What s New in SAP Integrated Business Planning 1802

Transcription

1 What s New in SAP Integrated Business Planning 1802 SAP Product & Solution Management February 15, 2018

2 Legal Disclaimer The information in this presentation is confidential and proprietary to SAP and may not be disclosed without the permission of SAP. This presentation is not subject to your license agreement or any other service or subscription agreement with SAP. SAP has no obligations to pursue any course of business outlined in this document or any related presentation, or do develop or release any functionality mentioned therein. This document, or any related presentation and SAP s strategy and future developments, products and or platforms directions and functionality are all subject to change and may be changed by SAP at anytime for any reason without notice. The information in this document is not a commitment, promise or legal obligation to deliver any material, code or functionality. This document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for particular purpose, or non-ínfringement. This document is for informational purposes and may not be incorporated into a contract. SAP assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP s willful misconduct or negligence. All forward-looking statements are subject to various risks and uncertainties that could actual result to differ materially form expectations. Readers are cautioned no to place undue reliance on these forward-looking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions. 2

3 Agenda Solution Updates - SAP Integrated Business Planning 1802 (Released) SAP Best Practices for SAP IBP 1802 Update Documentation Updates Customer Availability Center & Customer Influence Center Information on Upgrades Q&A* * Q&A chat is open for questions throughout the session with experts online to answer 3

4 Analytics and Exception Management Kenton Harman

5 Filter variants for Dashboard Filters It is now possible to save Dashboard filters for reuse First populate the Planning Area and attribute filter values Press the drop-down arrow next to the word Standard The filter can be saved for reuse Note: The dashboard filter only filters chart objects on the dashboard 6

6 Save As option in Analytic charts A new chart can be created based on an existing chart using the Save As option This option is only shown in Edit mode, and only if the chart was previously saved 7

7 Export of chart data to CSV file The chart s data can be exported to a comma delimited file directly from the chart This does not require the use of the Excel add-in The download button is on the chart button bar The file will be downloaded via the browser 8

8 Zoom option on Analytics charts Previously when showing large datasets, the charts would show a limited amount data. The scrollbar or zoom-in/out buttons could be used to show more or less data. The option to Show Data Overview on the chart options tab will automatically display the entire dataset 9

9 Support for null values in chart filters It is now possible to filter for blank or null attribute values The entry will be at the top of every attribute filter 10

10 Support for special characters in charts and dashboards Special characters are now supported in chart and dashboard names and descriptions 11

11 New color palette in charts A new red scale color palette is available in the chart options The light to dark palette is labeled Sequential Five The dark to light palette is labeled Reverse Sequential Five 12

12 IBP External API for key figure data You can now query IBP key figure time series data via external reporting tools The extraction uses the existing IAM communication scenario as security layer In the request, you provide the attributes, key figures, and the filters for the data you would like to query. The service returns the requested data in JSON format. The data can be returned for any time series planning area, version or scenario. Note: The use of the external API as a mass extraction tool is not supported. The API does not replace HCI-DS as an integration technology. 13

13 IBP External API and IAM The IAM communication management framework is used to restrict the APIs as well as the users that can access the data from outside the IBP cloud. For security reasons, it is not possible to access the data using a standard business user from outside the application. Only communication users created via the communication management are allowed to query data within IBP. The odata service is exposed in the SAP_COM_0143 communication scenario so that it can be called from outside SAP Integrated Business Planning. 14

14 IBP Excel Add-In Anna Linden

15 Permission Filters General Information (1) With SAP Integrated Business Planning 1802, permission filters are introduced which also affect the IBP add-in for Microsoft Excel. Example: Write Access for 2 key figures with an exclusion of 2 Customers and 3 Products. 16

16 Permission Filters General Information (2) Please note that the permission filters also need to be maintained in the restrictions of the business role assigned to the users. 17

17 Permission Filters General Information (3) The permission filters follow the known behaviour of visibility filters. One of the key rules is that, regardless of assignment, the resulting access controls is always the UNION of the restrictions defined by all three types of assignments to a user. In other words: if you assign your user SAPALL role, then visibility/permission filters cannot restrict access to your user. Example: The Union of the sets ALL RIGHTS & SUBSET OF ALL RIGHTS is ALL RIGHTS Finally, the editability check happens on SAVE on the Excel UI side. So once you change a value, you need to save in order for excel to provide feedback regarding editability. 18

18 Permission Filters - Cell rejection for key figure editability: Error Message The user will receive the following pop-up in Excel with various options to choose from: Opens a new window with the details of the non editable cells Highlights the cells for which the user has no permission to change the values Closes Pop-Up, no changes are being sent Sends only the valid changes for which the user has the permission to change cells 19

19 Permission Filters - Cell rejection for key figure editability 20

20 Time out check service call Between the IBP Excel add-in and the IBP Backend, there several systems such as Customer Proxy, Load Balancers, WebDispatchers, etc. running. Those systems e.g. proxies have individual timout setting capabilities. The Connection Time Out Check on the IBP Excel add-in helps to identify whether there is any system in between which is closing the connection between the IBP Excel addin and the IBP backend in a shortened time. IBP recommendation for time out settings: 10 Minutes For example, a user has requested data from the backend or tried to save data from the IBP Excel add-in. That starts a request to the IBP backend. In cases where the request takes a longer time to process (e.g. large amounts of data), the user could receive a message such as Underlying connection closed 21

