Far too often, Supply Chain management leaders make decisions in a data vacuum. But that doesn’t work in today’s fast-paced market. Rob Van Driel (Solutions Consultant, Anaplan) explained why & how Supply Chain leaders need to make timely, value-based decisions so you can respond quickly to shifts in demand and customer needs. Because: when value is king, margins are optimized, and profit is maximized.
Presented by Rob Van Driel, Solutions Consultant Anaplan on Supply Chain 4.0 : ready to operate in the digital era? (29 Nov, 2018)
A simple, straight forward set of 25 slides which provides the basics of S&OP (Sales & Operations Planning) from concept to implementation. (Used to introduce and discuss S&OP concepts with clients and prospective clients.) S&OP is also know as IBF or IBP (IBF = Integrated Business Forecasting; IBP = Integrated Business Planning)
Microsoft Data Platform - What's includedJames Serra
The pace of Microsoft product innovation is so fast that even though I spend half my days learning, I struggle to keep up. And as I work with customers I find they are often in the dark about many of the products that we have since they are focused on just keeping what they have running and putting out fires. So, let me cover what products you might have missed in the Microsoft data platform world. Be prepared to discover all the various Microsoft technologies and products for collecting data, transforming it, storing it, and visualizing it. My goal is to help you not only understand each product but understand how they all fit together and there proper use case, allowing you to build the appropriate solution that can incorporate any data in the future no matter the size, frequency, or type. Along the way we will touch on technologies covering NoSQL, Hadoop, and open source.
Learn how to harness the power of data through Microsoft Fabric to accelerate your AI capabilities for growth and scale.
What You'll Learn
Introduction to Microsoft Fabric: Understand the basics of Microsoft Fabric and its role in revolutionizing data management and analytics.
Exploring Microsoft Fabric's Features: Dive into the core functionalities and components that make Microsoft Fabric a powerful tool in data management.
Microsoft Fabric in Business: Discover how Microsoft Fabric transforms business processes, enhancing efficiency and decision-making with advanced data solutions.
Evolution of Data Management: Learn about the shift from traditional data management to dynamic, integrated solutions offered by Microsoft Fabric.
Microsoft Fabric Live in Action: Experience Microsoft Fabric firsthand through a live demo, illustrating its practical applications in real-world business scenarios.
AVATA is adding to their express solutions suite with “IBP express”, a hosted service offering that provides the framework for conducting the S&OP/IBP process with supported dashboard reports and KPI’s. IBP express will allow for a rapid deployment enabling your first S&OP/IBP cycle within 90-days.
IBP express is both a technology tool and service offering that supports advancing your current S&OP process or implementing S&OP/IBP for the first time. IBP express includes the required Education, Workshops, Coaching & Technology that will deliver a rapid ROI.
In this session, Sergio covered the Lakehouse concept and how companies implement it, from data ingestion to insight. He showed how you could use Azure Data Services to speed up your Analytics project from ingesting, modelling and delivering insights to end users.
Apache Kafka and the Data Mesh | Ben Stopford and Michael Noll, ConfluentHostedbyConfluent
Data mesh is a relatively recent term that describes a set of principles that good modern data systems uphold. A kind of “microservices” for the data-centric world. While the data mesh is not technology-specific as a pattern, the building of systems that adopt and implement data mesh principles have a relatively long history under different guises.
In this talk, we share our recommendations and picks of what every developer should know about building a streaming data mesh with Kafka. We introduce the four principles of the data mesh: domain-driven decentralization, data as a product, self-service data platform, and federated governance. We then cover topics such as the differences between working with event streams versus centralized approaches and highlight the key characteristics that make streams a great fit for implementing a mesh, such as their ability to capture both real-time and historical data. We’ll examine how to onboard data from existing systems into a mesh, modelling the communication within the mesh, how to deal with changes to your domain’s “public” data, give examples of global standards for governance, and discuss the importance of taking a product-centric view on data sources and the data sets they share.
Companies today can now drive the future of their business within and across departments at the strategic, tactical, and operational levels without having to compromise on usability, flexibility, ease of model changes, and the speed to assess the impact of business decisions and planning scenarios.
Connected Planning breaks down information silos to eliminate any inefficiencies among financial planning, corporate planning, and operational planning.
