plan ready: the power of knowing what ifinfo.steelwedge.com/rs/973-qzy-915/images/envision...

Plan Ready:

The power of knowing

What if

© 2015 Steelwedge Software, Inc. Confidential. 2

Steelwedge 2015 Roadmap Glenn Jones, EVP Product

© 2015 Steelwedge Software, Inc. Confidential.

analyze

assimilate

align

act

PlanStreaming Proposition

3

Open

• Multi-source data input, cleansing and normalization

Dynamic

• Collect demand & supply signals, assess impact vs plan, and alert extended supply chain to potential changing market and supply

Prioritized

• Focus users on what opportunities and issues that matter most

Intelligent

• Data driven architecture and advanced analytics. Cognitive learning

Operational Excellence


Decision Ready Planning: Plan at any time and frequency

4

Low Yield

Demand

Signals Stream

Supply Risk

Supply

Information Retail Point of Sale

Distributor Sell-in/Sell-Thru


In-time planning, anticipation and agile response for complex markets

PlanStreaming™


PlanStreaming™ Architecture

CP Agrawal, Chief Technology Officer


Cloud Architecture Evolution

1st generation cloud architecture

Web browser

Excel Mobile

10101 01101 10110

Special processes, extensions

3rd generation cloud architecture

• SAP on-demand

• Oracle on-demand

• Kinaxis

2nd generation cloud architecture

• Salesforce.com

• Workday

• Steelwedge 5.5

Company B

Company A

• Google

• Facebook

• Box

• Steelwedge PlanStreamingTM

Web serv ices FTP Web serv ices

• Leverages Silicon Valley innovation

• Distributed processing

• Distributed database with partitioning

• Interface via web services & ftp

Web client

Web services & application

servers

Database servers

Web client

7


Planning Is Data and Compute Intensive

8

Planning Measures = x

• Bill of Materials (BOM)

• Retail forecast

• Wholesale forecast

• Finished Good, WIP and Component Part Inventory

• Production plan

• Lead time (coverage)

Planning Relations = End Item x Destination x Source =

3,000,000 x 10 = 30M

History Future

M M M M1 M2 M3 M4 M5 M6 M7

Planning Periods = 24 Months

+ Interactive Scenario Simulation (What If)

30M Configurations* 24 months* 200+ measures = 14 B planning points

Product Customer

All All

Business Unit Market

Business Line Market Unit

Net Element Version CBT

Sales Item Customer Team

Customer

Scenario 1

Scenario 2

Scenario 3


Leverage Search and Social Network Technologies

9

Web browser

Excel Mobile

10101 01101 10110

Special processes, extensions

Applicati

on

Data

Services tier (SOA)

