Predictive analytics tools can provide deeper insights into business data by predicting future outcomes and trends. While these tools have potential benefits, many are difficult for most business users to employ as they require statistical or programming skills. SAP's BusinessObjects Predictive Workbench aims to overcome these limitations with an easy to use visual interface that integrates with existing BI solutions. It allows business users rather than just analysts to uncover patterns in data and share predictive findings to help inform business decisions.
Today there is a lot of buzz around customer experience. Many companies have realized that investments in customer experience improvement is important not just because it helps to boost the bottom lines of their businesses but because it takes at least 4 to 6 times more cost to acquire a new customer than to retain an existing customer.
Acquire Grow & Retain customers - The business imperative for Big DataIBM Software India
The emergence of Big Data and Analytics has changed the way marketing decisions are made. Marketing has moved away from traditional ‘generalisation’ practices such as customer segmentation, geographical targeting etc. and is focussing more on the individual – the ‘Chief Executive Customer’.
How An AI-Powered Trade Promotion Optimization Software Can Improve Consumer ...Gina Shaw
Artificial Intelligence (AI) will happen in both TPx and Retail Execution sooner than you probably think – Promotion Optimization Institute
According to Nielsen Holdings, 40% of Consumer Goods trade promotion spending doesn’t drive the desired results. Even though the trade promotions spend take up a lion’s share of the organizational revenue, traditionally manufacturers have always struggled in optimizing their promotion mix for the maximum bang for the buck.
With the advancements in AI technologies, it is now possible to powerfully harness data and run high-yield trade promotions.
What You Can Expect From The eBook?
1. Key Trade Promotion Optimization (TPO) challenges faced today
2. What is AI in the context of TPO?
3. How AI helps run profitable trade promotions?
4. What an AI-Powered analysis looks like?
5. Case-studies
6. How you can get started right away!
CGT Research May 2013: Analytics & InsightsCognizant
A new survey conducted by Consumer Goods Technology (CGT) and sponsored by Cognizant explores how consumer goods companies are approaching data management strategies and usage.
Moving Forward with Big Data: The Future of Retail AnalyticsBill Bishop
Out new report Moving Forward with Big Data: The Future of Retail Analytics goes deeper into new territory that's relevant to changes taking place across retailing.
It calls out significant progress in the past 9 months.
• The definition of big data has grown beyond technical, i.e. “what it is,” to include “what it does.”
• A lot more companies are executing big data projects (an increase from < 20% to now 65% of sample respondents).
• Most of the focus is on driving top line growth.
The document provides an overview of SurveyMonkey as a company that powers engagement with customers, employees, and markets through its People Powered Data platform. It discusses SurveyMonkey's massive footprint with over 2 million active users, its strong brand awareness, and powerful business model driven by viral growth. The document also summarizes SurveyMonkey's strategy of selling directly to enterprises, accelerating growth through its Teams product, and expanding internationally, and highlights its healthy financial results including 17% revenue growth in Q1 2019.
The document provides an overview of SurveyMonkey as a company and discusses its business model, growth opportunities, and financial highlights. It describes SurveyMonkey's mission to power individuals and organizations with people powered data to measure, benchmark and act on opinions. SurveyMonkey has over 17.5 million active users and serves customers, employees, and the market with its survey platform and solutions. The company is pursuing three primary growth drivers: selling directly to enterprises, accelerating growth in self-serve teams, and expanding internationally. SurveyMonkey is driving healthy revenue growth, has a highly visible subscription business model, and generates strong cash flow and retention rates.
Today there is a lot of buzz around customer experience. Many companies have realized that investments in customer experience improvement is important not just because it helps to boost the bottom lines of their businesses but because it takes at least 4 to 6 times more cost to acquire a new customer than to retain an existing customer.
Acquire Grow & Retain customers - The business imperative for Big DataIBM Software India
The emergence of Big Data and Analytics has changed the way marketing decisions are made. Marketing has moved away from traditional ‘generalisation’ practices such as customer segmentation, geographical targeting etc. and is focussing more on the individual – the ‘Chief Executive Customer’.
How An AI-Powered Trade Promotion Optimization Software Can Improve Consumer ...Gina Shaw
Artificial Intelligence (AI) will happen in both TPx and Retail Execution sooner than you probably think – Promotion Optimization Institute
According to Nielsen Holdings, 40% of Consumer Goods trade promotion spending doesn’t drive the desired results. Even though the trade promotions spend take up a lion’s share of the organizational revenue, traditionally manufacturers have always struggled in optimizing their promotion mix for the maximum bang for the buck.
With the advancements in AI technologies, it is now possible to powerfully harness data and run high-yield trade promotions.
What You Can Expect From The eBook?