21 New VBA-based Planning View Template The chart now supports the Felxible Time Axis, Totals / Sub-Totals, an average and in general autosizing of columns, etc. Download: SAP Note: Planning View Templates 22

22 Sales & Operations Planning Raghav Jandhyala

23 Key Figure Editability based on process status Control which key figures should be allowed to be edited by which users during a process stage. e.g. lock sales key figures from editing after sales planning step is completed. Assignment of Permission Filters to Process Steps Process Authorizations: Authorizations to View and Edit Process Templates and to manage and run processes. 24

24 Overview Multiple Processes in Gantt Chart View multiple processes in a Gantt chart view that are associated with a Process Template. Compare process improvements across multiple process cycles. Note: With the upcoming 1805 release, the older Process Management App will be discontinued 25

25 Supply Planning Pramod Mane

26 Enhanced UI to configure time-series-based supply planning operators The new S&OP Operator Profiles app allows to configure, display, and delete planning operator profiles for the planning algorithms and auxiliary algorithms used in time-series-based supply planning. The new app replaces planning operator configuration using the Configuration app, which was previously used to configure planning operators of the type S&OP Operator (SCM). The app UI has a new design in comparison to the Configuration app, with algorithm-specific UIs that show only those parameters that need to be set or displayed according to the algorithm type. 27

27 Enhanced UI to configure time-series-based supply planning operators Note the following about upgrading from a lower release: All planning operators created prior to 1802 will still be available in display mode in the Configuration app. Existing planning operators that are assigned to a planning area will be migrated automatically to the new app, where they can be displayed, edited, or deleted. Existing planning operators that are not assigned to a planning area will not be automatically migrated To use the app, the business catalog needs to be assigned to the user s role with the required authorization for PPF object maintenance. 28

28 Time-Aggregation Profiles (Telescopic Planning) Time aggregation has been enabled for the time-series-based supply planning optimizer. You can use it to set different planning granularities over the planning horizon for telescopic planning Time aggregation takes into account that planning for a further future is more uncertain, and thus fine-granular planning in days, for example - buys artificial precision at the expense of longer run-time. A new app has been introduced to manage time aggregation: Time Aggregation Profiles. 29

29 Time-Aggregation Profiles Assumptions during Telescopic Planning Demand: All demand is summed up and set as demand in the first period of aggregated bucket Minimum Key figures: In case minimum key figures (for example, minimum customer demand ) are defined in the lowest time-granularity, they are summed up and set as a minimum key figure value on first period of aggregated bucket. Lead Times: Lead-times are rounded to the aggregated bucket. Customer Transport and Transport: The highest value of the variable (customer) transportation cost rates that have been defined in the lowest granular time-bucket will be set as variable (customer) transportation cost rate in the first period of aggregated bucket. Production Resources: All resource capacities, Capacity Supply Expansion, and minimum capacity usages defined for the lowest granularity are summed up and set as resource capacity, Capacity Supply Expansion, and minimum capacity usage on first period of aggregated bucket. The highest value of the capacity supply expansion cost rate and minimum capacity usage violation cost rate that have been defined in the week will be set as capacity supply expansion and minimum capacity usage violation cost rate on first period of aggregated bucket. Adjusted Values: Only if an adjusted value has been set for each period of the lowest time-granularity, the values are summed up and set as an adjusted value on Monday. 30

30 Time-Aggregation Profiles De-Activated Features for Telescopic Planning The following features are switched off for planning after the aggregation has started: Aggregated constraints Minimum transport supply and minimum transport receipts Fair-share distribution Dynamic periods of supply Periods of maximum coverage These features are still considered for the part of the planning horizon to which the finest planning granularity is applied, for example, for the first three quarters that are planned in monthly periods. 31

31 Coverage Profile Based on Average Demand New Lot-Size Policy 4 is introduced. This needs to be assigned to location-product New attribute : PERIODSAVGDEMAND (Integer) on LOCATIONPRODUCT master data. This attribute specifies the average demand to be considered for calculating the target coverage The static periods of supply based on average demand lot-sizing procedure is considered by the time-series-based supply planning heuristic only. It is ignored by the time-series-based supply planning optimizer. 32

32 Coverage Profile Based on Average Demand 33

33 Late-Demand Fulfillment for Independent Demand Late deliveries are now supported for independent demand as well. Previously, this was only possible for customer demands To enable this function, the following new entities have been introduced: Input Key Figures: Maximum Late-Delivery Periods for Independent Demand (INDEPDEMLATEDELIVMAX) Late-Delivery Cost Rate for Independent Demand (INDEPDEMLATEDELIVCOSTRATE) Output Key Figures: Independent Demand Delivered Late (INDEPDEMDELIVEREDLATE) Average Delivery Delay of Independent Demand (INDEPDEMDELIVEREDLATEAVG) Total Supply for Independent Demand (TOTALINDEPDEMANDSUPPLY) New integer attribute of the LOCATIONPRODUCT master data type: LOCPRODLATEDELIVERYCOSTPOLICY. This attribute is to enable to disable fairshare/tiering functionality in the optimizer. If the value of the attribute is 0 fair-sharing is active. For any other value it is inactive. 34