A simple, straight forward set of 25 slides which provides the basics of S&OP (Sales & Operations Planning) from concept to implementation. (Used to introduce and discuss S&OP concepts with clients and prospective clients.) S&OP is also know as IBF or IBP (IBF = Integrated Business Forecasting; IBP = Integrated Business Planning)
Microsoft Data Platform - What's includedJames Serra
The pace of Microsoft product innovation is so fast that even though I spend half my days learning, I struggle to keep up. And as I work with customers I find they are often in the dark about many of the products that we have since they are focused on just keeping what they have running and putting out fires. So, let me cover what products you might have missed in the Microsoft data platform world. Be prepared to discover all the various Microsoft technologies and products for collecting data, transforming it, storing it, and visualizing it. My goal is to help you not only understand each product but understand how they all fit together and there proper use case, allowing you to build the appropriate solution that can incorporate any data in the future no matter the size, frequency, or type. Along the way we will touch on technologies covering NoSQL, Hadoop, and open source.
Learn how to harness the power of data through Microsoft Fabric to accelerate your AI capabilities for growth and scale.
What You'll Learn
Introduction to Microsoft Fabric: Understand the basics of Microsoft Fabric and its role in revolutionizing data management and analytics.
Exploring Microsoft Fabric's Features: Dive into the core functionalities and components that make Microsoft Fabric a powerful tool in data management.
Microsoft Fabric in Business: Discover how Microsoft Fabric transforms business processes, enhancing efficiency and decision-making with advanced data solutions.
Evolution of Data Management: Learn about the shift from traditional data management to dynamic, integrated solutions offered by Microsoft Fabric.
Microsoft Fabric Live in Action: Experience Microsoft Fabric firsthand through a live demo, illustrating its practical applications in real-world business scenarios.
AVATA is adding to their express solutions suite with “IBP express”, a hosted service offering that provides the framework for conducting the S&OP/IBP process with supported dashboard reports and KPI’s. IBP express will allow for a rapid deployment enabling your first S&OP/IBP cycle within 90-days.
IBP express is both a technology tool and service offering that supports advancing your current S&OP process or implementing S&OP/IBP for the first time. IBP express includes the required Education, Workshops, Coaching & Technology that will deliver a rapid ROI.
In this session, Sergio covered the Lakehouse concept and how companies implement it, from data ingestion to insight. He showed how you could use Azure Data Services to speed up your Analytics project from ingesting, modelling and delivering insights to end users.
Apache Kafka and the Data Mesh | Ben Stopford and Michael Noll, ConfluentHostedbyConfluent
Data mesh is a relatively recent term that describes a set of principles that good modern data systems uphold. A kind of “microservices” for the data-centric world. While the data mesh is not technology-specific as a pattern, the building of systems that adopt and implement data mesh principles have a relatively long history under different guises.
In this talk, we share our recommendations and picks of what every developer should know about building a streaming data mesh with Kafka. We introduce the four principles of the data mesh: domain-driven decentralization, data as a product, self-service data platform, and federated governance. We then cover topics such as the differences between working with event streams versus centralized approaches and highlight the key characteristics that make streams a great fit for implementing a mesh, such as their ability to capture both real-time and historical data. We’ll examine how to onboard data from existing systems into a mesh, modelling the communication within the mesh, how to deal with changes to your domain’s “public” data, give examples of global standards for governance, and discuss the importance of taking a product-centric view on data sources and the data sets they share.
Companies today can now drive the future of their business within and across departments at the strategic, tactical, and operational levels without having to compromise on usability, flexibility, ease of model changes, and the speed to assess the impact of business decisions and planning scenarios.
Connected Planning breaks down information silos to eliminate any inefficiencies among financial planning, corporate planning, and operational planning.
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
A business-friendly approach to data governance is imperative to engage all users and accommodate diverse business use cases spanning analytics, operational improvements, and compliance requirements. To increase adoption and collaboration, business and technical data users across your organisation need to have a common, agreed-upon, and documented understanding of which data is most important, what it’s called, and where it’s used.
Watch this on-demand webinar, where we explore the concept of business-first Data Governance, an approach that promotes adoption by the organisation, lays the foundation for data integrity and consistently delivers business value in the long term.