1. Key Trade Promotion Optimization (TPO) challenges faced today
2. What is AI in the context of TPO?
3. How AI helps run profitable trade promotions?
4. What an AI-Powered analysis looks like?
5. Case-studies
6. How you can get started right away!
CGT Research May 2013: Analytics & InsightsCognizant
A new survey conducted by Consumer Goods Technology (CGT) and sponsored by Cognizant explores how consumer goods companies are approaching data management strategies and usage.
Moving Forward with Big Data: The Future of Retail AnalyticsBill Bishop
Out new report Moving Forward with Big Data: The Future of Retail Analytics goes deeper into new territory that's relevant to changes taking place across retailing.
It calls out significant progress in the past 9 months.
• The definition of big data has grown beyond technical, i.e. “what it is,” to include “what it does.”
• A lot more companies are executing big data projects (an increase from < 20% to now 65% of sample respondents).
• Most of the focus is on driving top line growth.
The document provides an overview of SurveyMonkey as a company that powers engagement with customers, employees, and markets through its People Powered Data platform. It discusses SurveyMonkey's massive footprint with over 2 million active users, its strong brand awareness, and powerful business model driven by viral growth. The document also summarizes SurveyMonkey's strategy of selling directly to enterprises, accelerating growth through its Teams product, and expanding internationally, and highlights its healthy financial results including 17% revenue growth in Q1 2019.
The document provides an overview of SurveyMonkey as a company and discusses its business model, growth opportunities, and financial highlights. It describes SurveyMonkey's mission to power individuals and organizations with people powered data to measure, benchmark and act on opinions. SurveyMonkey has over 17.5 million active users and serves customers, employees, and the market with its survey platform and solutions. The company is pursuing three primary growth drivers: selling directly to enterprises, accelerating growth in self-serve teams, and expanding internationally. SurveyMonkey is driving healthy revenue growth, has a highly visible subscription business model, and generates strong cash flow and retention rates.
The document provides an overview of SurveyMonkey as a company that powers engagement through collecting feedback from customers, employees, and the market. It highlights SurveyMonkey's large user base and brand awareness, growing enterprise business, and opportunities in adjacent markets. SurveyMonkey's platform allows organizations to understand perspectives through surveys and use the collected data to drive business decisions.
SurveyMonkey provides an enterprise-grade solution for collecting feedback data through online surveys. It has a massive footprint with over 17 million active users and 4,800 enterprise customers. SurveyMonkey aims to help organizations transform feedback into business intelligence to drive growth. Its powerful business model is fueled by virality and expanding customer relationships. SurveyMonkey sees a large market opportunity in helping organizations understand customers, employees, and markets through its people powered data platform and solutions.
Bi24 whitepaper Bi24 - How legal firms can harness the power of analyticsDavid Ricketts
The document discusses how legal firms are employing business analytics to improve their sales performance in an increasingly competitive market. It outlines how new entrants are offering lower-cost services, putting pressure on traditional firms to overhaul their operations and prioritize business development. Analytics provides opportunities for firms to gain better visibility into sales data and track metrics like customer behavior and retention. When integrated into a CRM system, analytics can help firms develop targeted marketing strategies and sales processes. The document provides examples of how analytics reports can optimize activities like opportunity evaluation, campaign effectiveness, and predictive client spending.
The six-step guide outlines how to break through the analytics barrier and fully realize the benefits of analytics programs. The six steps are: 1) define customer experience outcomes, 2) integrate a big data infrastructure, 3) rethink the customer journey, 4) enhance insights with digital data and processes, 5) construct solutions from the customer perspective, and 6) test and measure for outcomes. Following these steps helps move analytics initiatives beyond operational reporting to enabling predictive insights that improve the customer experience.
The document describes several client challenges and how data analytics solutions helped address them. Specifically, it discusses how analytics tools helped:
1) A mini-market compete against a larger supermarket by analyzing transaction data and identifying top selling items. This increased quarterly sales by 10%.
2) A healthcare organization recover over $975k in overpayments by identifying high-risk claims through predictive analytics.
3) A healthcare payer improve patient health tracking and medication compliance, leading to reduced hospitalization and the highest quality rating.
Big Data's Big Payday Whitepaper_FINALChuck Taylor
Marketers are approaching a tipping point in 2015 where most will see a return on their investments in big data solutions for the first time. Survey results from the past three years show that marketers have made steady progress in using data to drive marketing. In 2015, over half of marketers expect to see positive ROI from these investments. Marketers who are already seeing ROI tend to invest more in data, be more optimistic about personalization efforts, and rely on more diverse sources of customer data than those who have not realized returns yet. Continued investment in data and demonstrating ROI internally will be important for success in 2015 according to the survey results.