Web services

In-memory computation and caching

Planning & simulation

Business rule

Analytics Master data

Configuration data

Data exchange manager

Workflow engine

Search and catalog

Data reporting manager

Transactional and master data store

Relationship data

Metadata store configuration data

Event

and a

lert

m

anagem

ent

Extend Cloud

Planning cache

In-tray app

Template toolbar

Planning data

Service tier

Event queue

Mess

agin

g b

us


1000x Performance improvement

Steelwedge PlanStreaming™ Compute Model for Proven Performance

10

50% Faster response

time

10x Faster planning

100x Data volume

Planning Point Capacity


0% 32% 47% 50%

135%

562%

925%

Number of Planning Items

Tim

e t

aken in S

econds

Future data (in months) 35

History data (in months) 15

Number of Time Series 14

Rel# 5.5

PlanStreaming

% Performance improvement with PlanStreaming

17 25 28 30 47

172

328

18 19 19 20 20 26 32

0

50

100

150

200

250

300

350

1 item 25 items 50 items 75 items 100 items 500 items 1000 items

Cost Effective Scalability & Performance

Planning Template Execution Performance - Rel#5.5 vs. PlanStreaming™

11


0%

255%

505%

1957%

2729%



Number of Records 65529

1 11

23

72

116

3 3.1 3.8 3.5 4.1 0

20

40

60

80

100

120

140

1 T.S 25 T.S 50 T.S 75 T.S 100 T.S

Planning Reports Execution Performance - Rel#5.5 vs. PlanStreaming™

T.S-> Time Series

Number of Time Series

Tim

e t

aken in S

econds

Rel# 5.5

PlanStreaming



12




Planning Template at detail level

Overrides Performance - Rel#5.5 vs. PlanStreaming™

70

162

208

47 54 53

0

50

100

150

200

250

25 Cells 50 Cells 100 Cells

Note: Performance

tuning of planning

data overrides are

still in progress

49%

200%

292%

Number of cells overridden

Tim

e t

aken in S

econds

Rel# 5.5

PlanStreaming



13


Next Generation UI


State of the Art User Interface

15


Supply Chain Visibility

16


Consumer Sentiment Analysis

17


End-to-End Top-to-Bottom IBP innovation drives performance


Traditional S&OP

Supply Planning Unconstrained Constrained

Demand Planning Region Customer Product

Supply-Demand Matching

Weeks

& M

onth

s D

ays

Steelwedge Vision:

19

Outs

ide L

ead T

ime

Insi

de L

ead T

ime

Fore

cast

Accura

cy

Manufacturer/Brand Owner

Traditional S&OP – Supply Chain Centric

View is limited

One powerful platform helping customers predict, shape and respond to opportunity


Integrated Business Planning

Executive S&OP

Revenue & Margin Planning

Product Lifecycle Planning

Traditional S&OP

Weeks

& M

onth

s D

ays

Steelwedge Vision:

20

Outs

ide L

ead T

ime

Insi

de L

ead T

ime

Fore

cast

Accura

cy





Integrated Business Planning, Expands Horizons

“Proactive Planning”




Executive S&OP



Traditional S&OP

Weeks

& M

onth

s D

ays

Steelwedge Vision:

21

Outs

ide L

ead T

ime

Insi

de L

ead T

ime

Channel Partner/Retailer

Demand Intelligence

POS Data Forecasts

Sell in/out/through

Partner Co-Planning & CRM Integration

Fore

cast

Accura

cy


Finished Goods Inventory FGI & WIP Component Inventory

Revenue Margin Cost




Key Customer Co-Planning & Account Planning




Executive S&OP



Traditional S&OP

Supplier

Weeks

& M

onth

s D

ays

Steelwedge Vision:

22

Outs

ide L

ead T

ime

Insi

de L

ead T

ime


Demand Intelligence

POS Data Forecasts

Sell in/out/through


Fore

cast

Accura

cy



Revenue Margin Cost




Integrated the Network “Collaborative Co-Planning”

Collaboration

-> Forecast

< - Forecast

Commit

<- Resource

Capacity

< - Future Inventory

<- Supplier’s

Supplier




Executive S&OP



Traditional S&OP

Collaboration

Supplier

-> Forecast

< - Forecast Commit

<- Resource Capacity


<- Supplier’s Supplier

Weeks

& M

onth

s D

ays

Integrated Replenishment optimizes inventory levels

Steelwedge Vision:

23

Outs

ide L

ead T

ime

Insi

de L

ead T

ime


Demand Intelligence

POS Data Forecasts

Sell in/out/through


Fore

cast

Accura

cy


Replenishment


Revenue Margin Cost







Executive S&OP



Traditional S&OP

Collaboration

Supplier

-> Forecast

< - Forecast Commit




Weeks

& M

onth

s D

ays Leapfrog the

competition:

Integrate Sense…

Steelwedge Vision:

24


Demand Intelligence

POS Data Forecasts

Sell in/out/through


Fore

cast

Accura

cy


Hours

Replenishment


Revenue Margin Cost




Response Management

Opportunities &

Customer Orders

….and Respond

Outs

ide L

ead T

ime

Insi

de L

ead T

ime




Executive S&OP



Insight Streaming

Traditional S&OP

Collaboration

Supplier

-> Forecast

< - Forecast Commit




Weeks

& M

onth

s D

ays

Online Heat Map

Social Indicators

Analytics

Causal Variables

Consumer

Leapfrog the competition:

Customer Intelligence

Steelwedge Vision:

25


Demand Intelligence

POS Data Forecasts

Sell in/out/through


Fore

cast

Accura

cy





Hours

ATP & Response

Replenishment


Revenue Margin Cost

Opportunities &

Customer Orders

Ratings

Outs

ide L

ead T

ime

Insi

de L

ead T

ime




Executive S&OP



Insight Streaming

Traditional S&OP

Collaboration

Supplier

-> Forecast

< - Forecast Commit




Weeks

& M

onth

s D

ays

Online Heat Map

Social Indicators

Analytics

Causal Variables

Steelwedge Vision:

26


Demand Intelligence

POS Data Forecasts

Sell in/out/through


Fore

cast

Accura

cy





Hours

ATP & Response

Replenishment


Revenue Margin Cost

Opportunities &

Customer Orders

Ratings

Insight Stream

Social Indicators

Causal Variables

Analytics

Outs

ide L

ead T

ime

Insi

de L

ead T

ime

Climate Information

Leapfrog the competition:

Supplier Intelligence

Consumer



PlanStreaming Solution Footprint

27

Legend: Roadmap

Steelwedge PlanStreaming™ Platform

Product Planning

Sales Planning

Supply Chain Planning


Application Framework



PlanStreaming™ Analytics

Insi

ghtS

tream

™


Legend: Roadmap

Steelwedge PlanStreaming™ Platform

Product Planning

Sales Planning



Application Framework



PlanStreaming™ Analytics

Insi

ghtS

tream

™

Steelwedge Solution Footprint – Supply Chain Planning

28


Demand/Supply Balancing

Allocation

Demand Management

Statistical Forecasting

CRM Integration

Customer Collaboration

Supply Management

Rough Cut Capacity Planning

Component Parts Planning

Supplier Collaboration

Response Management

Replenishment


Sales Planning Greg Gilbert, VP Product Management


3 Sales Planning Processes


Steelwedge Sales Planning

Planning Challenges

• Sales Engagement

• Rationalization of CRM data into planning process

• Forecasting UOM

• Need for customer collaboration

• Relationship between internal groups

• Process discipline

Sales Planning Solution

Business Benefits

• Reduce forecast error

• Improved cross functional input into planning process

• Measures to track value of input from various groups

Measure input and process

Customer and internal Collaboration

Flexible business modeling

Role based views

Machine learning


Three Routes to Market

• Collaborative customer planning

• Customer specific forecasts

• Heavy influence on market conditions and promotional activity

Brand Owner

Retail & on-line

Distributors &

Value Added Resellers

Direct

• Opportunity Driven

• Enterprise Sales

• Reseller forecasts as input

• Opportunity Driven

• Enterprise Sales team is primary view into demand visibility

1

2

3


How Steelwedge Sales Planning Delivers

33

• Out of box integration with SFDC

• ERP data connections with easy to use Excel interface where needed

• Customer collaboration

• Single global view

• Full audit trail

• Tracking by role

• Change management tracking and alerting

• Reporting pushed to inbox and mobile devices

• Process enforcement

• Unified model with role-based views

• Multiple roll-ups

• Multiple scenarios and plans


Opportunity to Demand Mapping

34

● Bring in Lower Probability /early stage deals at higher level (example: $ & BU), help convert to details based on historical mix

● Middle Stage opportunities are often linked to a platform or family, but not fully configured or quotes

● Detailed visibility quote for late stage opportunities

East Bank $35,500,000 25% 6/30/2016

Beckham Cons $14,530,000 35% 4/15/2016

Big Orange Ins $24,500,000 30% 5/20/2016

Reliable Cons $35,500,000 50% 2/20/2016

Macro Semi $14,530,000 50% 1/31/2016

State Auto $24,500,000 60% 2/20/2016

Australian Bank $35,500,000 90% 10/30/2016

Beckham Cons $14,530,000 80% 11/15/2016

Big Orange Ins $24,500,000 90% 10/20/2016

Demand Planning

Opportunity Amount Probability Close Date

• Low Probability

• Sketchy details

• Mid-long horizon

• High Probability

• Detailed opportunity

• Associated quote

Leverage historical data and machine learning to better predict actual deal probability and product mix translation