We also look at how Oripharm, one of the dynamic healthcare players in the Nordics and international markets, choose a data governance solution:
• to improve personalisation of products and services
• to achieve accurate and timely credit-risk analysis
• to increase user productivity by improving time-to-insights
• to mitigate risk and facilitate regulatory compliance and reporting
Speakers:
Mikkel Holmgaard - Data Governance Lead, Orifarm
Emily Washington - Sr. Vice President, Product Management, Precisely
A presentation on the OrchestratedBEER brewery management software solution for craft breweries. Presentation covers OBeer features & functions, company history, brewery challenges, and a technical overview of the ERP lifecycle
Sales and Operations Planning (S&OP) OverviewMichael Ryan
Improved revenues, business performance, and customer satisfactions are outcomes of a strong Sales and Operations Planning (S&OP) process.
S&OP can be applied to a variety of industries, from cosmetics to aftermarket parts manufacturers.
Webinar: Decoding the Mystery - How to Know if You Need a Data Catalog, a Dat...DATAVERSITY
There’s a lot of confusion out there about the differences between a data catalog, a data dictionary and a business glossary, and it's not always easy to understand who needs which and why. Join Malcolm Chisholm, Ph.D., President of Data Millennium, and Amichai Fenner, Product Lead at Octopai, as they help decode the mystery. Spoiler alert: one of these enables collaboration across BI and IT, which is it?
Sales & Operations Planning (S&OP) and integrated business planning (IBP) align demand, supply and finance, allowing a holistic view across all departments so that businesses can test the financial impact of different “what if” options and respond to unplanned events--both positive and negative. Visit http://www.steelwedge.com/resources/s-and-op-intro
Kafka for Live Commerce to Transform the Retail and Shopping MetaverseKai Wähner
Live commerce combines instant purchasing of a featured product and audience participation.
This talk explores the need for real-time data streaming with Apache Kafka between applications to enable live commerce across online stores and brick & mortar stores across regions, countries, and continents in any retail business.
The discussion covers several building blocks of a live commerce enterprise architecture, including transactional data processing, omnichannel, natural language processing, augmented reality, edge computing, and more.
Data Architecture Best Practices for Advanced AnalyticsDATAVERSITY
Many organizations are immature when it comes to data and analytics use. The answer lies in delivering a greater level of insight from data, straight to the point of need.
There are so many Data Architecture best practices today, accumulated from years of practice. In this webinar, William will look at some Data Architecture best practices that he believes have emerged in the past two years and are not worked into many enterprise data programs yet. These are keepers and will be required to move towards, by one means or another, so it’s best to mindfully work them into the environment.
S&OP is a monthly global process to balance supply and demand, bringing all business operational plans into one integrated plan. All activities is based on a common Forecast data set. The ultimate target for S&OP therefore is to balance Supply and Demand.
Architecting Agile Data Applications for ScaleDatabricks
Data analytics and reporting platforms historically have been rigid, monolithic, hard to change and have limited ability to scale up or scale down. I can’t tell you how many times I have heard a business user ask for something as simple as an additional column in a report and IT says it will take 6 months to add that column because it doesn’t exist in the datawarehouse. As a former DBA, I can tell you the countless hours I have spent “tuning” SQL queries to hit pre-established SLAs. This talk will talk about how to architect modern data and analytics platforms in the cloud to support agility and scalability. We will include topics like end to end data pipeline flow, data mesh and data catalogs, live data and streaming, performing advanced analytics, applying agile software development practices like CI/CD and testability to data applications and finally taking advantage of the cloud for infinite scalability both up and down.
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Modernizing to a Cloud Data ArchitectureDatabricks
Organizations with on-premises Hadoop infrastructure are bogged down by system complexity, unscalable infrastructure, and the increasing burden on DevOps to manage legacy architectures. Costs and resource utilization continue to go up while innovation has flatlined. In this session, you will learn why, now more than ever, enterprises are looking for cloud alternatives to Hadoop and are migrating off of the architecture in large numbers. You will also learn how elastic compute models’ benefits help one customer scale their analytics and AI workloads and best practices from their experience on a successful migration of their data and workloads to the cloud.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
A business-friendly approach to data governance is imperative to engage all users and accommodate diverse business use cases spanning analytics, operational improvements, and compliance requirements. To increase adoption and collaboration, business and technical data users across your organisation need to have a common, agreed-upon, and documented understanding of which data is most important, what it’s called, and where it’s used.
Watch this on-demand webinar, where we explore the concept of business-first Data Governance, an approach that promotes adoption by the organisation, lays the foundation for data integrity and consistently delivers business value in the long term.