34 Time-Series-Based Supply Propagation Heuristic New time-series-based supply propagation heuristic planning algorithm is now available. It is a variant of the existing time-series-based supply planning heuristic for infinite planning without shortages. Both planning algorithms create an infinite demand and supply plan, but they take contrasting approaches to insufficient supply: The existing time-series-based supply planning heuristic (infinite without shortages) fulfills all demands, balancing insufficient supply with negative project stock for the location products in question. This allows a planner to see exactly where the shortages originate and take measures to resolve them. The new time-series-based supply propagation heuristic propagates only the available supply downstream through the supply chain and does not fulfill all demands. In this case the planner can see the impact of the supply problem, that is, which customer demands and net demands of which customer products and location products will not be met. Note that since neither heuristic considers finite resource capacities as a limiting constraint, insufficient supply is always caused by other issues such as adjusted key figures or a missing source of supply for a location product. 35

35 Supply Propagation according to Demand Priorities In case of insufficient supply the various demand types are fulfilled according to their priorities, which are: 1. Demand caused by Adjusted and Minimum key figures Adjusted / Minimum will be always fulfilled, even with no supply available Might cause negative Projected Inventory 2. Demand caused by Inventory Correction 3. Independent Demand 4. Dependent Customer Demand 5. Dependent Location Demand and Dependent Production Component Fair share propagation of supply within demand types 4. and 5. fair share can not be guaranteed fair share even not possible in all cases (e.g. in conjunction with lot sizes) Supply quantities are computed based on demand quantities (not based on quotas) Priorities of demand types are pre-defined (not configurable) 36

36 Supply Propagation: Fair Share Related to Demand Quantities Customer 1 / P1 5 = 15 * (10/30) CD: 20 TCR: 15 Supply propagated due to demand (and not due to quotas) DC2 / P1 D: 30 I: 00 N: 30 S: 15 R: 15 DLD: 15 TR: 15 AT: 15 Customer 2 / P1 CD: 40 TCR: = 15 * (20/30) CD: Customer Demand TCR: Tot. Customer Receipts DCD: Depend. Cust. Demand CR: Customer Receipts D: Dependent Demand I: Projected Inventory N: Net Demand S: Supply R: Total Receipts DLD: Dep. Locat. Demand TR: Transport Receipts AT: Adj. Transport 37

37 Supply Propagation Related to Demand Type Priorities Customer X / P1 CD: 10 TCR: 10 Prio 4 Customer Source DC1 / P1 D: 10 I: 00 N: 10 S: R: 05 DLD: 10 TR: 05 Prio 5 DC3 / P1 D: 40 ID: 10 IDS: 10 I: 00 N: 50 S: 30 R: 40 Prio 3 CD: Customer Demand TCR: Tot. Customer Receipts DCD: Depend. Cust. Demand CR: Customer Receipts DC2 / P1 D: 20 I: 00 N: 20 S: R: 15 D: Dependent Demand I: Projected Inventory N: Net Demand S: Supply Transport Sources R: Total Receipts DLD: Dep. Locat. Demand TR: Transport Receipts MT: Min. Transp. Receipts Prio 1 ID: Independent Demand IDS: Indep. Demand Supply 38

38 Supply Propagation Related to Demand Type Priorities DLD: 15 TR: 15 DC1 / P1 D: 15 I: 5 N: 15 S: 15 R: 20 Prio 1 Negative Projected Inventory caused by Adjusted Transports DLD: 30 TR: 20 DC2 / P1 D: 30 I: 0 N: 30 S: 20 R: 20 DLD: 20 TR: 20 AT: 20 Plant A / P1 D: 60 I: -10 N: 60 S: 40 R: 30 DLD: 30 TR: 30 AT: 30 DLD: 20 TR: 0 DC3 / P1 D: 20 I: 0 N: 20 S: 0 R: 0 Prio 5 D: Dependent Demand I: Projected Inventory N: Net Demand S: Supply R: Total Receipts DLD: Dep. Locat. Demand TR: Transport Receipts AT: Adjusted Transport 39

39 Sub-Network Specific Selection With subnetwork-specific segmentation of planning objects, the time-series based planning algorithms (supply planning heuristic, supply propagation heuristic, or supply planning optimizer) read only the key figure data belonging to the subnetworks that a planner has selected for the planning session in the IBP Excel add-in or for a batch run. This data segmentation can significantly speed up the initial loading process and hence the entire batch run or the loading phase of an interactive planning session. To use this feature, the configuration expert has to define master data attributes of the type integer, for example, PLUNITNUM1 and PLUNITNUM2, and assign them to the PLANNINGUNIT master data type. Assign the above attributes to planning area coming from PLANNINGUNIT When the planner runs the planning algorithm, segmentation is performed automatically if master data has been changed or a new planning object has been created since the last planning run. 40

40 Business Network Collaboration Rajwinder Singh

41 Data Sharing Plan Outbound IBP to Ariba Network Optimized message handling for Data Sharing Plan Outbound job to limit number of records transmitted per cxml_productactivitymessage Default limit is 10,000 [Optional] New parameter Max. Records Per Message has been added to override the default limit (highly unlikely) All time buckets of a combination are accommodated in one message 42

42 IBP - Ariba Network Integration Ariba Credentials and Endpoints New app to Manage Ariba Network Credentials and Endpoints Business catalog SAP_CORE_BC_ARB (Ariba Network Integration) Contact the administrator of your Buyer account on Ariba Network for what information should be maintained here 43

43 Shared Data Tracking Change-History-Based Calculations Enable shared data tracking in Data Sharing Plan [IBP 17011] For example, to track the evolution of forecast key figure values that are exchanged with suppliers New parameter to enable Change-History-Based Calculations for the Planning Area 44

