Use of Analytics in Procurement

Did You Know
Use of analytical tool increased
demand forecast accuracy by 55%
- leading to increased contract
negotiation power and decreased
chances of stocks-outs!
© 2010 Accenture. All rights reserved.

Raj Dhawan, PhD
Supply Chain Management
Accenture
The CIPSA Special Interest Forum
Use of Technology in Procurement - Sydney
PROCUREMENT ANALYTICS

Agenda
What is Procurement Analytics
1
Why should it be used
2
How can it be implemented
3

Overview – Analytics
The process of using quantitative
methods to derive actionable
insights and outcomes from data.
 Involves the capture and use of data to support fact-based
decision making and gaining competitive advantage
 Typically reporting on what has happened in the past
 Using predictive analytics based on historical data to
ascertain what will happen in the future
WHAT WHY HOW

Applications in Procurement
 Vendor Evaluation
 Factoring complete and timely deliveries, quality of
materials, and time and effort to resolution on
problematic orders in addition to lowest cost
 Spend Analytics
 Examine multiple types of data sets (e.g., A/P data,
supplier-provided invoice data, tax data), Results in an
entirely different look at data elements decrease
maverick spend, of spend economies of scale
 Demand Forecasting
 Average cycle volume, Maximum demand peaks
 Contract Management
 Optimise discount levels, Forecast financial liabilities
WHAT WHY HOW

Applications in Procurement
 Supplier Relationship Management
 vendor score, purchase order value, PO volume
 Other examples
 vendor consolidation, reducing duplicate orders,
increasing contract orders while reducing open
market transactions
WHAT WHY HOW

Source: Competing on Analytics: The New Science of Winning (Davenport / Harris)
What?
CompetitiveAdvantage
Sophistication of Intelligence
Optimization
Predictive Modeling
Forecasting/extrapolation
Statistical analysis
Alerts
Query/drill down
Ad hoc reports
Standard Reports
“What’s the best that can happen?”
“What will happen next?”
“What if these trends continue?”
“Why is this happening?”
“What actions are needed?”
“What exactly is the problem?”
“How many, how often, where?”
“What happened?”
Predictive
Analytics
Descriptive
Analytics
Analytics Sophistication Levels
WHAT WHY HOW

Analytics Maturity for Organisations
Stage 5
Analytical
Competitors
Stage 4
Analytical
Companies
Stage 3
Analytical Aspirations
Stage 2
Localized Analytics
Stage 1
Analytical Novice
Routinely uses analytics as a distinctive
capability, takes an enterprise-wide approach, has
committed and involved leadership, and has
achieved large-scale results.
Has established analytical capabilities, and has a
few significant initiatives under way – but progress
is slow and missing critical elements.
Organization lacks one or several of the pre-
requisites for serious analytical work.
Applies analytics regularly, and realizes benefits
across the organization.
Pockets of analytical activity, but they are
uncoordinated and not focused on strategic targets.
WHAT WHY HOW
WHICH STAGE OF PROCUREMENT ANALYTICS IS YOUR ORGANISATION IN?

- Growing at a terrific rate (a compound
annual 60%), speeding up all the time.
-Around 1,200 Exabyte of digital data will
be generated this year
- Information created by machines
and used by other machines will
probably grow faster than anything else.
This is primarily ‘database
to database’ information. People are only
tangentially involved in most of it.•
Increase in computational power will facilitate operations on data thus leading to
“fact-based decision- making”
Why Analytics is now important
WHAT WHY HOW

Procurement Analytics Study
Based on an analytical (modeling and simulation) technique
–
Systems Thinking
“a holistic approach to analysis that focuses on the way that a
system's constituent parts interrelate and how systems work over
time and within the context of larger systems.”
Motivation for this study
To study the effectiveness of Systems Thinking in supply chain
scenarios by comparing decisions made with and without the use
of the technique.
WHAT WHY HOW

Basic Setup
Tasks
Participants
Experiment
1. Practitioners provided context and background information on tasks
2. Practitioners divided in two groups – random allocation, 40 each
3. A group of practitioners solve tasks based on their knowledge and
information provided
4. The second group is first trained in analytical method (systems
thinking). This group uses the analytical tools to solve the tasks.
5. For both the tasks compare the accuracy of results
without vs. with the use of Systems Thinking tools
WHAT WHY HOW

Simple Task
The Task
• In which quarter did
• the Contract Manager have maximum number of contracts on
hand?
• largest number of contracts expire?
• Contract Manager work (signing/expiry) on the least number of
Contracts?
Context
• Inflow of contracts – signing
• Outflow of contracts – expiry
• Details of inflow and outflow provided for time
periods
• Manual vs. Visual
Solution
• Active contracts in any quarter = expired –
new contracts from previous quarters +
those in current quarter
WHAT WHY HOW
Total active contracts

