Driving a new age ofconnected planning

…through Optimisation, Machine Learning and Artificial Intelligence

in the Supply Chain

Workforce

SupplyChain

Marketing

Finance

Sales

IT

TerritoryandQuotaPlanning

SalesForecasting

IncentiveCompensation

MarketingPerformanceMgt

TradeandPromotionPlanning

MaterialsCosting&Profitability

S&OPDemand&SupplyPlanning

WorkforcePlanningWorkforceOptimisation

AgileImplementation

Planning,Budgeting,andForecasting RevenueModelingCorporateStrategicPlanning

ProjectCapacityAnalysis

FinancialConsolidations

Onboarding

SharedServicesAllocations

ChannelMgt Budgeting

CustomerAccountPlanner

ProductionCapacityPlanning

ESOP&EquityComp

PredictiveLaborModeling

TheConnectedPlanningPlatform

Anaplan is

ProductProfitabilityAnalysis

AccountSegmentation/Scoring

RealEstateManagement

SourcingOptimisationInventoryOptimisation

Platform

People

Apps

A cloud Planning & Analytics platform

upon which Anaplan and our Partners have built

hundreds of Apps

that connect people and data unlike any technology

ever has

ZeroBasedBudgeting

2018 Best Corporate

Performance Management

2018 LEADER

Sales Performance Management Magic Quadrant

LATEST MARKET GUIDE

Trade Promotion Management and Optimisation

2016 NICHE

Sales & Operations Planning Systems of Differentiation Magic Quadrant

2017 LEADER

Strategic Corporate Performance Management Magic Quadrant

2016 HYPE CYCLE

Human Capital Management Software, Workforce Planning & Modeling

Anaplan’s Unique Planning Technology

2017 NICHE

Financial Corporate Performance Management Magic Quadrant

Yourmodels

Yourtime periods

Yourdata

Your hierarchies

Your versions

Your dashboards

Leverage200 apps

Your drivers and methods

Yourformulas

Choice of 140+ functions

Empower business people to own plans

Dynamically scale

Billions of cells

Thousands of users

Hundreds of models

Bus

ines

s va

lue

Fast Time to Deliver with Low IT Involvement

6 Weeks – FP&A – Aviva Insurance

14 Weeks – Open to Buy – Carter’s

15 Weeks – FP&A, Consolidations – Fanatics

8 Weeks – BOM based costing – Del Monte

Anaplan Projects are delivered in weeks, not months

“Iwaslookingforaplatformthatwasflexible,fast,collaborative,couldscale,wasbusinessowned,andusershadtolike… IwaslookingforaunicornthatIdidn’tthinkexistedandthenIfoundAnaplan. Anaplanisthatunicorn.”– SarahPark,VPBusinessDevelopment

Supply Chains can be complex

Connected Supply Chain SolutionsSolution Description Supply Chain Finance Sales

DemandDrivenS&OP

Drives top- and bottom-line via tradeoff and scenario analyses over multiple planning horizons with near-time demand signals and optimisation across all functions

• Supply Planning• Capacity Planning• S&OP• What-If / Scenario

Analysis• Promotion Planning

• COGS Planning• OpEx Planning• Workforce Planning• Operations Planning• Rev./Mktg. Planning

• Sales Planning & Forecasting

Demand Collaboration

Customer and channel collaboration across multiple dimensions with accessible, real-time sharing of assumptions and forecasts

• Demand Planning• Promotion Planning• Demand Forecasting• Inventory & Service

Policy Analysis

• Rev./Mktg. Planning• AOP

• Sales Planning & Forecasting

• Account Seg.Territory Planning

• Sales Coverage

Product Portfolio Planning

Rapid, distributed approach to identify and capitalize on profitable product opportunities

• NPI/EOL/Cannibalization• Brand/Platform Planning• Demand Forecasting

• Financial Insights• Product Costing• R&D Planning

• Sales Insights• Sales Forecasting

Order Profitability

Near-time what-if support forcost versus lead time and promotion versus service level decisions

• Inventory Planning• Distribution Planning• Promotion Planning• Policy Analysis• What-if Analysis

• OpEx Planning• COGS Planning• Rev./Mktg. Planning• Operations Planning• AOP

-

Cost to Serve Management

Transparent accountability to drive continuous cost improvement

• Supply Planning• Inventory Planning

• OpEx Planning• Operations Planning• Workforce Planning• ZBB

-

Optimisation& Solver

Process Workflow

Anaplan Intelligence

Connecting the Network

ConnectedEnterprise

ConnectedNetwork

What is optimisation?

Optimisation is a mathematical method applied to business needs in order to determine an optimized goal.

It enables businesses to maximize goals AND/OR minimize costs.

Common Optimisation Problems

• ProductionScheduling• MachineAllocation• MaintenancePlanning

Production

• NetworkDesign• LTLLoading• Fuel-useMinimization

Distribution

• InventoryOptimisation• VendorSelection• ShipmentPlanning

Purchasing• CombinatorialAuctions• CatalogLayout• AdvertisementSelection

OtherApplications

• WorkforceScheduling• OfficeAssignment

HumanResources

• PortfolioOptimisation• FundCloning• BondManagement

Investment

Component of Function that can be changed.

e.g., unit volume

Optimisation Problem Definition

Objective Variable Constraint

Maximize or minimize the value of some function, F(x1,x2…xn)or Determine Feasibility

e.g., maximize profit

Constraints on individual x’s and/or combinations of x’s

e.g., production capacity

y=x+4

y=2x- 8

y=-0.5x+7

y=-0.25x+6

y=-0.5x+3

Linear Programming Visualization

Feasible Region

Flexible optimisation

usually requires

programming background

Using only model based line items and formulas, the Optimiser does not require any specific modeling skills.

