Your Sales and Operations Planning (S&OP) Analytics: Crystal Ball or Ball and Chain?

1

Your S&OP Analytics:

Crystal Ball or Ball and Chain?

Bob Ferrari, Executive Editor- Supply Chain Matters Blog

Managing Director- The Ferrari Consulting and Research

Group LLC

August 13, 2013

Copyright 2013 The Ferrari Consulting and Research Group LLC

Key Messages

Slide 2

S&OP needs to move toward more

timely decisions and better prediction

of events and business outcomes

The Planets of Business Needs and

Information Technology Are Aligning

Toward More Leveraged Use of

Predictive Analytics as the Enabler

Predictive

Analytics

Constraint

Modeling

Best Outcomes for

Your Business = +

Copyright 2013 The Ferrari Consulting and Research Group LLC Slide 3

Outline

Snapshot of today’s global supply chains and

S&OP mechanisms

Explore what are predictive analytics capabilities

Reflect on todays S&OP challenges and needs

Converging forces (Business, Supply Chain, IT)

Implications and Takeaways

Recommendations

Copyright 2013 The Ferrari Consulting and Research Group LLC 4

End-to-End Supply Chain

4

Supplier Customer Suppliers’

Supplier

Source

Internal or External Internal or External

Your Company

Return

Deliver Make Source

Return

Plan

Deliver

Return

Source

Return

Make Source

Return

Plan

Deliver

Return

Deliver Make

Plan

Return Return

Customers

’

Customer

Physical, Information, and Financial Flow

5

Today’s Supply Chains

• Complex, global-based value-chains

• Segmented-Open-Closed-Vertically

Integrated- Outsourced

• Servicing more demanding customers:

• Increased product complexity

• Technology-enabled online consumer

• Shorter product development cycles

• Multiple years of cost-cutting, lean and demand-

driven initiatives

• Explosion in data- drowning in data

• Dramatic increases in supply chain disruption

and risk events

The New Normal

Slide 6

Risk Complexity Unpredictability

Balancing Efficiency – Agility - Responsiveness

In a 7 Day by 24 Continuous Cycle


S&OP As Originally Launched

Aligning supply and demand in a

series of process steps

Achieving one-number consensus

Context of the financial plan

Sequential in nature with lots of data

collection and analysis

Operations-led

Execution planning horizons

Push to senior management for

needed decisions

Slide 7

Demand

Analysis

Supply

Analysis

S&OP

Meeting

Financial Goals & Metrics

Business Metrics

Sales & Marketing Forecasts

Inventory Plans

Forecasts and Order Rates

Supply Plans

New Product Plans

Source: Dick Ling, Andy Coldrick Original Creators of S&OP

Constant Analysis of Data


S&OP As Matured in Today’s Supply Chain

Environments

Broad cross-functional involvement and

collaboration

External stakeholders and trading

partners

Senior management sponsored and

need for process to support more

integrated business planning

Longer planning horizons (tactical and

strategic)

Outside-in orientation

Orchestrate implementation of desired

business outcomes

Slide 8

Portfolio of Products and Services

Suppliers

Trading Partners

Customers

Sales & Marketing

Managing

Supply

Managing

Customer

Demand

Activity

Portfolio

Demand

Supply

Integrative

Reconciliation

Executive S&OP

Goal: A Decision Support Process for End-to-End Supply Chain

Requirements


Previous Steelwedge Webinar- Tom Wallace

Wallace’s takeaway messages regarding

today’s evolution of S&OP:

Continues to iterate important inflection points

Needs to integrate both financial and operational

planning

S&OP scope is both strategic and tactical

Needs to enhance agility through near-term tactical

and medium and long-term strategic plans.

Days of blood, sweat and Excel are over

Slide 9


Current Process Challenges

Multiple research surveys indicate S&OP processes

have stalled

Too much time invested in assembly and analysis of data

Process lacks ability to synchronize planning and fulfillment

information

Desire and/or need to move beyond a monthly cycle

More integrative tools beyond spreadsheets / ad-hoc analysis

Too much time required in background analysis projects vs.

ability to make informed decisions at an S&OP meeting

Latency and inconsistency in S&OP decision-making leads to

senior management frustration

Desire by participants to move toward extensible integrated

business planning and response

Slide 10


Time for Polling Question

What is the single most significant

challenge hindering your firm’s S&OP

process?

