1) Building an effective demand-driven supply network (DDSN) is challenging due to the complexity of market information and the need to balance customer service and inventory levels.
2) A demand signal repository (DSR) is a data warehouse that stores retailer data, internal data, and third-party data to provide visibility and drive demand-driven insights. It supports functions like replenishment, demand planning, and account management.
3) Using real-time data from a DSR, companies can more accurately forecast demand, evaluate promotion effectiveness, and ensure product availability through logical replenishment policies.
Database Marketing, part two: data enhancement, analytics, and attribution Relevate
Part 2 of our 3-part series on database marketing where we will give you the roadmap you’ll need to successfully manage your marketing database for increased marketing success.
The webinar is presented by industry experts Andy Pappas, VP, Database Marketing & Analytics, and Tom Guernon, Director Sales.
You'll Learn:
-Data Enhancement: How external data and hygiene best practices can impact your programs
-How to employ Smart profiling for the best in audience selection for solicitation efforts
-Predictive Analytics including modeling and performance indicators to rank who is most likely to respond to your offers
-Campaign Attribution & Reporting: Common reporting functions and how to set these up to measure your campaign success
Equitec's production-based solutions are a result of the multidimensional data obtained from Consumer Dynamics, the company's proprietary information platform. By incorporating the consumer decision process (CDP) model with the Consumer Dynamics platform, similar variables can be recognized and analyzed to provide solutions for firms.
Database Marketing, part two: data enhancement, analytics, and attribution Relevate
Part 2 of our 3-part series on database marketing where we will give you the roadmap you’ll need to successfully manage your marketing database for increased marketing success.
The webinar is presented by industry experts Andy Pappas, VP, Database Marketing & Analytics, and Tom Guernon, Director Sales.
You'll Learn:
-Data Enhancement: How external data and hygiene best practices can impact your programs
-How to employ Smart profiling for the best in audience selection for solicitation efforts
-Predictive Analytics including modeling and performance indicators to rank who is most likely to respond to your offers
-Campaign Attribution & Reporting: Common reporting functions and how to set these up to measure your campaign success
Equitec's production-based solutions are a result of the multidimensional data obtained from Consumer Dynamics, the company's proprietary information platform. By incorporating the consumer decision process (CDP) model with the Consumer Dynamics platform, similar variables can be recognized and analyzed to provide solutions for firms.
Customer Analytics in Retail - Know Thy CustomersDhiren Gala
A solution to decode the mysterious ways in which customers move is closer than you think.
Customers are at the heart of any business. One unshakable rule of any business is to “know your customer.” In today’s business climate, this means using Business Intelligence (BI) to analyse complex customer data. With BI, companies can answer a wide range of critical questions about their customer base.
Life Sciences: Leveraging Customer Data for Commercial SuccessCognizant
As the healthcare buying process becomes increasingly complex, master data management solutions focused on customer relationships are critical for life sciences companies to excel.
SAP WHITEPAPER: Reacting in the Retail Moment, Analyzing Big Data in Real Tim...Beyond Technologies
Under any circumstances, retail is an extremely competitive industry. But today, an uncertain economy and low consumer confidence, coupled with shorter product lifecycles and well-informed, demanding customers, make it especially difficult to execute a profitable strategy.
Retailers have only a narrow window to make the sale and seize the opportunity. Thriving in this environment means maximizing the profit potential of each interaction, transaction, and customer contact.
Smarter campaign management engaging customers at point of maximum impactHolger Kyas
Abstract: In today’s data driven world, C2B organizations need to be innovative marketing leaders to succeed and create meaningful customer experiences. Companies who excel at this are using advanced analytics and “science fueled creativity” to engage their customers at the point of maximum impact. Hear from advanced analytics experts and leaders from Hilton Grand Vacations, Prolifics and IBM on how they are using intelligence to deliver smarter campaigns to positively affect their bottom line.
Executive Summary
Business-to-business (B2B) marketing automation systems are among the hottest sectors of the technology industry. Vendor revenues have grown at 50% per year since 2009 and will probably top $1 billion in 2014. Leading vendors including Eloqua, Marketo, and Pardot have been acquired or gone public at tremendous valuations. Major software companies including IBM, Oracle, Salesforce.com, Adobe, and Teradata have purchased B2B or business-to-consumer (B2C) marketing automation products. Venture capitalists have invested several hundred million dollars in start-ups and existing firms.
