Den Einkauf intelligenter machen durch volle …...Digital assistant for demand management, contract...
Transcript of Den Einkauf intelligenter machen durch volle …...Digital assistant for demand management, contract...
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1 © 2018 Ivalua, Inc. © 2018 Ivalua, Inc.
Den Einkauf intelligenter machen – durch volle Ausschöpfung des Potenzials von KI
BME Webinar / Oliver Oehmke / Senior Account Executive
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2 © 2018 Ivalua, Inc.
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3 © 2018 Ivalua, Inc.
AI is everywhere! Is it? Last week, while finishing preparing my presentation…
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AI & Procurement…
• AI, myths & legends…
• AI in procurement • what?
• why?
• how?
• Ivalua’s approach to AI…
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5 © 2018 Ivalua, Inc. © 2018 Ivalua, Inc.
AI myths & legends (& hype…)
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A dystopian future where machines enslave or kill us? (based on blockbuster movies, the answers looks like “yes”…)
Humans vs. Machines…
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Humans vs. Machines…
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Serious games…
1997
IBM’s Watson wins at Jeopardy agains champion Ken Jennings
2011
IBM’s Deep Blue wins over Kasparov at chess
2016
Google’s Alpha Go beats world Go champion Lee Sedol
2017
Libratus, an AI system beats four expert players of Texas Hold ‘Em poker
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Serious games… The evolution of AI is constant and rapid.
• Deep Blue was dumb but powerful. It was powered by brute-force human-created logic that would test and evaluate every possible sequence of moves at every turn and choose the best one.
• Watson had to be able to understand natural language questions and find the knowledge associated with them through encyclopedic recalls. But those questions are often nuanced and contain hidden, convoluted meanings that are hard to find, which made it even harder.
• Alpha Go had to learn from humans from thousands of past games because Go has more possible moves than the number of atoms in the universe, making it the most sophisticated board game in the world.
• 2nd generation of Alpha Go learnt by itself by playing against itself million of times to discover what works and what does not.
• Libratus also learnt by itself and also was equipped to understand other players’ behavior because poker is a game of luck, deception, and bluffing!
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Despite all of that, AI is still relatively dumb when compared to ALL what humans can do.
If it is all what you can do.
DEPTH
BREADTH
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Despite all of that, AI is still relatively dumb when compared to ALL what humans can do.
If it is all what you can do.
It is what AI can do… Narrow AI = can do 1 thing extremely well. Fails at everything else. DEPTH
BREADTH
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https://sloanreview.mit.edu/article/just-how-smart-are-smart-machines/
Despite all of that, AI is still relatively dumb when compared to ALL what humans can do.
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Demystifying AI = understand where we are, where we go! (to get the right level of expectations)
AI = Machine ability to understand, learn, and act on information and events designed to augment, provide assistance to or perform tasks independently from humans
AI stages Artificial Narrow Intelligence (ANI)
Execute specific
focused tasks without ability to self-expand
functionality
Artificial General Intelligence (AGI)
Perform broad tasks, reason,
and improve capabilities comparable to humans
Artificial Super Intelligence (ASI)
Demonstrate inteligence
beyond human capabilities
Timing Today In 20 yrs? Soon after AGI
Implications Outperform humans in specific repetitive
functions like driving, medical diagnosis,…
Compete with humans across all endeavors, such as earning
university degrees, and convincing humans that it is
human (Turing test).
Outperform humans, helping to achieve societal objectives or threatening
the human race.
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AI in procurement, what?
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AI is definitely on top of the agenda of most CPOs...
50% of mature supply
chains will use AI and advanced analytics for
planning.
By 2025, the artificial intelligence market will
surpass $100 billion.
AI will be a top five investment priority for more
than 30% of CIOs.
IDC Constellation Research
Gartner
45% of CPOs using or
piloting AI.
Deloitte
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Support for humans Repetitive task automation Context & learn
Analyze & understand structured data
Scenario for Sourcing decision/vendor mgmt/nego
Scoring model/algo for supplier perf.
ML for spend categorization and analysis/new knowledge/opportunity identifications, contract/transaction analysis for risk/fraud/opportunities…, Recommendations for CatMan, Sourcing, SRM,…
Analyze & understand unstructured data
NLP/chabots for basic query/request management
NLP/OCR for invoice processing, contract intelligence
Digital assistant for demand management, contract mgmt/mining
Perform digital tasks Smart workflows for vendor mgmt/onboarding, disputes/exceptions + older technology like P2P…
Blockchain/smart contracts for supply chain (& +) automation RPA for MDM and data cleansing/normalizing, PO/Invoice/Payment processing
Some examples…
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AI in procurement, why?