SalesSight™ Salesforce App

35

Opportunities Master Data

Opportunities Master Data

Account manager Demand planner

Region manager

Opportunities Master data

SalesSight™

Master data

Opportunities

Time series data & reports

Revenue to volume

Aggregation/ disaggregation

SalesSight™


Response Management Dhruv Bansal, VP Product Management


Steelwedge Response Management

Supply Challenges

• Constrained supply allocation

• Component shortage

• Visibility to supplier lead time and capacity

• Quality issues

Demand Challenges

• Demand variation within lead time

• Trade-off demand by customer, region, BU

• Unexpected promotion

• Scheduling flexibility

Response Management Solution

Business Benefits

• Customized agile supply chain response based on strategic value of customers

• Decision making enabled by analytics: service level, product mix, revenue target

• Collaborate across business functions on single view of demand and supply data

Segmentation

Prioritization

Allocation Strategy

Rough Cut

Capacity Planning Supplier

Collaboration

What-If Scenario Planning

37


Scheduling

Supplier Collaboration

RCCP

Allocation Strategies

Operational Analytics

Response Management Key Capabilities

Scheduling

• Release to production suggested preq, WO, transfers

• Forward-backward

• ATP

Allocation Strategies

• Prioritization of demand

• Fair share driven quotas between BU, Geo, suppliers

• Optimization on profitability, service level, lead time

Operational Analytics

• Can this promotion be supported?

• Am I meeting my customer Service level?

• What is the impact of changing product mix, priorities, service levels?

• What is the impact to Revenue, Cost and Profitability?

Response Management

38


Value Proposition: Sense, Prioritize, Capitalize

39

Market Changes

• Low Volume High Mix

• Commoditization

• Price Pressures

• Increased Service Level

• Transition to Value Add Software

• Faster planning cycle

• Reduced head count

• Fewer systems/ integration

• Lower support requirements

• Committed partner

Simplify

• Early identification of stock-outs and E&O

• Differentiated response based on customer SLA

• Continuous adjustment to demand supply fluctuations

Service Level

• Profitability from key customers

• Optimize product mix

Unlock Opportunities


Sense

Prioritize

Capitalize

• Single view of demand and response Continuously balance supply and demand as conditions fluctuate, evaluate options, and understand choice impact on future plan

• Collaborative platform Multiple stakeholders (internal and external) across the supply chain can review and adjust recommendations before executing a plan

• Manage by metrics Monitor and manage by exceptions, control and assess supply chain response based on customer (or internal) metrics

− Quickly monitor demand/supply mismatches

− Early identification of stock-outs or low service levels

− Early identification of E&O

− Prioritize items where improved forecast accuracy yields the greatest benefits

Sense, Prioritize and Capitalize


Sense, Prioritize and Capitalize

• Cloud Based Big Data Platform Quickly evaluate planning trade-offs within minutes by utilizing the latest big data technology stack capable of linear horizontal scaling with exponential performance gains

• Data Science Industry leading demand supply matching algorithms based on rules, heuristics and pure optimization

41

Sense

Prioritize

Capitalize


InsightStream™ Understand new and immature markets


Immature and Emerging Markets

• 100’s of channels (Retail & Distributors)

• Minimal point of sale data

• High latency in 3rd world markets

• Consumer feedback via social network

China

India Africa

43


What if you could gain a better understanding of demand?

• Capture available POS, other channel data, orders, shipments, & returns

• Complement it with consumer sentiment via news feeds and social media

• Apply advanced demand sensing predictive analytics

• To identify future demand for existing and new products

44


Steelwedge PlanStreaming™ Analytics

45

Measurable results:

• Improved forecast accuracy

• Rapid response to changing business needs

• Reduced stock-outs

• Improved inventory turns

• Lower inventory cost

• End-to-end visibility and decision making Executive view

Continuous planning view

Algorithms are options in our core

planning products (ie. demand shaping, supply management,

demand management, etc.)

Comprehensive coverage from descriptive to prescriptive analytics for end-to-end value


Analytics Roadmap

46

Str

uctu

red D

ata

U

nst

ructu

red D

ata

Demand Planner

Data Scientist

Steelwedge Optimized Advanced Algorithms

Open Source Algorithms in R, Python

Steelwedge UI

IPython Interface

Web Interface

Steelwedge Analytics Engine Framework


Thank You

plan ready: the power of knowing what ifinfo.steelwedge.com/rs/973-qzy-915/images/envision...

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