44 Shared Data Tracking Change-History-Based Calculations New History dimension is available and can be included in the planning level of the key figure used to track shared data History Attributes Data Sharing Attributes 45

45 Shared Data Tracking Change-History-Based Calculations IBP Excel Add-In can be used to view Supplier Forecast Waterfall History Attributes Data Sharing Attributes For example: Proactive or reactive excess and obsolescence analysis 46

46 Demand Sensing Poorya Farahani

47 New Lag-based Snapshot Concept (in Demand Sensing) With SAP Integrated Business Planning 1802, we introduce a more flexible, simpler and more efficient (in terms of performance) snapshot concept to replace the old change history snapshot concept which is used only in Demand Sensing. Due to the visibility and simplicity of the new lag-based snapshot concept, customers can leverage it not only in Demand Sensing, but also for different other purposes, such as time-based waterfall analysis and alerting. The new snapshot concept significantly reduces the required data volume for Demand Sensing, and creates full visibility over the historical and future snapshot data. Snapshot upload can be done like any other key figure via flat file or HCI. All snapshot records can be viewed in Excel/WebUI and updated when needed without any restriction. New snapshot concept can be directly used instead of the older change-history snapshot key figure in Demand Sensing. New snapshot operator can be used to generate snapshot of any key figure for any sub-set of lags. For example, timebased waterfall analysis can be done by taking snapshot of consensus demand only for lags 0, 3, 6 and comparing against sales/shipments. 48

48 Create a new Lag-Based Snapshot Configuration Using the new Fiori App, Manage Lag-Based Snapshots - create a new lag-based snapshot configuration 49

49 View the Snapshot Results in IBP Excel Here is a view displaying the source keyfigure and the target snapshot keyfigure 50

50 Demand Planning Poorya Farahani

51 New Forecast Algorithms With IBP 1802, two new classes of forecasting algorithms are added to our available forecasting methods of IBP-D. 52

52 New Forecast Algorithms - ARIMA and SARIMA (seasonal ARIMA) models ARIMA models can be thought of as an extension to exponential smoothing algorithms, where the focus of the latter is on describing trend and seasonality in the data, while ARIMA models focus on describing autocorrelations in data. Products have long lifecycles Considerable sales history is available Sales Sudden changes in trends require automatic and rapid adjustments of the forecast OR Long-term correlation between the historical data points can t be observed Dependency between the historical sales and other variables can t be observed OR Data on other demand influencing variables is not available Time IBP offers an automated version of the ARIMA and SARIMA implementation where the system internally does various tests to determine how many times the input time series needs to be differenced in order to come to a stationary time series (parameters d and D), also determines the optimal orders for the AR and MA parts. 53

53 New Forecast Algorithm - Brown s Linear Exponential Smoothing Brown s Linear Exponential Smoothing algorithm is a forecast algorithm that is suitable to forecast time series that contain trend. In that regard it can be viewed as an alternative to double exponential smoothing algorithm. It uses only one smoothing parameter, the alpha, but the algorithm executes the smoothing twice to get to an estimate of the level and the trend. The resulting forecast responds to changes in the trend more rapidly than a forecast calculated by the double exponential smoothing algorithm would do so and it is less sensitive to the initialization of the model. It has an adaptive variation in which the main smoothing coefficient, alpha, is changing from period to period during training as it adapts to new data points. There is no trend dampening option for Brown s Linear Exponential Smoothing. There are no additional details provided in the forecasting log regarding the Brown s linear exponential smoothing algorithm, only the computed error metrics are shown. 55

54 Brown s Linear Exponential Smoothing in IBP Define Forecast Model Alpha Coefficient is a number between 0 and 1 that is used as a multiplier to smooth the level and the trend in the historical data. The larger is the alpha coefficient, the faster is the reaction of the forecast to changes in the data. The typical value range for alpha is 0.05 to 0.5. Adaptive Method - if you select this checkbox, the algorithm continuously recalculates the alpha coefficient based on the delta coefficient you specify, thus smoothing the error values as opposed to the actual demand data. This continuous adjustment allows quicker response to changes in the pattern in the time series. Delta Coefficient is a number between 0 and 1 that is a smoothing parameter that will influence the adjustment of the alpha coefficient. 56

55 Improved Choose Best Logic Using a Test Phase

56 Functionality Prior to IBP 1802 When multiple forecasting steps are contained in the model the system will select the most appropriate one by comparing a model fit error. Model fit error is also called training error. There can be cases when the model fit error is small because the predictive model fits well the historical data, but when the model is used to predict or when it is applied to new data it does poorly. This is called the overfitting phenomena. Overfitting usually occurs when the model is excessively complex relative to the number of observations. 58

57 Improved Logic for Choose Best Forecast Using a Test Phase To avoid overfitting it is a general practice to split the data set into a training and a validation (test or holdout) data set. Usually the 80 / 20 approach is suggested, to validate the predictive models or algorithm on the remaining 20% of data. A robust predictive model is the one that has low training error and low test error Improved logic as of IBP 1802: Configuration option in the Manage Forecast Models app to specify a hold-out or test phase when Choose Best forecast option is used. Forecast algorithms are trained using the sales history without the test phase and generate forecast for test phase Compute error metric for each forecasting algorithm by comparing the predicted sales with actual sales data over the test phase and then select the winning algorithm Forecast with winning algorithm by leveraging all historical data points to re-train the selected forecast model. 59