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“Automation ++”
Automation and gains in efficiencies are one of the key reasons why Procurement has been looking at technology since years.
So far, the focus was on tactical, manual, and repetitive tasks.
Smarter systems (AI,…) open new horizons for automation by making more complex tasks “automatable.”
They are in the cognitive space (analyze/decide/act)!
Smart Tech. penetration
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But there is more…
Simulation:
You are eating breakfast at home…
You have the radio on…
You hear that there was an earthquake in a region where you have several suppliers…
What do you do?
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Simulation…
You are eating breakfast at home…
You have the radio on…
You hear that there was an earthquake in a region where you have several suppliers…
What do you do?
Describe tasks/activities and give context on timing/systems used/people contacted…
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22 © 2018 Ivalua, Inc.
My own mock-up when exploring possibilities of Chatbots. Not related to IVALUA.
Now, imagine…
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Risk characteristics:
• Multiple sources (internal, external, geopolitics, nature,…)
• Real-time and always changing
VUCA: Volatility, Uncertainty, Complexity & Ambiguity
Too much data to apprehend in real time for us, humans!
Risk/incident management is a great example of where AI can be your best ally.
Characteritics of smart tech.:
• Watch (always on)
• Analyze massive sets of data (computational power)
• Develop insights (hidden correlations, new knowledge)
• Act / recommend
• Learn (from results or from correction by people)
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Procurement / supply chain on auto-pilot?
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Expectations of using AI in the context of Procurement…
Based on the simulation and all what we said so far, what expectations do you/your organization has/could have from AI?
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Effectiveness (better outcomes)
Big Data • Data cleansing
• Data collection
• Data analysis / crunching
Insights / Actionable intelligence • From descriptive to prescriptive
• Recommendations (opportunities, risks,…)
• Actions
AI in Procurement = from tech. as an “admin.” to tech. as a colleague or consultant.
Efficiency (less energy)
• More and smarter automation
• Query mgmt. / Digital assistant
• Context awareness / proactive
• Customization to each user
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AI in procurement, how?
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Challenges to AI (in Procurement)?
• What are the challenges?
• Ranking / importance of each challenge?
• What to do to address them?
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Some of the challenges for adoption of AI (in Procurement)
• Fears: future of work & jobs, machines taking over humans, black box…
• Strategic approach: buy-in / vision / roadmap / budget
• Maturity/unproven technology
• Regulations
• Data: • Availability, completeness
• Bias
• Skills & talent
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● Data quality remains poor (supplier master, spend, contract, invoice etc)
● Data silos across source-to-pay processes
● Data flows between procurement and ERP systems, often “out-of-sync”
The Potential is Enormous, but…
There are big roadblocks:
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Data hygiene isn’t a “nice to have”—it must be mandatory for every company taking a serious look at AI
• Perform extensive data cleansing activities: In many cases, the root of bias in AI systems sits in the data that feeds it. Enterprises must make sure their data is clean and fit for purpose.
• Train algorithms with varied data sets: Fueling algorithms with restricted data sets will focus the model too much on particular characteristics and will inevitably build a bias that misrepresents the environment.
• Investigate de-biasing tools: The range of tools and expertise is growing rapidly; enterprise leaders must bring in the brains and brawn they need to mitigate bias in their platforms using the raft of solutions in development and already available in the market.
• Create a culture of data ownership: Ensure data governance is in place, connect data creator and data consumer.
Data hygiene…
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The future of Procurement requires new skills
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33 © 2018 Ivalua, Inc. © 2018 Ivalua, Inc.
Ivalua’s approach to AI
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Ivalua enables its customers to build strong data foundations to get ready for AI…
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Data foundations…
Suppliers + BOM/Parts/Services + Org. (users/taxonomy) + Documents (Contracts, PR, PO, Inv.) + Internal data/KPIs + External data/KPIs
MASTERDATA TRANSACTIONS CONTEXT
360° view of supplier information and activity
(>> ERP, strategic and business not just tactical)
Agility & operational risk assessment & action
(Actionable intelligence)
Single, controlled source of truth
(You cannot manage what you cannot measure)
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36 © 2018 Ivalua, Inc.
