Are you interested in learning more about your spend data cleanse options? In this slideshare we summarized the obstacles and challenges we've seen energy companies go through when trying to select a solution for their dirty spend data problem.
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Today’s top energy executives recognize the huge value in
effective spend analysis…
Millions in
Cost Savings
Operational
Efficiencies
Optimized
SRM
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…but often overlook the most important criteria when
considering vendors
!
!
!
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Many variables seem important; others actually are important
Total Spend Analyzed
Speed of Data Cleansing
Number of Features
Number of Rules
Energy Spend Analyzed
Usability for Energy Professionals
Energy-Specific Rules
Quality of Data Cleansing
vs
vs
vs
vs
Most Important!
Integration w/ Transactional Platforms Integration w/ Strategic Platformsvs
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And when executives prioritize the wrong variables, they end
up with solutions that pose meaningful risks
Millions in
Lost Savings
Bad Data
Inaccurate
Reporting
Total Spend Analyzed
Speed of Data Cleansing
Number of Features
Number of Rules
Integration w/ Transactional Platforms
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“Experience in analyzing spend in your industry”
What to Look For in a Spend Analysis Solution
“To succeed at spend intelligence, it would help
if you were to hook up…a solution provider that
has familiarity with your industry”
Steps to Success for All Enterprises
So what do the industry experts recommend?
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Is it really that risky to choose a cross-industry provider?
Well, let’s take a look…
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Here are some of the
biggest customers that
one cross-industry
provider has…
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…are VERY different from the
things these companies buy
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Different suppliers
Different products
Different services
Different data
And…
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Complexity of Spend Data High
Plus, data from some industries is more complex
Commodities Engineered products
Specialized vendors Vendors providing many
products & services
Centralized purchasing Distributed purchasing
Basic services Highly-Technical Services
Products
purchased
Services
purchased
Suppliers
Organization
Data ComplexityLow High
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Complexity of Spend Data HighData Complexity High
Data ComplexityLow High
Turns out, energy company data is especially complex
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And we’re not talking about a small difference
Vs.
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10” .375 X42 ERW DRL HYUNDAI W/FBE 14-1
Accurately classifying cryptic, energy-specific items like this
requires highly specialized rules and schemas…
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…which cross-industry vendors cannot profitably develop
Energy
Consumer Goods
Automobiles
Airlines
Beverages
Fast Food
= Cross-Industry Vendors’ Profitability Threshold
Complexity of Spend Data High
Data ComplexityData ComplexityLow High
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After all, items like this need to be decoded piece-by-piece, and
even then – hundreds of permutations are possible
Material Group
Shape Steel
Wire Rod
Tubing
Piping
Casing
Alloy Ingot
Manufacturer
Hyundai Automobile
Hyundai Railway
Hyundai Steel
Hyundai Ship
Hyundai Plant
Hyundai Electric
Outside Diameter
6 inches
8 inches
10 inches
12 inches
14 inches
10” .375 X42 ERW DRL HYUNDAI W/FBE 14-1
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Now imagine this 1 transaction…
…multiplied by millions
10” .375 X42 ERW DRL HYUNDAI W/FBE 14-1
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So what happens when energy firms actually buy
cross-industry spend solutions?
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They’re left with shocking (real-life) examples like this:
HVAC Mechanical Construction Service
Cross-Industry Vendor Classification: Correct Classification:
Cooling Tower Maintenance
✓
Line Item: Cooling Tower Maintenance
Price: $38,300,000
Supplier: Bunneys Inc.
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Cross-Industry Vendor Classification: Correct Classification:
Development Environment Software Real Estate
✓
…and many, many (real-life) examples like this:
Line Item: Improvement Allowance
Price: $3,200,000
Supplier: Red Hat Software
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Chemicals
Not Chemicals
9%
91%
$51.5M
CHEMICALS, GENERAL
Cross-Industry Vendor Classification: Correct Classification:
…which combine to form (real-life) categories like this:
Production Chemicals $2,641,910
Painting and Coatings $1,487,143
Nitrogen Services $443,150
Pumps $10,088,197
Motors $9,037,047
Electric Submersible Pumping (ESP) Lift Services $3,704,851
Variable Frequency Drives $3,165,546
Pump Seals $3,034,483
Drill Bits $2,691,688
Valves $2,641,910
Separators $1,487,143
Wire and Cable $1,390,791
Casing and Tubing Services $882,221
Coil Tubing services $822,310
Motor Maintenance $708,009
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The analysts for these energy firms spend days fulfilling simple
requests…
…and have no choice but to circulate incomplete reports
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Meanwhile, unactionable categories like this one…
Engineering Spend
Misclassified Elsewhere
+$32.6 M
$58.9 M
Spend Classified
as “Engineering”
Portion that Wasn’t
Actually Engineering
-$11M
…cost them millions in lost savings every year
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Ok, so can I do it myself?
Well, let’s take a look…
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Let’s look at 1 transaction.
10” .375 X42 ERW DRL HYUNDAI W/FBE 14-1
Curious how an analyst might decode and classify this?
It’s a bit complicated…
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Manufacturer
Hyundai Automobile
Hyundai Railway
Hyundai Steel
Hyundai Ship
Hyundai Plant
Hyundai Electric
…
He would likely recognize “HYUNDAI” as a Hyundai Corp manufacturing
facility, but that still leaves hundreds of plausible classifications
?