Yet, despite this growth, fewer than 20% of B2B marketers have purchased an integrated marketing automation system (although many more use email, Web analytics, and other component technologies). Even more alarming, many past buyers do not use their systems fully and a significant portion report little benefit from their investment.
The lesson of these statistics is not that marketing automation doesn’t work. The same studies show that the majority of users are satisfied and productive. Rather, the point is that marketing automation works only when marketers deploy their systems effectively. This How-To Guide will help to ensure that you are among the successful majority of B2B marketing automation buyers, not the unhappy remnant.
This 15-page guide includes the following sections:
What is B2B Marketing Automation?
Core Functions
Specialty Functions
Key Considerations
Vendor Landscape
Best Practices
Demand Metric's How-To Guides are designed to provide practical, on-the-job training and education and provide context for using our premium tools & templates. If there is a topic that you would like to see covered, please contact us at info@demandmetric.com (link sends e-mail) to make a content request.
As it incorporates a gamut of functions from business activity monitoring to performance management and business planning, business intelligence attracts a growing number of companies who earlier specialized in individual functions
Customer Analytics in Retail - Know Thy CustomersDhiren Gala
A solution to decode the mysterious ways in which customers move is closer than you think.
Customers are at the heart of any business. One unshakable rule of any business is to “know your customer.” In today’s business climate, this means using Business Intelligence (BI) to analyse complex customer data. With BI, companies can answer a wide range of critical questions about their customer base.
Life Sciences: Leveraging Customer Data for Commercial SuccessCognizant
As the healthcare buying process becomes increasingly complex, master data management solutions focused on customer relationships are critical for life sciences companies to excel.
SAP WHITEPAPER: Reacting in the Retail Moment, Analyzing Big Data in Real Tim...Beyond Technologies
Under any circumstances, retail is an extremely competitive industry. But today, an uncertain economy and low consumer confidence, coupled with shorter product lifecycles and well-informed, demanding customers, make it especially difficult to execute a profitable strategy.
Retailers have only a narrow window to make the sale and seize the opportunity. Thriving in this environment means maximizing the profit potential of each interaction, transaction, and customer contact.
Smarter campaign management engaging customers at point of maximum impactHolger Kyas
Abstract: In today’s data driven world, C2B organizations need to be innovative marketing leaders to succeed and create meaningful customer experiences. Companies who excel at this are using advanced analytics and “science fueled creativity” to engage their customers at the point of maximum impact. Hear from advanced analytics experts and leaders from Hilton Grand Vacations, Prolifics and IBM on how they are using intelligence to deliver smarter campaigns to positively affect their bottom line.
Executive Summary
Business-to-business (B2B) marketing automation systems are among the hottest sectors of the technology industry. Vendor revenues have grown at 50% per year since 2009 and will probably top $1 billion in 2014. Leading vendors including Eloqua, Marketo, and Pardot have been acquired or gone public at tremendous valuations. Major software companies including IBM, Oracle, Salesforce.com, Adobe, and Teradata have purchased B2B or business-to-consumer (B2C) marketing automation products. Venture capitalists have invested several hundred million dollars in start-ups and existing firms.
Yet, despite this growth, fewer than 20% of B2B marketers have purchased an integrated marketing automation system (although many more use email, Web analytics, and other component technologies). Even more alarming, many past buyers do not use their systems fully and a significant portion report little benefit from their investment.
The lesson of these statistics is not that marketing automation doesn’t work. The same studies show that the majority of users are satisfied and productive. Rather, the point is that marketing automation works only when marketers deploy their systems effectively. This How-To Guide will help to ensure that you are among the successful majority of B2B marketing automation buyers, not the unhappy remnant.
This 15-page guide includes the following sections:
What is B2B Marketing Automation?
Core Functions
Specialty Functions
Key Considerations
Vendor Landscape
Best Practices
Demand Metric's How-To Guides are designed to provide practical, on-the-job training and education and provide context for using our premium tools & templates. If there is a topic that you would like to see covered, please contact us at info@demandmetric.com (link sends e-mail) to make a content request.