We also look at how Oripharm, one of the dynamic healthcare players in the Nordics and international markets, choose a data governance solution:
• to improve personalisation of products and services
• to achieve accurate and timely credit-risk analysis
• to increase user productivity by improving time-to-insights
• to mitigate risk and facilitate regulatory compliance and reporting
Speakers:
Mikkel Holmgaard - Data Governance Lead, Orifarm
Emily Washington - Sr. Vice President, Product Management, Precisely
A presentation on the OrchestratedBEER brewery management software solution for craft breweries. Presentation covers OBeer features & functions, company history, brewery challenges, and a technical overview of the ERP lifecycle
Sales and Operations Planning (S&OP) OverviewMichael Ryan
Improved revenues, business performance, and customer satisfactions are outcomes of a strong Sales and Operations Planning (S&OP) process.
S&OP can be applied to a variety of industries, from cosmetics to aftermarket parts manufacturers.
Webinar: Decoding the Mystery - How to Know if You Need a Data Catalog, a Dat...DATAVERSITY
There’s a lot of confusion out there about the differences between a data catalog, a data dictionary and a business glossary, and it's not always easy to understand who needs which and why. Join Malcolm Chisholm, Ph.D., President of Data Millennium, and Amichai Fenner, Product Lead at Octopai, as they help decode the mystery. Spoiler alert: one of these enables collaboration across BI and IT, which is it?
Sales & Operations Planning (S&OP) and integrated business planning (IBP) align demand, supply and finance, allowing a holistic view across all departments so that businesses can test the financial impact of different “what if” options and respond to unplanned events--both positive and negative. Visit http://www.steelwedge.com/resources/s-and-op-intro
Kafka for Live Commerce to Transform the Retail and Shopping MetaverseKai Wähner
Live commerce combines instant purchasing of a featured product and audience participation.
This talk explores the need for real-time data streaming with Apache Kafka between applications to enable live commerce across online stores and brick & mortar stores across regions, countries, and continents in any retail business.
The discussion covers several building blocks of a live commerce enterprise architecture, including transactional data processing, omnichannel, natural language processing, augmented reality, edge computing, and more.
Data Architecture Best Practices for Advanced AnalyticsDATAVERSITY
Many organizations are immature when it comes to data and analytics use. The answer lies in delivering a greater level of insight from data, straight to the point of need.
There are so many Data Architecture best practices today, accumulated from years of practice. In this webinar, William will look at some Data Architecture best practices that he believes have emerged in the past two years and are not worked into many enterprise data programs yet. These are keepers and will be required to move towards, by one means or another, so it’s best to mindfully work them into the environment.
S&OP is a monthly global process to balance supply and demand, bringing all business operational plans into one integrated plan. All activities is based on a common Forecast data set. The ultimate target for S&OP therefore is to balance Supply and Demand.
Architecting Agile Data Applications for ScaleDatabricks
Data analytics and reporting platforms historically have been rigid, monolithic, hard to change and have limited ability to scale up or scale down. I can’t tell you how many times I have heard a business user ask for something as simple as an additional column in a report and IT says it will take 6 months to add that column because it doesn’t exist in the datawarehouse. As a former DBA, I can tell you the countless hours I have spent “tuning” SQL queries to hit pre-established SLAs. This talk will talk about how to architect modern data and analytics platforms in the cloud to support agility and scalability. We will include topics like end to end data pipeline flow, data mesh and data catalogs, live data and streaming, performing advanced analytics, applying agile software development practices like CI/CD and testability to data applications and finally taking advantage of the cloud for infinite scalability both up and down.
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Modernizing to a Cloud Data ArchitectureDatabricks
Organizations with on-premises Hadoop infrastructure are bogged down by system complexity, unscalable infrastructure, and the increasing burden on DevOps to manage legacy architectures. Costs and resource utilization continue to go up while innovation has flatlined. In this session, you will learn why, now more than ever, enterprises are looking for cloud alternatives to Hadoop and are migrating off of the architecture in large numbers. You will also learn how elastic compute models’ benefits help one customer scale their analytics and AI workloads and best practices from their experience on a successful migration of their data and workloads to the cloud.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Management Information System (MIS) Project - Lotus Thread Company Limited & ...Parth Gajjar
This document tackles two critical business challenges through the lens of case studies:
Case Study 1: Optimizing Distribution Networks - Lotus Thread Company Limited (LTCL)
This section delves into the well-known case study of LTCL, a thread manufacturer grappling with optimizing its distribution network. The case likely presents a scenario where LTCL needs to choose from various distribution options.