10” .375 X42 ERW DRL HYUNDAI W/FBE 14-1
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Material Group
Shape Steel
Wire Rod
Tubing
Piping
Casing
Alloy Ingot
Manufacturer
Hyundai Automobile
Hyundai Railway
Hyundai Steel
Hyundai Ship
Hyundai Plant
Hyundai Electric
… …
So, he would need to know that the code “ERW” denotes casing, tubing, and
piping; this narrows material groups, but still leaves 3 possible variations
?
✓
10” .375 X42 ERW DRL HYUNDAI W/FBE 14-1
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Material Group
Shape Steel
Wire Rod
Tubing
Piping
Casing
Alloy Ingot
Manufacturer
Hyundai Automobile
Hyundai Railway
Hyundai Steel
Hyundai Ship
Hyundai Plant
Hyundai Electric
… …
Outside Diameter
Third, he would need to know that 10” indicates an outside diameter, and that
this measurement rules out piping and casing
✓
6 inches
8 inches
10 inches
12 inches
14 inches
Tubing ✓
✓ ✓
10” .375 X42 ERW DRL HYUNDAI W/FBE 14-1
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This single transaction could have been classified in more
than 200 different ways…
See how difficult accurate energy spend classification is?
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Now imagine that 1 transaction…
…multiplied by millions
(50% of which is unclassified, blank, and/or inaccurate)
It’s a decoding job not fit for a human
10” .375 X42 ERW DRL HYUNDAI W/FBE 14-1
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Out of curiosity…
Let’s see what it would take a human (your analyst)
to cleanse this data to a 98%+ level of accuracy?
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Scrubber, 24" x 4', Horizontal, 300 # MAWPScrubber, 24" x 4', Horizontal, 300 # MAWP
An analyst would need to cleanse 312 transactions per hour (or 1 transaction
every 12 seconds) for a full year to cleanse just 1 year of data!
1 average year of data = 1.3 million transactions
Assume (conservatively), ~ 50% of transactions –
650,000 lines – require cleansing and classification
With no vacation, there are 2,080 hours in a work year
Which means…
Here’s the math:
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That’s right – he would need to decode one of these:
every 12 seconds, with no breaks, for a full year
(and that would just get you one year of cleansed data that is a year out-of-date)
10'' .375 X42 ERW HYUNDAI W/FBE 14-16 MILS.
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Data scientists spend 80% of their
time mired in “data janitor work.”
This is a problem across the board for
attempted in-house solutions...
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There’s another cost that hurts your bottom line
The average, entry-level data analyst makes $60,000/yr.
Let’s assume you have a modest team of 5 analysts, who
spend 80% of their time cleansing spend data rather than
analyzing it
Which means…
Let’s look at your best-case scenario:
You spend (at least) $240,000 every year for
analysis you never receive
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Well, because when it comes to energy spend…
$2+ Trillion
Energy Spend
Cleansed $320 Billion
Energy Spend
Cleansed
“Largest” Cross-Industry
Vendor in the World
…we’re the big kids on the block
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And, our industry focus allows us to do things
that others simply can’t…
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(an investment that isn’t cost-effective for cross-industry vendors)
…like perfecting a rules engine that exclusively parses and
classifies Power, Oil, and Gas data
50+ engineers, analysts, developers Millions of energy-specific rules
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Remember that line item example from earlier?
Material Group
Shape Steel
Wire Rod
Tubing
Piping
Casing
Alloy Ingot
Manufacturer
Hyundai Automobile
Hyundai Railway
Hyundai Steel
Hyundai Ship
Hyundai Plant
Hyundai Electric
Outside Diameter
6 inches
8 inches
10 inches
12 inches
14 inches
10” .375 X42 ERW DRL HYUNDAI W/FBE 14-1
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Our rules deconstructed and classified it in seconds…
Material Group
Shape Steel
Wire Rod
Tubing
Piping
Casing
Alloy Ingot
Manufacturer
Hyundai Automobile
Hyundai Railway
Hyundai Steel
Hyundai Ship
Hyundai Plant
Hyundai Electric
… …
Outside Diameter
✓
6 inches
8 inches
10 inches
12 inches
14 inches
Tubing ✓
✓ ✓
10” .375 X42 ERW DRL HYUNDAI W/FBE 14-1
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…when a cross industry vendor would have
misclassified it as this:
10” .375 X42 ERW DRL HYUNDAI W/FBE 14-1
Mainline Pipe x
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(cross-industry vendors often claim the whole process can be automated,
but to achieve 98+% accuracy, human expertise is required)
Raw Spend Data Rules Engine Expert Analyst Cleansed Data
And just to be sure, our energy experts verify all classifications
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It means you can expect things from us…
…that you could never get from a cross-industry vendor…
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…like no more time wasted on “data janitor work”…
…and no more anxiety over inaccurate reporting
Clean Data
Analyze
✓
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Plus, you’ll finally be able to manage all of your spend…
“For every dollar of spend under management,
Aberdeen has historically quantified 5% to 20%
cost savings”
…and save millions of dollars for your organization
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Ready to see what Best-in-Class Data can do for you?
Complete
All of your enterprise
data…
Accurate
…classified to a 98+%
degree of accuracy…
Repeatable
…kept up-to-date with
regular refreshes
Granular
…organized in useable,
natural buying groups…
Contact us and We’ll show you!