58 Improved Logic for Choose Best Forecast Using a Test Phase Configuration option in the Manage Forecast Models app to specify a hold-out or test phase when Choose Best forecast option is used. 60

59 Improved usability by supporting Mass assignment of phase-in/out curves Phase-In and Phase-out with user defined curves Assign multiple Reference Products and phase in/out dates You can assign multiple reference products to a new product at the same time. You can navigate from the list of assigned reference products to the details of the individual reference products You can assign phase-in or phase-out dates and phase-in or phase-out curves to several forecast dates at the same time. You can copy the assignment of reference products to several new products 61

60 Inventory Optimization Atul Bhandari

61 SAP IBP for inventory Version-specific Master Data Handling Cyclical Sourcing Fiori enhancements Support for DDMRP 63

62 Supporting Version-Specific Master Data Users can now create versions of data modeling different values and settings for any attribute in any data model Master Data Type, for instance: Create an inventory plan with a version modeling sourcing from vendors only. SOURCETYPE = U for all PRDID_LOCID_SOURCEID combinations in SOUCREPRODUCTION Master Data Type. Create an inventory plan with a version modeling non-stocking customer-facing nodes. Assign STOCKINGNODETYPE = N to product-location combinations in the LOCATIONPRODUCT Master Data Type. All IBP for inventory operators support version-specific master data: Global (Multistage) Inventory Optimization Calculate Target Inventory Components Local (Single-stage) Inventory Optimization Lost Demand Calculation Forecast Error CV Calculation Manage Forecast Calculations - Inventory Optimization (Batch mode only) 64

63 Global Configuration for handling cyclical sourcing (loops) A new Global Configuration Setting can be used for detecting and removing advanced (3 to 6 levels) loops defined in the Source Location Master Data. Parameter Group: INVENTORY Parameter Name: LOOP_HANDLING Parameter Value: LOG or REMOVE Configuration Rules: If the parameter value is set to LOG, then the loops are logged in business logs. If the REMOVE parameter value is provided, then the loops are logged and removed. If any other value different from REMOVE is provided, then logging and removal functionality is invoked. If the global configuration is not configured, then the application just logs the loops. Number of loops reported in business logs is limited up to 100. Type Class Number Message Occurred At Information /IBP/CM_PL_OP 78 Step 1 out of 1 for the job Job 3,024 for operator type IO was scheduled from 11/22/ :29 Information /IBP/CM_PL_OP 300 Execution of job 3024 begins. 11/22/ :29 Information /IBP/IO 14 Started Inventory Optimization Batch Mode with Algorithm type MULTI STAGE IO 11/22/ :29 Information /IBP/IO 16 Started preparation of inventory optimzation call with base period /22/ :30 Warning /IBP/IO 36 Source PRDID 123, LOCID 999, LOCFR 5555 ignored due to bidirectional loop 11/22/ :30 Information /IBP/IO 17 Started inventory optimization algorithm 11/22/ :30 Error /IBP/IO 35 Multiple stage loop detected in the network for PRDID 456, LOCID /22/ :37 Information /IBP/IO 24 Inventory Optimization call unsuccessful and stopped. 11/22/ :37 Information /IBP/CM_PL_OP 280 The responsible application component for this job is : SCM-IBP-INV 11/22/ :38 65

64 Logic for handling cyclical sourcing (loops) 1. Identify one lane to remove from optimizer for each loop. 2. Log ignored lane(s) Logic Step 1: Identify all loops and the lanes and nodes in each loop. Node refers to a product-location combination. Refer to steps below for each loop. Step 2: Identify lane(s) for which the target node has multiple sources of supply. If only one such lane then ignore this lane, otherwise go to Step 3. Step 3: Identify lane(s) after Step 2 for which the source node has multiple target nodes. If only one such lane, then ignore this lane, otherwise go to Step 4. In most of our test cases, Step 3 was sufficient to identify the lane to ignore. Step 4: Identify lane(s) after Step 3 for which the sourcing ratio key figure is the lowest in the current week. If only one such lane, then ignore this lane, otherwise go to Step 5. Step 5: Identify lane after Step 4 for which the sourcing location is most recently added to the data. Ignore this lane. A warning business log message is created that is visible to the user in excel or application logs in web UI. Number of such log entries is limited to 100. Example Lanes AB, BC and CA, where for lane AB, A is the source node and B is the target node. Loop: Lanes AB, BC and CA Additional lanes: DB Node B has multiple sources -> Lane BC Loop: Lanes AB, BC and CA Additional lanes: DB, DC, CG Nodes B, C have multiple sources -> Lanes BC and CA Node C has multiple targets -> Lane BC 66

65 Enhancements to Fiori Supply Chain Network Application Ability to display Key Figures Values by: Currency To ID. Unit of Measure to ID Clear button added to Header bar to support editing of selections. Users can clear selections for: Product ID. Key Figure. Period Type. From/To. 67