Data foundations…
Suppliers + BOM/Parts/Services + Org. (users/taxonomy) + Documents (Contracts, PR, PO, Inv.) + Internal data/KPIs + External data/KPIs
MASTERDATA TRANSACTIONS CONTEXT
360° view of supplier information and activity
(>> ERP, strategic and business not just tactical)
Agility & operational risk assessment & action
(Actionable intelligence)
Single, controlled source of truth
(You cannot manage what you cannot measure)
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37 © 2018 Ivalua, Inc.
Data foundations…
Suppliers + BOM/Parts/Services + Org. (users/taxonomy) + Documents (Contracts, PR, PO, Inv.) + Internal data/KPIs + External data/KPIs
MASTERDATA TRANSACTIONS CONTEXT
360° view of supplier information and activity
(>> ERP, strategic and business not just tactical)
Agility & operational risk assessment & action
(Actionable intelligence)
Single, controlled source of truth
(You cannot manage what you cannot measure)
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38 © 2018 Ivalua, Inc.
Data foundations…
Suppliers + BOM/Parts/Services + Org. (users/taxonomy) + Documents (Contracts, PR, PO, Inv.) + Internal data/KPIs + External data/KPIs
+
Adoption by internal users (Procurement + Stakeholders)
+
Adoption by external partners
=
Compliance, visiblity, agility…
MASTERDATA TRANSACTIONS CONTEXT
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Data foundations… for better decisions!
Analytics Everywhere - The Power of A Connected Suite!
Real-time360° view on all “objects” (suppliers, parts, contracts, POs,…)
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Then, build AI capabilities on top of your strong data foundation…
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Our Strategy & Vision For AI (and our pragmatism…) Embed AI into core Ivalua Platform for Multiple Use Cases Across S2P
Unified Data Foundation
Supplier risk,
performance,
master data
Sourcing projects,
BOM & outcomes
Contract Data,
Clauses, Terms
Catalog, forecasts,
orders, receiving
data
Invoice, payment,
discount data Spend Data
Data Layer
Intelligence Layer Deep Learning NLP Machine Learning
Engagement Layer
Improve decision making for
all users by providing easy
access to relevant insights
Automate more tasks / work
in order to free capacity for
more strategic efforts
Enable a new and different
way to engage and interact
with solutions
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AI Roadmap
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Example of Robotic Process Automation (RPA) + AI: invoice data capture
• PO-Flip • Receipt-Flip • Web form • Integration
via EDI/cXML
• Scan/OCR
• PO-Flip • Receipt-Flip • Web form • Integration
via EDI/cXML
• Scan/OCR
• Automated, rules driven workflow Invoices matched appropriately are processed straight-through or else routed based on workflow configuration.
• Validate invoice data prior to processing Have suppliers or AP validate extracted invoice data with supplier information, PO or receipts and trigger onboarding for any new suppliers.
• Digitize paper and PDF instantly Capture and digitize data from PDF or scanned invoices instantly using OCR and machine learning.
• Machine learning for Invoice Data Capture Self-learning algorithm to accelerate the conversion and mapping of scanned invoices, and improve accuracy
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AI in our solution (today and plans for 2019)
Natural User Interface • Natural Language Understanding • Multi-intents • Adapted Answers • Multilingual, Multimodality (text, speech, ...)
Free Up Capacity with more automation • IDC Industrialization • Spend Classification • Supplier Deduplication
Contract Intelligence • Contract Analysis • Contract Data Capture
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Integrated Virtual
Assistant
An entirely new way to interact with your Procurement
application(s). IVA helps users make better, faster decisions.
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46 © 2018 Ivalua, Inc.
IVA – Your Integrated Virtual Assistant
This multi-faceted virtual assistant lives on the Ivalua Platform and interacts
with users in natural language. Iva will be able to…
Retrieve information
on spend, suppliers, transactions +
Instantly create/edit shopping cart,
requisitions, expense reports +
Generate quick insight charts to display data
Search web for relevant information,
e.g., pricing
Image recognition
Provide “How-To” guidance for users
Understand voice commands and actions via Amazon
Alexa (e.g., approve/reject)
*Above is still in development and all the use cases above may not be available in version 1 of the virtual assistant
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48 © 2018 Ivalua, Inc. © 2018 Ivalua, Inc.
Conclusion…
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Summary (Source = McKinsey)
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Humans vs. Machines… A zero-sum game…
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Humans + Machines… A win-win…
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52 © 2018 Ivalua, Inc.
Procurement people, live long and prosper
Technology to augment, not replace people.
Robots will make jobs more human.
Cooperation between humans and machines will get us to where we have never been before!
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