A. Too much time required to gather and analyze

data to come-up with meaningful insights

B. Cannot keep-up with the current pace of business

C. Process needs to become more predictive to

business outcomes

D. Ability to analyze information and trends during

the actual S&OP meetings

Slide 11

What are Predictive

Analytics Capabilities

Slide 12

Standard Reports

Ad Hoc Reports

Query / Drill Down

Alerts

Statistical Analysis

Randomized Testing

Predictive Modeling

Optimization “What’s the best that can happen?”

“What will happen next?”

“What happens if we try this?”

“Why is this happening?”

“What actions are needed?”

“What exactly is the problem?”

“How many, how often, where?”

“What happened?”

Predictive and

Prescriptive

Analytics

Descriptive

Analytics

(the “what”)

Degree of

Intelligence

Source: Analytics At Work, Thomas H. Davenport, Babson College

Analytics Defined- Tom Davenport


Analytics Within Supply Chain Processes

Deployed in supply chain process for quite

some time

Supply chain planning and optimization

Transportation scheduling and routing

Factory and production process scheduling

Multi-echelon inventory optimization/ network

design

New advances in information technology,

now open new opportunities and awareness

Dramatically accelerated clock speed of

business and added complexity and risk

Slide 14


Analytics and Big Data

An Analytically-Driven Process

“Big-Data” term often over-hyped and used to convey

all sorts of concepts

Organizations are literally drowning in data but lack

meaningful insights

Analytics is essentially how to process, analyze and

visualize vast arrays of information in more

innovative ways

Analytics-enabled decision-making in speed, quality

and context

Both a qualitative and quantitative mindset:

What do we know vs. what do we think we know

Requirement of augmented or new skills

Slide 15


Analytics Applied to Key S&OP Decisions

Sensing market changes ahead of the competition

Defining the most appropriate segmentation of supply

chain(s)

Determining most profitable product and/or customer

segments and how to best respond.

Identifying new opportunities for responsiveness,

reducing inventory or decreasing costs

Ability to simulate or compare different response

scenarios to market opportunities and/or supply chain

non-alignment quicker than industry competitors

Slide 16


One Other Polling Question

What is your organization’s current

awareness of predictive capabilities?

A. We have no such capabilities at this time

B. We are beginning to explore use

C. We need further understanding to the

benefits of S&OP

D. We have a staged deployment plan for use

Slide 17

Converging Forces in

Business, Supply Chain and IT

Slide 18

C-Suite Concerns and Objectives

Slide 19

“ As a group, CEO’s are investing more in customer insights than any

other functional area. They are seeking a better understanding of

individual customer needs and improved responsiveness”

2012 IBM Global Chief Executive Officer Study of over 1700 CEO’s Across 18 industries

Top CFO and Finance priorities over next 2-3 years:

73 percent cite lowering costs and increasing productivity

61 percent cite investing in analytics, planning, budgeting/forecasting

44 percent cite needs for upgrading organizational skills

2013 Accenture CFO Survey of 1250 Senior Finance Executives from Multiple Industries

Top Cited Concerns:

• Our inability to predict future performance in the new normal of

permanent market volatility (70 percent)

• Worried about the resilience of their supply chains (80 percent)

March 2012 Accenture Outlook: Preparing for the Unpredictable

Strong Evidence of Business Benefit

Slide 21

“Two-thirds of respondents report that use of information

(big data) and analytics is creating competitive advantage

for their organizations.”

Compares with 37 percent citing benefit two year ago- a 70

percent increase in two years

Source: Analytics: The real-world use of big data

IBM Institute for Business Value and Said Business School

2012 survey of over 1100 professionals across 26 industries


IT Technology Convergence

From OLTP to in-memory database and highly

scalable OLAP

Sequential processing to MPP

Data attached to the application to de-coupled

streaming databases

Data aligned to business constraints, insights

and decision-making support

Centralized data warehouse to bundled

analytical appliances

Centralized to distributed data management,

ownership and control of data

Slide 22


Supply Chain Process Convergence

More rapid and volatile business cycles are motivating many

manufacturers and retailers to re-look at sequential planning and

execution processes

Converge planning with sensing of orders, changed

events, disruptions, market opportunities

Augment planning with analytics, and shift emphasis

toward more predictive capabilities

True decision support fueled by embedded analytics

Slide 23

The Holy Grail of

Supply Chain Insights-Enabled

Execution


Implication of These Converged Forces

The ability to extract insights at sophistication levels not easily

achieved in the past

From historic sequential to more predictive and near real-time

planning and fulfillment information analysis

Leverage the advancements in in-memory computing,

visualization, business intelligence convergence

Incorporate both structured and unstructured information

Cloud computing and composite apps allow S&OP teams to fill-in

process gaps

Sense and respond capabilities to orchestrate desired business

outcomes

Supplemental mobile and social enabled tools to accommodate

virtual mobility and time-critical needs

Slide 24

An S&OP Information Architecture Blueprint

Slide 25

What-If

Scenario

Management Enhanced

Collaboration

Analytics-

Based

Decision

Support Simulation

S&OP Information Utility (Streaming Data)

