
  

  Causal Factors

  
  

  Factors which cause the deviation from a trend, are known as Causal Factors. E.g. a sales promotion, due of it’s result you expect sales to rise. On the other hand, a sales promotion by your competitor can impact your sales negatively, which also becomes a causal factor.

  
  

  Causal factors such as promotions, marketing campaigns and production stoppages are essential components when analyzing demand pattern.

  
  

  Global Causal Factors effect all the nodes of forecast tree, seasonal CFs are normally global.

  
  

  Local CFs can be different for each item-location combination.

  
  

  Event is another word for CF, it can be loaded easily with Code, value and intensity information. Event information is not necessarily required to be loaded in future.

  
  

  
  

  ............to be continued.