As it incorporates a gamut of functions from business activity monitoring to performance management and business planning, business intelligence attracts a growing number of companies who earlier specialized in individual functions
Why retail companies need demand planning and forecastingSarah J
In this fast-paced world, customers want instant access to products, across all channels, at all times. Retail companies therefore need to precisely forecast and manage their inventory whilst meeting customer demands in this competitive marketplace
Why retail companies need demand planning and forecastingTarannum shaikh
In this fast-paced world, customers want instant access to products, across all channels, at all times. Retail companies therefore need to precisely forecast and manage their inventory whilst meeting customer demands in this competitive marketplace
Developing a customer data platform to provide omnichannel customer visibility for a retailer serving +100M households.
The Global Customer Insight team for one of the world's largest retailers, serving over 100M households, wanted to create a unified customer data platform to provide complete visibility across their customer's omnichannel touchpoints. Historically, the retailer had less than 50% visibility to their customer's omnichannel engagement. As a result, their analysis and data
scientists relied on data from multiple sources and legacy technology platforms to generate customer insights for stakeholders, resulting in reduced productivity, multi-day run-times, and incomplete insights
Learn more: https://www.tredence.com/services/customer-analytics
Intelligent database management: Your new sales allyMdAyubAnsari1
A centralised database can be of tremendous use while consolidating and processing raw data
Such a database can help sellers draw expert insights and create targeted campaigns
We explore the various ways through which centralised and intelligent database management can streamline and support sales operations
The digital-first lifestyle of customers today has made it imperative for businesses to opt for intelligent data synthesis and database management to sell effectively. Decoding dynamic buyer preferences, cross-referencing multiple buyer data points to deliver structured value propositions, understanding market segmentations, and getting a unified view of buyers – everything boils down to how a company handles its data.
Why opt for a centralised database
The key to systematic data synthesis is generating data using standardised techniques and incorporating best practices to process vast volumes of industry-segmented data. Consolidating raw data from multiple sources to create a centralised database can provide a complete view of the data of an organisation, equipping leaders to generate critical insights instantly. Sellers, when armed with such knowledge, can draw targeted campaigns to maximise sales.
There are several ways a centralised database can streamline operations in comparison to a distributed database.
Eliminating Redundancy: A centralised database can prevent unnecessary duplication of data and minimise the time taken to process large datasets. It also results in saving storage space.
Data Integrity: Centralised control of data can empower administrators to define integrity constraints and ensure regulatory compliance of data.
Security: The administrators can ensure that access to the database is through secure and approved channels, due to their absolute control over operational data. If access to sensitive data is attempted without prior approval, the administrators can define authorization checks for higher security.
Data Consistency: Companies can drastically cut down on inconsistent data by removing redundancies through centralised database management.
Enforcement of standards: With the centralization of data, administrators can establish and enforce the data standards, such as naming conventions, data quality standards, etc.
Reduced application development and maintenance time: A consolidated repository can support several processes that are common to various applications, such as retrieving data stored in the database to gain insights. This facilitates faster development of applications.
Portability: Such a database is easier to use when compared to dealing with multiple sources of data. Data is stored in one location and can be easily copied, reorganised, or ported to another location if need be. This method is cost-effective too as it minimises maintenance costs.
Intelligent Database Management
To ensure data enrichment of contact information, businesses need to set up multiple validation engines, both automated and man
Bridging the Gap Between Business Objectives and Data StrategyRNayak3
Explore the fundamental elements of a robust data strategy that aligns with business objectives, from defining goals to prioritizing data architecture.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
2. Getting the Intelligence to Build Demand-Driven Supply Networks
Introduction
Building an effective Demand-Driven Supply Network (DDSN) presents an ongoing challenge.
Most companies remain in the early phases of developing this business capability. The
necessary information on which strategies are based is very complex and can change quickly.
Businesses must not only respond quickly to market requirements such as demand, supply
variables, and seasonal trends, but also maintain a balance between high levels of customer
service and manageable inventory levels.
This paper identifies the challenges of building a Demand-Driven Supply Network, explains
how to use near-real-time data in an integrated Demand Signal Repository (DSR), and shares
examples of current successes and ideal states.
The Challenges of Building
a Demand-Driven Supply Network
A Demand-Driven Supply Network (DDSN) is designed to improve the responsiveness of a
company’s value chain. Some of the challenges of building an effective DDSN include an
improper understanding of consumer consumption, not enough IT resources, and outmoded
business practices around the tracking and use of Point of Sale (POS) scan data. A primary
objective is to use real-time POS consumption data to build a better DDSN.