Case Study 2: IT System Adoption at Bharat Petroleum Corporation Limited (BPCL)
The second case study focuses on BPCL, a major Indian oil corporation, and its adoption of a new IT system.
------------------------------------------------------------------------
Whether you need a presentation for a business meeting, a sales pitch, or an educational lecture, I can create a custom design that meets your specific needs and goals.
Contact me today to discuss your next presentation project!
Parth Gajjar
[Whatsapp : https://wa.me/+918238231270]
[https://iconventurecompany.com/]
[www.linkedin.com/in/iparthgajjar]
Speeding up the Supply Chain requires a new Supply Chain Planning approach - Enhanced User Experience
Introduce state-of-the art user experience with communication capabilities (SAP JAM) and MS Excel Spreadsheets.
Built on SAP HANA
Demand Networks require real-time monitoring and a focus on short-term planning
Basic Learning outcomes of my SCM-310: Intro to SAP ERP course
The planning, operations and business process and functions that make up an ERP software. The applications and useful advantages of ERP. Practicals of SAP
Data science in demand planning - when the machine is not enoughTristan Wiggill
A presentation by Calven van der Byl BCom Economics and Statistics, BCom Honours Mathematical Statistics, Masters Mathematical Statistics, Inventory Optimization Demand Planning Manager, DSV, South Africa.
Delivered during SAPICS 2016, a leading event for supply chain professionals, held in Sun City, South Africa.
Demand Planning is a complex, yet often de-emphasized function in the supply chain planning function. The demand planning function is often characterized by an over-reliance on off the shelf software as well as a great deal of manual intervention. This presentation will outline the current developments and perspective in big data analytics and how they can be leveraged with the demand planning function to improve forecasting agility and efficiency. A simulation study will be presented in order to illustrate these principles in practice.
Gazelle has forecasting and supply planning modules along with web based interface for sales person and supplier login.
The forecasting module can generate the forecast based on 180 statistical models which can be moderated upon.
This forecasted demand can be used to generate a daily supply plan.
It is a complete planning tool and stores all data, and can take care back orders, truck loads, without any customization.
It can be integrated with SAP for automatic data pull.
Our supply chain solutions have saved our customers upto 10% of their supply chain costs on a practical basis. This has been achieved through:
Business forecasting solutions like Oracle Demantra, Avercast and LookAhead – improved forecasting accuracy upto 95% that has reduced inventory holding costs.
Network optimization and dispatch planning solutions like Supply Chain Guru – has reduced supply chain cost to serve per unit by upto 35% of the product cost.
Supply Chain Planning solutions like Avercast and Oracle, that have reduced excess safety stock through inventory optimization.
Manufacturing, a slow-adopter of Analytics, is now catching up in leaps and bounds. Across all business domains, applying analytics is providing answers to the most critical questions of the business.With exponential expansion of data, data driven insights have become a strategic necessity.
This booklet explores a few use cases of Big Data for manufacturing and how it can be leveraged.
For more info visit: https://www.teamcomputers.com/businessanalytics/Manufacturing/Booklet-Manufacturing-Digital.pdf
Similar to Towards connected planning for Supply Chain (20)
#bluecruxtalks crash course - Part 4 - Technology Stack StrategyBluecrux
Your expectations from your APS are too high. If you think it will solve your supply chain challenges, think twice.
Typically, Supply Chain Managers aim toward operational excellence and end-to-end visibility by implementing advanced planning solutions with the intention of:
- Seeing all the incoming demand and splitting work accordingly
- Planning resources more effectively
- Making better decisions faster to avoid shortages or reduce bottlenecks
But your APS cannot do it all on its own.
A broader technology stack needs to be embedded around your APS to get effective E2E digital transformation around your supply chain transformation processes.
Check out the final part of our #bluecruxtalks crash course and learn which type of solutions can augment your APS capabilities and how.
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Supply Chain Managers are still continously challenged with local shortages and balancing inventory even when using advanced planning systems.
When facing local shortages, Supply Chain Planners must wait for all the data to be collected and analyzed in Excel, to paint a picture in many cases with lagging data and wait for the right person and/or organization to approve changes to the original plan… but the shortage is still there.
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Part of the answer lies in (a lot of) live data and organizational change.
Want to learn in detail how you can build the next generation of planning processes?