66 DDMRP Philosophy - Flow Approach The primary objective of DDMRP is to enable FLOW: end-to-end Supply Chain where the rate of supply is aligned to the rate of demand, through the FLOW is key where demand is volatile (driven by promotions, innovation, shortening product life cycles, competition ) and there are rigidities in supply (long lead-times, large batches, capacity constraints, ) which result in challenges in service, inventory, speed to market, and ultimately cost. FLOW is achieved through a 5-step methodology 1. Determine where in supply network to place buffers 2. Set up Buffer Profiles (master data) and determine sizing of each buffer according to lead times, demand, variability 3. Adjust buffer sizes based on actual lead times and actual and projected demand 4. Generate replenishment orders at decoupling points based on actual demand (consumption-based). Generate orders between decoupling points using classic MRP dependent demand logic 5. Prioritize orders in real time according to actual buffer penetration, and leverage order priorities in executing replenishments (distribution, production, procurement) 68

67 Supporting Demand-Driven MRP (DDMRP) in SAP IBP for inventory SAP IBP for inventory 1802 will support the first two steps of the DDMRP methodology, through the following new capabilities: Strategic inventory positioning operator Buffer levels re-calculation operator Fiori app for decoupling point scenario comparisons view mode A new sample model is introduced in SAP IBP (SAP3B) to support DDMRP inventory planning, separate from the SAP3 sample model and allows users to maintain buffer profiles. Both DDMRP operators Recommend Decoupling Points (Solve) and Calculate DDMRP buffer levels support: Batch mode run in both Web UI Application Jobs and Excel UI apps. Creation of scenarios (in Batch mode). Version-Specific Master Data and Key Figure. Planning Unit-based planning (Sub-Networks planning). The DDMRP operators do not support Excel UI simulation. 69

68 Supporting Demand-Driven MRP (DDMRP) in SAP IBP for inventory Recommend Decoupling Points (Solve) Operator Operator uses heuristics to recommend decoupling points: Identifies critical path for decoupling lead time. Determines if product location is on multiple critical paths and recommends as decoupling point. Outputs from Operator run include: Decoupling points Decoupled lead time Lead Time and Variability categories Buffer levels 70

69 Supporting Demand-Driven MRP (DDMRP) in SAP IBP for inventory Calculate DDMRP buffer levels Operator Operator allows users to load own decoupling point decisions and run scenarios of recommended outputs. Outputs from Operator run include: Decoupling points Decoupled lead time Buffer levels 71

70 Supporting Demand-Driven MRP (DDMRP) in SAP IBP for inventory Fiori App DDMRP Buffer Analysis Introducing Fiori app DDMRP Buffer Analysis to help users analyzing decoupling point scenarios. For scenarios created in Excel UI, users can compare results of scenarios versus baseline for: Decoupled Lead Time. Average On Hand Quantity. Average On Hand Value. The Fiori app include the following: List Manager page listing scenarios and relevant information. A Scenario Landing Page where users can: review Baseline vs Scenario results, filter results by Product, Location, Planning Unit, Time, Currency and Unit of Measure. The Fiori app supports view mode only; scenarios are not editable in the app. 72

71 Supporting Demand-Driven MRP (DDMRP) in SAP IBP for inventory Buffer Profile Master Data Maintenance in Excel 73

72 Practical Implications of DDMRP Support in IBP 1802 As of now, IBP does not fully support DDMRP, it cannot be sold as part of a total solution based on DDMRP IBP for inventory is being made available to partners to build their own 5 step DDMRP solutions within IBP Camelot ITLabs is current integrating their solution with IBP/inventory will be available shortly Demo development underway enablement will be offered Other partners are also moving forward SAP intends to release full 5-step support for DDMRP in IBP going forward, leveraging IBP for response & supply for steps

73 Order-based Planning Andrew Boyle

74 Order Based Planning 1802 Topics Analyze Resource Usage Analyze Supply Usage in Excel (i.e. Supply Pegging in Excel) 76

75 Recap - application Analyze Supply Usage (Existing Functionality) Analysis Supply Usage provides an overview of component supply you are responsible for and how it is used by with respect to primary demands The application provides analytical capabilities such as filtering, grouping, and calculation of totals on any column if applicable. You can navigate to the "Analyze Demand" view for any component supply through which you can analyze the order network for a single primary demand together with the gating factor 77

76 78

77 Application Analyze Supply Usage Resource consumption As a supply planner you want to get an overview of resource consumption and how it is initiated by primary demands The application Analyze Supply Usage supports additional use cases such as Supply for which primary demands is processed on the bottleneck resources Split and aggregation of resource consumption by any demand attribute Competing demands on the short-term horizon 79

78 Application Analyze Supply Usage Resource consumption In addition to the existing filter criteria, you can filter supply by work center. The result set will show all supply element processed on the selected work centers. Furthermore you can restrict the selection to a Future Interval e.g. next calendar week, instead of selecting all supply elements from the past up to a certain horizon. This is very helpful to get the resource consumption for exact interval like a certain day or week. 80

79 81

80 Order Based Planning 1802 Topics Analyze Resource Usage Analyze Supply Usage in Excel (i.e. Supply Pegging in Excel) 82

81 Analyze Supply Usage in Excel (i.e. Supply Pegging in Excel) With Supply Pegging in Excel the user may analyze supply used by primary demands directly in the excel interface at an aggregated level. Example: On a lower level of the supply chain the planner wants to see, how supply quantities for a bottleneck component are used by forecast and sales orders, split up by customer classification (assume forecast is defined on level product location customer classification) Check the distribution of the bottleneck component for distribution center and customer classification In case of shortages analyze demands that are fulfilled by priority rules 83