Aligning Demand and Supply
with Consumer-Driven Planning
Aligning demand and supply with Consumer-Driven Planning means using real-time
consumption data to ascertain what is really happening in the marketplace, and creating an
effective and accurate forecast and plan to more accurately manage demand and supply.
Consumer-Driven Planning supports organizations in creating realistic and achievable sales
targets, developing detailed market intelligence, managing promotions more effectively, and
establishing optimal inventory levels for a maximum return on investment at stores and in
distribution across the value chain. In other words, it enables a company to establish a clear
and unified vision of current and future demand, so that it can develop an execution plan that
aligns all supply and sales processes around that vision.
Consumer-Driven Planning can help companies:
Eliminate Out-of-Stock (OOS) conditions.
Reduce safety stocks and remainders.
Decrease stock levels and inventory costs.
Cut unnecessarily long lead times.
Improve promotion effectiveness.
Increase customer service.
Drive down costs.
Connected Experiences for Consumer Goods March 2009 Page 2
3. Getting the Intelligence to Build Demand-Driven Supply Networks
Good demand planning requires communication among stakeholders across the organization,
particularly in the areas of marketing, sales, and supply chain management. Consumer-Driven
Planning enables effective collaboration between key individuals and departments, and helps
maintain the security of confidential information.
Building Business Efficiency
with a Demand Signal Repository
A Demand Signal Repository (DSR) is a powerful enterprise data warehouse that stores large
volumes of external and internal data that has been harmonized to provide visibility up and
down the supply network. It can also be used to feed line-of-business applications that
support DDSNs. A DSR stores retailer data, third-party data, and internal data in order to
drive demand-driven business insights across the value chain of stakeholders.
The following outlines some examples of these enterprise data sources.
Retailer Data Sources
Point of Sale Scan Data
Store and DCs Inventories
Planograms
Store Clusters
Retail Item Hierarchies
Events
Internal Data Sources
Sales
Promotions
Events
Item Hierarchies and Attributes
Store/Location Hierarchies
Forecasts
Shipments
Third-Party Data Sources
Syndicated Data
Weather Data
Map/Spatial Data
A DSR is an important building block of an efficient DDSN for the following reasons:
It is the central database for all demand data.
It harmonizes external data with internal line-of-business data to support
multidimensional analytics across the organization.
It supports cross-functional reporting and analysis with integrated demand analytics
embedded into critical spend areas such as trade promotion management.
It can be used to support business monitoring and trigger alerts for impending business
issues (for example, Retail Out of Stock).
Connected Experiences for Consumer Goods March 2009 Page 3
4. Getting the Intelligence to Build Demand-Driven Supply Networks
An effective DSR is extremely useful in gathering data from disparate sources. A DSR provides
item, location, and calendar harmonization for disparate data types—for example, POS data
from stores, warehouse withdrawal data, and syndicated data. It is the source of retail-specific
information for retail forecasts, store withdrawals, shipments, and planograms, providing
demand insight data on what customers bought within a category, and who they bought
it from.
The following image illustrates key trends in Consumer Packaged Goods (CPG) around DSR.
Making Better Business Decisions by Incorporating Near-Real-Time
Insights from the DSR into Functional Areas
Effective inventory planning and management depend on accurate sales forecasts. Detailed
consumption data from the DSR can be used to revitalize and improve the accuracy of
business planning around the following functions:
Replenishment
Demand Planning
Account Management
Category Management
By incorporating near-real-time demand data from the DSR into business planning and
management, companies can take into account the impact of a promotion and predict the
demand for new products. Factors such as trends and seasonality can also be incorporated
into the forecast.
Forecasts can easily be shared among stakeholders and updated on a regular basis. New sales
data and information about promotions, product launches, and discounts can be entered into
the program regularly. These regular updates help maintain the integrity of the forecast and
reduce overall statistical errors.
Connected Experiences for Consumer Goods March 2009 Page 4
5. Getting the Intelligence to Build Demand-Driven Supply Networks
Increasing Demand with Successful Promotions
Driving Accountable Marketing
An effective promotion can facilitate the successful launch of new products into the
marketplace. It can also have a dramatic impact on the demand for existing products.
This is why promotion management is an important part of the forecasting process.
By using the data from the DSR in combination with a consumer-driven approach, companies
can determine the best strategy for stimulating customer demand—for example, discounts,
special offers, or marketing campaigns. Through the evaluation of harmonized POS data from
the DSR, they can determine the impact of specific initiatives on such factors as sales volume,
product turnover, and margins, and then decide which products to promote through which
channels.