Management Dashboard (Sense and Respond)

Business Activity Monitor and Management Platform

In-Memory Enabled

Faster Planning and Decision Support Cycles

Demand

and

Supply

Planning

Data

Leading

Indicator

Data

Execution

and

Fulfillment

Data

Unstructured

Data

Demand &

Financial

Sensing

Data

Best

Optimized

Business

Outcomes

Continuous or

Ad-Hoc

Analysis and

Review

Exception

and

Response

Based

Planning

Insertion of

Additional

Analysis or

Predictive

“Apps”


Slide 26



Clock speed of business change has dramatically increased

Extended and global supply chain now constantly challenged

with complexity / variability / volatility and risk

Organizations and S&OP teams drowning in data but lacking

important insights

Sequential planning and execution processes no longer

keeping-up with business change is reflected in S&OP

process frustration

Senior management converging on need for improved

business responsiveness and predictive decision-making

Technology convergence will open new opportunities in

supporting more predictive decision-support

Slide 27


A Revised Goal

Extensible Integrated Business Planning

Making timely, more well informed and insightful decisions

based on information insights and business goal context

Single information and intelligence-based repository that

supports decision-making within the S&OP process (equates

to original Reconciliation Process)

Abilities to sense and respond to market opportunities and/or

operational risk

Anticipate or shape market, product demand, supply or

fulfillment changes quicker than competitors

Simulate or compare various business scenario options

Orchestrate desired business outcomes

Slide 28

Select Examples of Predictive Analytics- Case Study 1

Slide 29

Global distributor and wholesaler of pharmaceutical drugs and

medicines servicing hospitals, pharmacies and healthcare providers.

A predictive capability that synthesizes market intelligence from customers,

manufacturers and other sources to identify significant or unusual upticks

in orders for specific pharmaceuticals that could trigger a broader market

shortage. Can also identify potential areas of abuse.

If supply shortage occurs or is expected, an automatic allocation system is

recommended and initiated that allocates limited supplies of that drug to

customers based on a set of pre-defined parameters.

If network-wide shortage is predicted, it can trigger alerts to procurement

supply team to augment inventory of specific likely drug alternatives that

customers will likely substitute.

Select Examples of Predictive Analytics- Case Study 2

Slide 30

A global wired and wireless network infrastructure equipment provider

Within a year of implementing analytics capability, the company could

determine in near real-time, when a product was not selling as expected,

and trigger demand shaping recommendations for other similar products.

Alternatively, if product sales trend higher than forecast, a quick analysis

of likely sales growth based on available sales forecasts triggers a review

of contract manufacturing material and capacity planning options to

determine timing options to boost production both short and long-term.

Recommendations

Slide 31


Leverage Power of Newer Technology Tools

o Data attached to an application to de-coupled

streaming planning and execution data

feeding an S&OP information utility

o OLTP central data warehouse to in-memory,

highly engineered, OLAP “apps”

o Data aligned to business constraints, insights

and predictive decision-support capabilities

o More emphasis on data visualization /

simulation and planning scenario tools

o Augmenting existing IT investments with

more cloud-based predictive and business

intelligence capabilities

Slide 32

Leverage Current Converging Forces of Advanced Technology


Plan for Impact on Existing People and Process

Recognize the growing awareness of

the power of a predictive analytics

driven process

Be cognizant that predictive analytics

capabilities are still evolving

Encourage the receptiveness of S&OP

participants to analytical concepts

Understand requirement for

augmented skills

Slide 33


Other Recommendations

The goal is enhancing S&OP decision-making vs. that of

technology and tools

S&OP team must take ownership- IT partnership and support

Begin in small, managed scope and expand

Tailor the process, data sources and analytics tools to

support specified opportunities based on S&OP priorities

Include the change management and skills impacts in your

milestones. Consider centralization of capability

Critical to strive for high data quality and well understood

information taxonomy

Not a rip and replace of existing systems but rather an

insertion of augmented capability

Slide 34


Final Thoughts

Slide 35

A vibrant S&OP process supporting

timely decisions and better prediction

of events and business outcomes

Seize the opportunity of the alignment

of business, supply chain and IT

planets toward more leveraged use of

predictive analytics

From Key Performance Indicators (KPI’s)