82 84

83 Analyze Supply Usage in Excel (i.e. Supply Pegging in Excel) Planning Areas SAP7 and SAP74 now include a planning level for ASU (Analyze Supply Usage), configured to a new external data source. The planning areas are also preconfigured to include key figures at lower levels of granularity for supply types Once copied, a planning area may be configured to restrict or include additional attributes of demand and supply such as: Attributes of the Material or other root attributes like Material Description or Material Group Additional attributes from the sales field catalog like Customer Number or Delivery Priority A planner can then choose these attributes and key figures to analyze the bottom-up relationships as desired via the Excel UI. 85

84 Definition of planning level for Analyze Supply Usage (Pegging) in Excel 86

85 87

86 Analyze Supply Usage in Excel (i.e. Supply Pegging in Excel) Example with Deeper level of detail 88

87 SAP Best Practices for SAP IBP 1802 Update Thomas Fiebig

88 SAP Best Practices for SAP Integrated Business Planning V Technical upgrade to SAP Integrated Business Planning 1802 New scope item IBP for response and supply response planning allows for sales order confirmation and adjusting the supply and allocations plan based on short-term changes in demand and supply constraints New scope item IBP Business Network Collaboration supplier commit with SAP Ariba shares a component forecast with suppliers in SAP Ariba and receives committed quantities for further constrained supply planning Two new scope items IBP order-based planning inbound integration with SAP S/4HANA and IBP order-based planning outbound integration with SAP S/4HANA describe the configuration and execution of exchanging order data between SAP S/4HANA On-premise and SAP IBP View Confirmations in Response Planning Supplier forecast in SAP Ariba Supply Chain Collaboration 90

89 IBP for response and supply response planning Process flow Supply and Allocation Planning Product Allocation Supply proposals Review Demands by Priority Run and Check Order Confirmation Run Create and Simulate Scenario Order Confirmation for adjusted allocation Execution on orders Sales Order Confirmations Sales Order Processing Open,Confirmed,Delivered Sales Orders Ranked Demand Sales Order Confirmation Adjusted Allocation Supply Plan Sales Order Confirmations Available-to-Promise Processing Sales Order Confirmations Response Planning SAP IBP Process External Process 91

90 IBP Business Network Collaboration supplier commit with SAP Ariba Process flow Demand Planning Global Demand Plan Demand Sensing Sensed Demand Copy Initial Stock and Unconstrained Forecast Unconstrained Forecast Generate Component Forecast Component Forecast Review Forecast Component Forecast Review & Release Component Forecast Component Forecast Publish Supplier Commits Supplier Committed Forecast Check Alerts Supplier Committed Forecast Analyze Supplier Committed Forecast Supplier Committed Forecast Supply and Allocations Planning Supply Proposals, Product Allocations SAP IBP Process Steps SAP Ariba Process Steps SAP IBP Process 92

91 Unified planning process flow Tactical Frequency: Monthly Horizon: 1-3 years Buckets: Months, Weeks Financial Planning Annual Operating Plan Marketing Planning Marketing Plan Demand Review Consensus Demand Plan Supply Review - Heuristic, Optimizer Constrained Demand Plan Reconciliation Review Constrained Demand Plan Management Business Review Final Consensus Demand Plan Mid-Term Operational Frequency: Weekly Horizon: 1-12 months Buckets: Weeks, Days Sales Planning Sales Forecast Demand Planning Global Demand Plan Inventory Optimization Inventory Plans Supplier Commit with SAP Ariba Committed Forecast Supply and Allocations Planning Supply Proposals. Product Allocations Managed Cases and Exceptions Supply Chain Control Tower Short-Term Operational Frequency: Daily Horizon: 1-12 weeks Buckets: Days Demand Sensing Sensed Demand Response Planning Supply Proposals, Sales Order Confirmations Execution Sales Order Processing Open,Confirmed,Delivered Sales Orders Procurement Purchase Orders Available-to-Promise Processing Sales Order Confirmations Stock Transfer Stock Transfer Requisitions Production Production Orders SAP IBP Process External Process 93

92 Further Enhancements in Foundation Anna Linden

93 Enhancements in Model Configuration New Fiori App Planning Area to display, copy, check, and activate non-sample planning areas. In the Attributes app you can now see the following data: Planning levels the attribute is assigned to Key figures that use the attribute as period weight factor In the Master Data Types app you can now do the following: Navigate to the Planning Areas app See the status of a copy operation in the Last Detailed Log column In the Time Profiles app, you can do the following: Navigate to the Planning Areas app See the status of a copy operation in the Last Detailed Log column 95

94 Change-History-Based Calculations Use change-history-based calculations to perform operations on historical key figure values that you have captured via the change history or the shared data tracking feature in business network collaboration. By tracking and exporting the values of your key figures over time, you can see how your forecasted demand has changed how your supplier's commit has changed how your supplier's component forecast has changed. In the Configuration app, the Planning Area and Details screen now includes the Change-History- Based Calculations checkbox. 96

95 Disaggregation New global configuration parameter KF_UPLOAD_NO_PROPORTIONAL_DISAGG for disaggregation. During data upload with time disaggregation you might not want to consider old values already stored in the database. You can use this parameter to overwrite the default disaggregation behavior. For the same purpose, the Disaggregation DISAGG operator has the new parameter NO_PROPORTIONAL_DISAGG. New parameter set to X, the system will ignore the existing values and the disaggregation modes are overwritten as follows: Proportional if aggregated value is not zero Equal distribution becomes disaggregation mode Equal, unless a period weight factor is defined, in which case the period weight factor is used. 97