Then check out the slide deck of the third session in our #bluecruxtalks crash course, where we discuss next-generation planning processes.
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In today’s world, Supply Chain Planners are under higher pressure to wear more hats inside the organization. They are expected to:
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In this fourth and final session of our APS transformation series, we want to share what we’ve seen in the industry. We’ll give insight into what your peers perceive as core capabilities part of the APS suite and supporting activities that best find their home in other, best-of-breed solutions.
Are you ready to build the best-in-class planning technology stack with a solid business case together? We are!
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4. Driving a new age of
connected planning
2011
commercial launch
20 offices
in 13 countries
75%+ FY17
subscription
revenue growth
(FYE January)
1000+
employees
in 14 countries
900+ customers
in over 40 countries
Partners
Best-in-class
250+
apps
Patented
in-memory data
engine
$120M FY17
total revenue
momentum
6. Barriers that needs to be addressed:
Organizational
Silos
• Lack of visibility
• Sharing of Data
Data
• Inconsistency
• Quality
• Reconcile
Flexibility
• Dynamic changes
• Varying timeframes
• Different planning
levels
Technology
• Manually intensive
• Alignment tools
Workflow
• Different planning
horizons & cycle
times
• In ability to quickly
change pans
7. legacy vs Anaplan
ERP system
MES system
Transportation management system
Warehouse management system
MRP system
HCM tool
Microsoft (Excel®)
Financial planning system
CRM tool
S&OP
Management
reports
Inventory
management
MPS
Forecasting
tool
Strategic
pricing tool
Supply
optimization
tool
Order
fulfillment
tool
Single, secure
source of planning
and decision data
Greater
collaboration, deeper
insights,
faster alignment
Dynamic,
continuous planning
for any area of your
business
Across one
department or area
Across the company
One business process
9. “Anaplan gave us speed and agility.”
RK Del Rosario, Supply Chain Planning Manager
ANAPLAN FOR CONNECTED PLANNING
Days slashed from routine
planning processes
CHALLENGES
• Legacy tools took up to 6 hours to run some
operations
• Planners used inaccurate averages, resulting in
imprecise forecasts
• Process failures resulted in lost sales and excess
inventory
RESULTS
• Two-week planning process was cut to two days
• A five-day revision process now takes five
minutes
• Channel, SKU, and customer profitability are
available monthly
11. Step 1: connect supply chain planning data and processes
Transportation
management system
ERP system
MES system CRM tool
Warehouse
management system
Microsoft (Excel®)HCM toolMRP system
Financial planning
system
Benefits:
• Automated integration
• Single Repository
• Visual representation of data
• Network visibility
12. Step 2: Connect people and plans across the organization
Demand
Signal
ManagementTrade
Promotions
Management
Demand
Management
Planning
Dashboards
Collaborative
Planning
Statistical
Forecasting
Sales
Forecasting CRM
Pipeline
Management
NPI/EOL
Forecasting
Financial
Forecasting
Marketing
Forecasts
Demand
Shaping
Demand Analyst
Marketing
Account Management
Sales management
Demand Planning
Controller
Rough-Cut
Capacity
Plan
Supplier
Plan
Sourcing
Plan
Planning
Dashboards
Capacity
Plan
(Constraints)
Consensus
Demand
Plan Capacity
Plan
(Resources)
Allocations
Plan
Inventory
Plan
Materials
Planning
Master
Production
Schedule
Procurement
Plan
Production Manager
Supply Planner
Inventory Manager
Master Planner
Distribution Manager
Warehouse Manager
Consensus
Planning
Executive
S&OP
Demand Planning
Supply Planning
Decision
Benefits:
• Complete profitability analysis
• Better anticipate market changes
• Real time implications supply chain
decisions have on corporate strategy
• Improve service levels
13. Step 3: Collaboration Across The Network
Raw Material
Suppliers
Contracted
Producers
Transportation Distribution
Center
Warehouse Customer
Channel
CustomersProduction
Facilities
3rd Party
Logistics
Channel
Partners
Transportation
Benefits:
• Visibility across all extend network events
• Immediate action due to deviations extended network
• ‘What if’ scenarios including suppliers and customer
• Better support omni-channel
14. Connected Planning Creates Value
Plan demand for tens of thousands of
SKUs globally
Consumer Products Manufacturer
Reduced Planning Cycle Time 80% (2
weeks to 2 days)