This enables planners to more accurately assess what is the right assortment and inventory
level of products along the distribution network, taking into account special promotions,
stock rotations, and constraints such as display space and allocation rules. This type of detailed
demand planning helps ensure that companies can meet their sales objectives and improve
margins.
Improving Field Intelligence by Combining Mobile Merchandising
and POS Sell-Through Analytics as an Integrated Retail Execution
Decision Cockpit
POS data from the DSR, when combined and harmonized with physical observations at the
shelf, can be used to drive a Retail Execution Decision Cockpit. This, in turn, can drive a
consumer-driven account planning approach that utilizes near-real-time demand
dashboards—part of a Retail Execution Decision Cockpit—to provide near-real-time
business insights that allow businesses to save time and resources.
The following image illustrates the concept of using DSR data in an integrated Retail
Execution BI portal.
Connected Experiences for Consumer Goods March 2009 Page 5
6. Getting the Intelligence to Build Demand-Driven Supply Networks
Ensuring Product Availability with Logical Replenishment Policies
Every business’s goal is to ensure that products are always available when and where they are
needed. The ideal situation is to make this happen while maintaining the minimum required
stock level, thus preventing unnecessary storage costs. Therefore, a sound replenishment
policy is an important component of demand-driven inventory planning.
With a sound replenishment policy driven by real consumer demand, a business can:
Reduce stock replenishment delivery costs.
Minimize inventory excess and increase stock turnover rates.
Reduce lost sales from stock-outs.
Respond quickly to market demands.
Good replenishment policies help businesses establish replenishment dates and quantities
for each warehouse and product, and synchronize the flow of products from production
warehouses, to distribution centers, all the way out to point of sale.
Changing the Game
As companies mature in their DDSN approach, they can leverage technology to change
the game and create significant competitive advantage. By leveraging the demand-sensing
capabilities provided by a DSR system, along with business knowledge they have gained,
companies can drive other business processes and thus productionalize their business insights.
For example, a business monitoring capability that utilizes predictive analytics can be
leveraged to watch for impending business issues, and automatically deliver alarms and alerts
to account managers and merchandisers when they occur. For example, the system can watch
for an impending retail Out-of-Stock (OOS) condition, and then send an automated alarm or
alert to the account manager or merchandiser responsible for servicing that specific retail
outlet. This then allows the merchandiser to respond proactively and thus prevent the OOS
condition from occurring.
As companies leverage their investment in developing DDSNs and the supporting
demand-sensing capability, they use technology to change the game. The can transform
their business and operation from being reactive to being more proactive.
Connected Experiences for Consumer Goods March 2009 Page 6
7. Getting the Intelligence to Build Demand-Driven Supply Networks
Demand-Sensing Maturity Model and Road Map
The ability to sense what is happening with the demand-side replenishment is critical
to success. An important key to building a successful Demand-Driven Supply Network
is adopting the technology and solutions according to a timeline that will not only
accommodate the current state, but also grow in value as new solutions are implemented.
The following image illustrates the four phases of a demand-driven organization.
It is important that a company consider the key decisions that must be made around the
technologies, architecture, and applications they will use to make better decisions. However,
the technology is only part of the solution. Building a successful DDSN can transform a
company in ways that require business and technology to unify. Uniting technology with
business strategy enables a company to maximize the value of DSR data and Consumer-Driven
Planning strategies. For this to be successful, it is usually necessary that there be role-based
decision cockpits leading the initiative. In general, the companies that most successfully
implement this strategy are those that view their DSR investment as a business
transformation project with a technological component.
Connected Experiences for Consumer Goods March 2009 Page 7
8. Getting the Intelligence to Build Demand-Driven Supply Networks
Basic Business Architecture, Current State, and Idea States Explored
Currently, most businesses have a combination of one-off solutions for both business strategy
and technology. This can result in difficulty in understanding and effectively using any data
harnessed by technology.
The following image illustrates downstream data analysis based on current state issues.
Consumer-Driven Planning and a DSR-based DDSN enable a company to streamline processes
across the chain, aligning data and attributes, uniting business and technology.
The following image illustrates a target state that incorporates DSR technology and
demand-driven business insights.
Connected Experiences for Consumer Goods March 2009 Page 8