96 Data Lifecycle Management - New Application Job Template Purge Key Figure Data Outside Planning Area Planning Horizon to permanently delete key figure data that is outside the planning area's planning horizon 98

97 Mandatory task after upgrade Business users need to familiarize themselves as soon as possible with the new way of configuring and scheduling forecasting without using a planning operator. There is no need for you to change any configuration or business settings immediately after the upgrade to keep things up and running. In the Configuration app, you cannot create new planning operators of the IBPFORECAST type, and you cannot assign such planning operators to new planning areas. Instead, you can use the Manage Forecast Models app to set the parameters and the Statistical Forecasting application job template in the Application Jobs app or in the IBP Excel add-in to run the forecasting. Note that all existing planning operators of the IBPFORECAST type that are assigned to a planning area will be automatically migrated to the new app and will be available as planning profiles. Existing planning operators that are not assigned to a planning area will not be automatically migrated. 99

98 Mandatory task after upgrade S&OP Operator Runs - Old: Warning New: Error It checks that all output and input/output key figures in a version are flagged as versionspecific. If this is not the case, the S&OP operator aborts. Planning Area Activation Check: New set of checks are run when you activate a planning area that includes external planning levels to verify if an external planning level contains the attributes needed, and if the assignment of the reference column is valid. With these new checks, you can detect the incomplete configuration of order-based planning earlier than in the previous releases of IBP. 100

99 Prepare for 1805 As of 1805, the BACKEND and FRONTEND values will be removed for the BUFFERING global configuration parameter. Setting the parameter to TRUE, the default and recommended value, can help improve the performance. We recommend that you set the TRUE value before the upgrade to

100 Documentation Updates Anna Linden

101 New: SAP Cloud Platform Integration Guide Tips and Tricks incl best practices to ensure that your integration projects in SAP Cloud Platform Integration for data services run smoothly. --> Cloud Platform Integration Guide Tips and Tricks Integration projects in SAP Cloud Platform Integration Integrating IBP with Cloud Systems Avoid Mapping Effort by Using Generic Datastores Using a Realistic Test Environment Authorizations for the SAP Business Suite RFC user Overview of Integration Technologies Provided by SAP Cloud Platform Integration for Data Services ABAP Query/ABAP Aggregation Versus Query/Aggregation ABAP Query and Execute Pre-loaded: How to Transport the Generated Report Find Fields in the Source or Target Field List for Mapping 103

102 Customer Influence Program Update John Lopus

103 Customer Influence Our Tool for Product Enhancement Ideas Powered by SAP Innovation Management Global co-operation of customers in the projects via the collaboration site Customer Influence: Search and Vote for improvement requests Submit your own improvement request Comment on improvement requests Follow improvement requests (get notified) Choose your areas of interest to get notification on any projects that might interest you in the future. Collaboration language is English Contribute and Influence 105

104 How it works for customers Integrated Business Planning continuous influence session is now ALWAYS open for your improvement request submission! Logon to Follow the continuous session you want to Influence Submit your improvement request Vote on other good ideas Once idea reaches voting treshold, it is ready for review* Product development reviews ideas Product team informs about results of review Suitable improvement requests are built into an upcoming release Specific for IBP: minimum of 5 company votes is decided review cycle will be twice per year Next review in April 2018 *minimum # of votes can be different in Continuous Sessions (Product Owner s decision) 106

105 Results of Review Cycle Q Improvement ideas submitted as of November 13 based on votes from more than 70 companies 43 of your ideas included in Review phase by SAP product management o 7 Accepted for Development or were already in progress o 2 Merged as duplicate or similar requests o 20 In Review for Portfolio Still being considered for a future release o 6 Not Planned o 8 Still in Review 107

106 Information on Upgrades John Lopus 10 Minutes

107 IBP Release Timeline On-Demand IBP 1802 IBP 1805 IBP 1808 IBP 1811 IBP 1902 IBP Feb Jun Aug Nov Feb May Note: All future planned releases dates are subject to change. 110

108 Upgrade Communications Where to find information? Help.sap.com/ibp Prior to Upgrade Customer Notification Important Notes, & Date confirmation Release Notes SCN Link to IBP Upgrade Communication Process PPT: IBP Upgrade Planning For patch releases of the software, SAP produces Release notes and Upgrade Notification to communicate the updates and impact. 111

109 2018 Upcoming Planned Upgrades Primary upgrade window Primary Upgrade Window: Default Upgrade timeframe during which systems will be scheduled for upgrade. Reschedule requests can be communicated to or via customer support incident. SAP IBP 1802: Applied to Customer Systems February through March 2018 Planned Release to Hosting February 6, 2018 SAP IBP 1805: Applied to Customer Systems May 11 to June 8, 2018 Planned Release to Hosting May 8, 2018 SAP IBP 1808: Applied to Customer Systems August 10 to August 31, 2018 Planned Release to Hosting August 7, 2018 SAP IBP 1811: Applied to Customer Systems November 9 to November 30, 2018 Planned Release to Hosting November 6, 2018 Future timings of upgrades are subject to change

110 SAP IBP Customer Survey SAP IBP Customer Surveys will be distributed in the next couple of weeks. Please complete the surveys to share from your SAP IBP experience and rate SAP. 113