Food & Beverage Manufacturer
Improved forecast accuracy by 15%
Food & Beverage Manufacturer
Reduced functional FTE requirement for
impacted processes by 40%
High Tech Manufacturer
Reduced Order Processing Time 70%
from 7 to 2 Days and increased capacity
by 150%
High Tech Manufacturer
Effectively Planned 55% incremental
demand and revenue via new bundles
High Tech Manufacturer
1.5% sustained increase in Net
Income
Global Apparel Manufacturer
Reduced inventory on hand by an
estimated $100M
Global Apparel Manufacturer
Increased EBIT 25+% over 3 years
Global C&IP Manufacturer
Intelligent
Self-learning, Insightful,
Predictive, Cognitive
Collaborative
Networked, Inclusive,
Distributed, Accessible
Dynamic
Real-time, Responsive,
Flexible, Fast
16. Intelligent Planning Roadmap
Optimization
• Fully integrated into
Anaplan UI
• Optimal – Feasible problem
• Gurobi Solver Engine
Machine Learning/AI
• POCs with Google Cloud and
other partners
Predictive
• Currently available 26
algorithms
• Examples: Linear regression,
Exponential smoothing,
Erlang, Holt-Winters
Optimization
• Future versions to include all
major problem types
• Multivariable linear
regression
Machine Learning/AI
• Leverage ML/AI algorithms
and models for planning data
Immediate Term Future
This content is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decision.
17. Connected
Network
Planning
• Collaborative Planning across the supply network
• Dynamic and Continuous Planning and Optimization
• Intelligent, Faster and better decisions
Machine
Learning
Algorithms
Continuous
Optimization
Leading Edge Innovative Technology
18. Component of Function
that can be changed.
e.g., unit volume
Optimization Problem Definition
Objective Variable Constraint
Maximize or minimize
the value of some
function, F(x1,x2…xn)or
Determine Feasibility
e.g., maximize profit
Constraints on
individual x’s and/or
combinations of x’s
e.g., production
capacity
19. Using only model based line
items and formulas, the
optimizer does not require any
specific modeling skills.
Optimizer Highlights
UI DRIVEN MODEL BASED FAST CALCULATION
Problem definition relies on a
simple, Anaplan standard UI to
give more flexibility to users.
Gurobi is the fastest
optimization engine on the
market. Because the operation
locks the model, it’s a
prerequisite for the optimizer
to be fast.
This content is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decision.
20.
21. ML POC: Large Beverage Company
POC Hypothesis: Determine if forecast improvements could be achieved
to yield COGS savings and associated SCM benefits
Scope: Apply ML on POS data over 8-10 weeks
Result: ML yielded a 15% improvement in forecast accuracy projected
to save $2M in COGS for the sample of products in the study.
Benefits: Targeted areas to apply the result
• Financial forecasting at granular levels
• Better allocate marketing spend across brands
• Trade promotions and marketing event planning that lift sales up
Additional downstream benefits through SCM
• Reduced Safety Stock Investment
• Reduced Expired and Obsolete Products
• Reduced Working Capital
22. ML POC: large CPG/consumer healthcare company
Result:
• more accurate forecasts than stat models in 79% of cases
• On average ML yielded 24% MAPE (vs. industry avg. of 36-40%)
• potentials of $4.1M in savings.
• $1.7M by addressing some of the missed sales
• $2.4M in efficient inventory management
Opportunities: Operating cost savings with improvements in sales prediction
by:
• Forecasting at granular level
• Optimizing supply planning on top of ML results
$4.1MSavings for 6 weeks in forecast accuracy
24. ML Model Performance
(Illustrative with one product example)
• ML models (with any combination of data) performing consistently better than stat models
• Granularity of forecasting ability (at UPC-DC level) shows models can be tuned to yield better result for
individual product or brand
25. Anaplan PlatformUsers Google Cloud Platform Data Sources
POS
ML POC Solution Architecture
Financial
Forecasting
Demand
Planning
Others
Data
Hub
External
Data
Shipping
Promotions
Big Query
Machine
Learning
Cloud
Storage
26. 26
• A connected planning approach results in better, more
collaboratively created plans that are resilient in the
face of change
• Anaplan is a unique platform to develop, integrate,
reconcile, refine, and manage plans
• Anaplan capabilities can be implemented quickly using
agile processes
• Anaplan is highly scalable and supports very complex,
financial, product and supply chain planning models
Key takeaways
Questions