Delivered Technology in Anaplan

UI Driven Model Based Fast Calculation

Problem definition relies on a simple, Anaplan standard UI to give more flexibility to users.

Gurobi is one of the fastest optimisationengines on the market. Because the operation locks the model, it’s a prerequisite for the Optimiser to be fast.

Gurobi is on the Anaplan platform

Anaplan Core Anaplan Optimiser

Result Data

High Speed Transfer

Optimisation

∃

∑ ∀

• AnaplanenablesstreamlinedDataCollectionandCommunication

• MathematicalOptimisation acceleratesandimprovesPlanCreation

Anaplan + Gurobi

Optimisationgreatly

accelerate the planning process!

InputCollection

PlanCreation

Communication

Execution

ATypicalPlanningCycleforaDecisionService

+

Requirement byCategory Optimisation &AdvancedAnalyticsUseCases

AdvancedStatisticalForecasting

• Aligning forecastcomponentstodrivehighestaccuracy.• Provideforecasterswithconfidenceintervalstohelpassessrisk• Zero-basedforecastingtechniquesforhighlifecycleturnover

products

TransportationOptimisation

• Minimizationoftransportationcosts• Lowertotalcosttodeliver(acomponentoftotalcost toserve)• Automated, capacityconstrained shipmentassignments

WorkforceOptimisation

• LaborOptimisation bysite, qualification,etc…• Staffingnewproductionlocations• Workschedulingforallemployeesbyday,hour,etc…• Right-sizelabor,managementandleadership

Supply NetworkPlanning

• Optimal allocationofavailablesupplyacrossthedistributionchain• InventoryOptimisation,consideringopportunitycostandcostto

serve• AssetFootprinting

ProductionScheduling

• Detailed, timephasedscheduling• Arrangementofprocessordersforexecution

Price&PromotionsOptimisation

• Demand shaping• Inventoryreduction• Channelpricingsensitivity

OrderPromising(GATP)

• Available toPromise/GlobalAvailabletoPromiseincludingcapabletoproduce/procure

Resource&CapacityAllocation

• Constraint-basedRCCP• Scheduling constraints• Optimalallocationsformaximumprofitability

Optimisation & Solver

Optimisation with Anaplan

• Full Anaplan core support

• UI driven –no coding required

• Optimal –Feasible problem

• Linear problem only

ConnectedNetwork Planning

highly autonomous

continuously learning

decision making

business network

Machine Learning

Algorithms

Optimisation& Integrated

Solver

Opportunities with technology

Which SCM use cases to consider to apply ML?

Demand SensingProduct

Launch

Optimize Production

Inventory &

Working Capital

Predictive Maint-enance

Optimize pricing

Trade Promotion

Supply Chain

Rea

lized

Gai

n $

% Improvements over Statistical Models

Demand Forecasting

Demand Forecasting - Traditional

Sales VolumeTime Series Data

Statistical Model Forecast

How does the ML forecasting model work? Inputs Model Forecast

• Linear Regression

• Linear Classification

• Gradient Boosted Trees

• Wide and Deep Neural Network

• Deep Neural Networks

• Recurrent Neural Network

Transaction Data

Sales Volume

Demographics

Promotional Data

Seasonal TrendsForecast

Supply Chain Planning Customers

Sales & Operations Planning

End to End Supply Chain Planning

Supply Planning

Operations

Demand Planning

Trade Promotion

Merchandise Planning

ProfileLargest Beverage Company in the World

130 Years Old

Headquartered in Atlanta, GA

1.9B Daily Servings in 200+ Countries

$46B Net Operating Revenues with $184B Market Cap

23M+ Retail Customer Outlets

7,000 Associates, 900 Plants, and ~250 Bottlling Partners

Current StateManual

• Spreadsheet Calculations in Excel

• Distributed and collected via email

Inconsistent Method

• Minimal Standardization

• Either too high or too low detail

Disconnected

• Assumptions throughout process

Innovation Planning

(NPI, Collaboration, Capacity Planning)

Future StateAutomated

• All in One Tool

• All Data Sharing through the tool

Consistent Method

• More Standardization

• Lowest level data in the tool à roll ups to appropriate levels

Fully Connected

• Connected from S&OP to Ops Forecast

• Communication through tool and email

Why Anaplan?Collaboration with multiple entities

Speed of Calculation-large data sets

Intuitive and easy for end-users

Flexible Modeling

Workflow management among multiple user groups

Tracking changes and assumptions documentation

Multiple Use Cases across various functions in Organisation

CPG Presence and Growth

Innovation Planning

(NPI, Collaboration, Capacity Planning)

Consumer goods and retail

Major American manufacturer and retailer of children's apparel

Founded in 1865

Sales of $3.1B

654 locations

Convoluted sourcing rules known by one resource in an antiquated Access database

Wanted to compute a weekly buy for 250K SKUs (1.2B cells) end to end in less than 10 minutes

Supply Planning

SolutionScalable, robust, and intuitive solution to calculate buy quantities and make adjustments based on sourcing rules to support the buy/forecast/capacity planning processes

16-week implementation

Connected PlansMerchandise & Assortment Planning

Results7 days of inventory saved (or $15M per buy, $30M annually)

Reduced forecast process from 3+ days to 2.5 days

Reduced planner’s work in building buy from 4-5 hours to under one hour

Buy model takes less than 10 minutes compared to hours in their previous process

More time to analyze output and identify any potential issues prior to submitting

Supply Planning

Supply Planning

https://www.hubcomestoyou.com/london/