This document discusses how The Data People helps companies identify their best customers and maximize profits through data-driven strategies and analytics. They analyze customer data to build detailed profiles, identify valuable customer segments, predict churn, and develop targeted marketing strategies. Case studies show how they helped companies like Alliance & Leicester increase website visits by 100% through improved targeting, and helped Nescafe launch a successful direct marketing campaign by creating an accurate customer profile model.
Nucleus Research found organizations can earn an incremental ROI of 241 percent by using Big Data capabilities to examine large and complex data sets. One driver of high returns was the ability to improve business processes and decisions by increasing the types of data that can be analyzed.
Arun Gupta, Customer Care Associate and Group Chief Technology Officer, Shoppers Stop presented at the Premier Business Leadership Series 2010, http://www.sas.com/theserieshk.
With many retailers worldwide struggling to maintain revenues, how do you grow in such a tough competitive landscape? As a leading Indian retailer and pioneer in using technology, especially business analytics, Shoppers Stop is not only thriving but has helped revolutionise the retail sector. Gupta will share insights on using analytics to drive business value, reduce operational costs and provide better products and customer experience.
The document discusses key questions to consider when evaluating a marketing intelligence platform. It begins by explaining that most marketers still rely on multiple disconnected data sets and analytics tools that are difficult to use. The top questions to ask are: 1) Can the platform consolidate all marketing data? 2) Can it clean and standardize the data? 3) Can it deliver accurate customer segmentation based on long-term customer behavior? For most companies, a third-party cloud-based marketing intelligence platform is the best option to gain valuable customer insights.
How Pharma Can Fully Digitize Interactions with Healthcare ProfessionalsCognizant
This document discusses how pharmaceutical companies can fully digitize their interactions with healthcare professionals (HCPs). It notes that HCPs are increasingly using digital technologies and prefer engaging with pharmaceutical companies through digital channels. The document recommends that pharmaceutical companies build an end-to-end digital platform to facilitate various types of virtual interactions with HCPs, including web conferences, email marketing, e-detailing apps, social media management, and more. It emphasizes the importance of collecting and analyzing HCP interaction data across channels to develop a unified, customer-centric view of each HCP in order to better understand and serve their needs and preferences for digital engagement over time.
Analytical CRM - Ecommerce analysis of customer behavior to enhance sales Shrikant Samarth
Task: You are required to choose a dataset (or related datasets) in an area of interest suitable for analyzing customer relationships.
Approach: Topic is chosen – Customer behavior Analysis in Ecommerce Industry for Enhancing Sales. Brazilian E-commerce public dataset was downloaded, cleaned and performed multiple regression in SPSS to check the relationship between the dependent variable and multiple independent variables.
Findings: Customer can be retained if the product delivered in time and if there is a delay in the product delivery, it is a duty of a seller to inform the customer for the same. The payment method has proven to be an important parameter to enhance sales over a period of time. analysis suggests on-time delivery, flexibility in payment method and good customer service would help the seller to gain customer trust which would help them to convert more sales.
Tools: IBM SPSS , Excel (pivot tables and charts), Tableau
Analytics For Retail Banking - MarketelligentMarketelligent
MarketIntelligent provides analytic services to help clients make better business decisions. They offer expertise in credit risk and marketing analytics across various banking products. Their services include developing scorecards to predict customer behavior, maximize profits from assets and fees, reduce losses, acquire profitable customers, increase activation and cross-sell revenues.
How Artificial Intelligence is Impacting Marketing Today and How Smart Market...Mark Osborne
Overview of Artificial Intelligence AI and Machine Learning technologies that are impacting marketing today, and how marketers can plan their career and build the relevant computer science / engineering / statistics / and data-driven decision-making skills to excel in the future. Covers relevant algorithms, and marketing strategies like segmentation, targeting, and positioning, and how marketers can prepare
When_will_Marketers_be_promoted_to_the_boardroomJo Lane
Marketers are well positioned to benefit from big data due to their skills and focus on customers, but they need to establish ownership over big data analysis to fully capitalize. Currently big data ownership is shared across marketing, IT, and dedicated big data teams. For marketers to gain influence, they must be specifically trained in big data analysis and clearly communicate how it will meet business objectives. As more companies adopt big data, it will become central to strategic decision making and increase marketers' status within their organizations.
The document summarizes predictions from retail analysts for key trends in 2011. Mobile technologies like mobile web, coupons, and apps will be important for retailers. Customer data analytics will also be crucial to help retailers better understand customers and optimize inventory, merchandising and marketing. Social media and customer relationship management tools will be further integrated into retailers' cross-channel strategies to improve the customer experience. Business intelligence applications will also help retailers make more customer-centric decisions using customer data.
Whitepaper: Ventana Research - Sales Compensation ManagementIconixx
Ventana Research undertook this benchmark research to determine the attitudes, requirements and future plans of those who engage in sales compensation management and to identify the best practices of organizations that are the most mature in it.