To Key Responsive Indicators (KRR)

Thank You

Contact Information: Bob Ferrari

Email: [email protected]

Twitter: @Bob_Ferrari

Web Site: http://www.theferrarigroup.com

mailto:[email protected]





http://www.theferrarigroup.com/

Appendix Slides

Copyright 2013 The Ferrari Consulting and Research Group LLC Slide 38

Introduction

• Independent supply chain and B2B

industry analyst- previous leadership

roles at AMR Research and IDC

• Multiple years of supply chain

business planning, operational and IT

systems implementation experience

• Recognized supply chain strategic and

tactical thought leader, technology

market influencer

• Consultant in supply chain strategy,

business process, and information

technology deployment

• Founder and Executive Editor Supply

Chain Matters blog

Top Ten SCM Blogs Top 25 Most Influential

SCM Blogs

Logistics Degree.net

© 2013 Steelwedge Software, Inc. Confidential. 1

Single Line of Sight: Plan, Perform, Profit

Planning Analytics – Big Data Driven S&OP Nari Viswanathan


< Control and visibility

> Risks

> Business change

> Collapse: planning/execution

12 months=70%

Growth in Data

Bigger Demand/Supply Network =

Bigger Data


Explosion of Data

Requires Advanced S&OP Technology D

ata

volu

me/

com

ple

xity

Business Value

20-

100X

2-

10X

X

Big Data Powered S&OP:

Measures units/dollars, links departments/ time

horizons and

delivers

multiple

supply

scenarios

Advanced S&OP:

Measures units/dollars

links

supply,

demand &

finance

Traditional

S&OP:

Measures units


Characteristics of S&OP Datasets

• Classic Big Data problem – High volume, velocity and

variability

• Steelwedge Integrated Business Planning manages – Millions of planning data

elements

– 1000’s of business rules

– Deep & complex hierarchies


Volume Velocity Variability

Vertical, horizontal and

multi-dimensional

aggregation and

disaggregation in real-time

Reflects real world

complexity

Harmonizes

Heterogeneous Data

(from different formats,

structures & semantics)

S&OP Big Data Model

1000

Customers

100M to 1 B

planning

relations

10000

orders

per day

1-10M

calculations

per minute

100 new

items per

day

1000 new

customer-

product

combinations

per week


Planning Versus Analytics

• Planning

– Forward looking

– Suited for simulation and

mathematical calculations

– Planner roles typically use

– OLTP technology

• Analytics

– Backward looking

– Suited for metrics and

aggregation

– Execs and business

analysts

– OLAP technology

Ideal solution marries the best of both these worlds


Planning Analytics

Scalability & Performance

Benefits

• Higher User & Data Scalability

• Higher Performance at Scale

• Faster Report Creation

• Superior End-user Self-service

• Dedicated Reporting Data base

Operational

Data base

(OLTP)

S&

OP

Insi

ght

S&OP Insight

High Performance with High Scalability

Operational

Data base

S&OP Insight (OLAP)


#1: To High Resolution S&OP

The Hierarchy of Supply Chain Metrics Source: Gartner


#2: Extra-Ordinary Scenarios


#3: Better Global Visibility


S&OP Apps – Planning Analytics For Offline Processes

Set S&OP Parameters

& Drive Process

S&OP Enhanced

Data

Inventory Segmentation

Stocking Strategy

Demand Policy

Demand Pattern Segmentation

Inventory Segmentation

Service Level Planning

Automate and

Standardize

Offline

Orphaned

Processes

Customer

Developed

Solutions

Range

Based

Forecasting

In collaboration with Aztral & Blake Johnson

Range Forecast

../../../Product Management/Releases/New Features/Analytic Tools/ED- SW Apps/Demand Policy Apps -Working Excel.xlsx

../../../Product Management/Releases/New Features/Analytic Tools/ED- SW Apps/segmentation final.xlsx

Your Sales and Operations Planning (S&OP) Analytics: Crystal Ball or Ball and Chain?

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