Simple Task - Results
Procurement
• How many contracts
• Current state of
contracts
• Expiry/renewal
• Reporting
WHAT WHY HOW
• Even simple, routine tasks can sometimes get
overwhelming or not given sufficient attention…
• Electronic capture of data, visual representation and alerts
go a long way
Accuratecalculationoftimeperiodwithlargest
contracts(percentageofparticipants)

Complex Task
The Task
• Forecast sales of mobile phones over next two
years
Context
• Telco operating in a new market
• Uncertain demand
• Historical information
• External factors
• Sales drives procurement, impacts inventory
Solution
• Sharp increase in product demand in first 8
months, followed by sharp decrease in the
following 10 months and then gradual decline
WHAT WHY HOW

Complex Task - Results
•Naïve mental models
• Not taking into account all factors
• Not capturing the right causal relationships
• Not being able to compute affect of input
factors to forecast
Out of stock – rush orders,
higher purchase price,
unhappy business units,
unhappy customers, loss of
market share
Excess stock – inventory
holding costs, extra resources
for maintenance, increased
cost  decrease in profit
Accurate Forecast
GUT FEEL
WHAT WHY HOW

Complex Task - Results
Procurement
• When to order and how many
• Accurate information on volume
leading to better negotiating
power
• Lesser chances of going out of
stock or having excess
• Improved communication with
business units and vendors
WHAT WHY HOWCorrectforecast(percentageoftotalparticipants)
FACT BASED
Improved understanding
of stocks and flows

Summary of Results
WHAT WHY HOW
 Native ability
 to comprehend complex
procurement issues is limited –
too many variables to process
 Fact-based decision
making
 leads to better results –
accurate, measurable, resulting
in lower costs and greater
savings.
 Analytical tools
 improve our ability to capture right information, process it and
help in informed decision making.

How will Analytics support a
Procurement Organisation
Internal
Customer
Management
Training &
Development
Supplier
Relationship
Management
Procurement
Shared
Services
Requisition to Pay
Systems
Source to Contract
Systems
ENABLERS
Other Analytical
Tool
Source to Contract
Requisition to Pay
Contract
Lifecycle
Management
Organisation Structure Governance/ Compliance Proc. Performance
DEMAND
MANAGEMENT
SOURCING SUPPLIER
MANAGEMENT
PROCUREMENT STRATEGY
Capture information,
generate reports and
provide insight
Use information and insight
for day to day activities –
operationalise analytics
Use information and insight
-monitoring, continuous
improvement , one-off
decisions
WHAT WHY HOW
1
3
2

Corporate
Funcitons
Where does the analytics
role fit
Category
Managers
Category
Managers
Category
Managers
CPO
Procurement
Manager
Procurement
Manager
Procurement Shared Services
Procurement
Manager
Human
Resources
Legal
IT
Contract Managers
Finance
WHAT WHY HOW
Vendor Managers
Recruitment,
training
Financial master
data sharing, AP,
budgeting
Contracts
data sharing
Data capture,
systems support,
shared resources,
systems
integration
Strategy and Governance
2. Procurement
Analytics Manager
• Part of Strat & Gov
• Reports to CPO
• Makes sense of
analysed data,
benchmarks
• Supports
Procurement,
Category and
Contract managers
• Liaises with business
units
1. Data Analyst
• Part of PSS
• Potentially shared /
outsourced
• Supports Analytics
Manager
• Ensures data is
captured, and joined
• Models data,
generates forecasts

Focus on value and not on math!
 Focus on business benefits
 What is the issue, hypothesis and realistic
solution. How will this benefit business, help in
improving efficiency or add value
 Using the right tools
 BI, scorecards, what-if scenario analysis,
predictive analysis, optimisation
 Using the right skill
 Business trained analysts, not only from IT
WHAT WHY HOW

Implementation Challenges
 Organisation
 Top leadership awareness and support
 Partnership with business units
 Skill-set not available
 Processes
 One-off versus Operationalised
 Systems
 Right technology not available; antiquated
 Technology not usable
 Data
 Data in multiple systems
 Data not captured; existing data not analysed
WHAT WHY HOW

Next Steps
 Organisation
 Leadership – gain support
 BUs – collaborate, share
 Skills – develop, hire or share
 Culture – fact-based, not just gut-
feel decisions
 Process
 Embed analytics in processes
WHAT WHY HOW
 Systems
 Short-term – integrate, consolidate
& fully utilise existing systems
 Long-term – invest in an
eprocurement suite and
specialised analytical tools

Summary
 Procurement Analytics is the use of data to gain insight into what
has happened, and more importantly – what may happen – to
better manage spend, contracts, vendors and internal customers.
 There is now ample data, and technology that is usable by
procurement staff, to gain such insights.
 Evidence suggests that, analytical tools, when used appropriately
by skilled users, are able to facilitate fact-based decision making.
 Procurement leadership needs to instill a culture of fact-based
decision making at all levels of procurement.
 Procurement staff needs to be provided support via appropriate
tools and skills to fully leverage Analytics.
WHAT WHY HOW

rajat.dhawan@accenture.com
0402 925 505
rajatdhawan.com

Use of Analytics in Procurement

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