Intelligent Integrated Marketing for Car DealersRalph Paglia
The document describes Left Brain Marketing Planning, a new approach to marketing resource allocation that is customer-focused, data-driven, and aims to deliver high returns on investment. It notes that traditional marketing planning fails to account for changing consumer behaviors and media consumption. Left Brain Marketing Planning uses analytical tools and experimental design principles to determine which marketing resources best influence customers at different points in their purchase journey, rather than focusing primarily on media buys. Examples of companies adopting aspects of this approach are provided.
Business analytics has many applications across different business functions and sectors including finance, marketing, HR, customer relationship management, manufacturing, and credit card companies. Some key uses of business analytics include using financial data to determine pricing and advise on investment performance, analyzing customer behavior and demographics to improve marketing strategies, predicting employee retention and attrition rates to inform HR practices, and examining customer transactions to help retail and credit card companies target customers. Marketing analytics specifically helps evaluate the effectiveness of marketing efforts, optimize campaigns, improve customer targeting, and support real-time decision making. While business analytics provides benefits, organizations also face challenges of data integration, selecting appropriate metrics, and ensuring privacy. HR analytics applications include measuring employee performance, informing promotion and salary decisions
Business analytics can help organizations make better decisions by applying analytical techniques to business problems. While many organizations collect large amounts of data, few systematically analyze this data to improve decision making. Common approaches used by organizations to enhance decisions include analytics, testing hypotheses with data, and improving data quality. Business analytics frameworks provide tools to leverage more information for strategic and operational decisions.
The document provides an overview of SurveyMonkey as a company that powers engagement through collecting feedback from customers, employees, and the market. It highlights SurveyMonkey's large user base and brand awareness, growing enterprise business, and opportunities in adjacent markets. SurveyMonkey's platform allows organizations to understand perspectives through surveys and use the collected data to drive business decisions.
SurveyMonkey provides an enterprise-grade solution for collecting feedback data through online surveys. It has a massive footprint with over 17 million active users and 4,800 enterprise customers. SurveyMonkey aims to help organizations transform feedback into business intelligence to drive growth. Its powerful business model is fueled by virality and expanding customer relationships. SurveyMonkey sees a large market opportunity in helping organizations understand customers, employees, and markets through its people powered data platform and solutions.
Bi24 whitepaper Bi24 - How legal firms can harness the power of analyticsDavid Ricketts
The document discusses how legal firms are employing business analytics to improve their sales performance in an increasingly competitive market. It outlines how new entrants are offering lower-cost services, putting pressure on traditional firms to overhaul their operations and prioritize business development. Analytics provides opportunities for firms to gain better visibility into sales data and track metrics like customer behavior and retention. When integrated into a CRM system, analytics can help firms develop targeted marketing strategies and sales processes. The document provides examples of how analytics reports can optimize activities like opportunity evaluation, campaign effectiveness, and predictive client spending.
The six-step guide outlines how to break through the analytics barrier and fully realize the benefits of analytics programs. The six steps are: 1) define customer experience outcomes, 2) integrate a big data infrastructure, 3) rethink the customer journey, 4) enhance insights with digital data and processes, 5) construct solutions from the customer perspective, and 6) test and measure for outcomes. Following these steps helps move analytics initiatives beyond operational reporting to enabling predictive insights that improve the customer experience.
The document describes several client challenges and how data analytics solutions helped address them. Specifically, it discusses how analytics tools helped:
1) A mini-market compete against a larger supermarket by analyzing transaction data and identifying top selling items. This increased quarterly sales by 10%.
2) A healthcare organization recover over $975k in overpayments by identifying high-risk claims through predictive analytics.
3) A healthcare payer improve patient health tracking and medication compliance, leading to reduced hospitalization and the highest quality rating.
Big Data's Big Payday Whitepaper_FINALChuck Taylor
Marketers are approaching a tipping point in 2015 where most will see a return on their investments in big data solutions for the first time. Survey results from the past three years show that marketers have made steady progress in using data to drive marketing. In 2015, over half of marketers expect to see positive ROI from these investments. Marketers who are already seeing ROI tend to invest more in data, be more optimistic about personalization efforts, and rely on more diverse sources of customer data than those who have not realized returns yet. Continued investment in data and demonstrating ROI internally will be important for success in 2015 according to the survey results.
This document discusses how The Data People helps companies identify their best customers and maximize profits through data-driven strategies and analytics. They analyze customer data to build detailed profiles, identify valuable customer segments, predict churn, and develop targeted marketing strategies. Case studies show how they helped companies like Alliance & Leicester increase website visits by 100% through improved targeting, and helped Nescafe launch a successful direct marketing campaign by creating an accurate customer profile model.
Nucleus Research found organizations can earn an incremental ROI of 241 percent by using Big Data capabilities to examine large and complex data sets. One driver of high returns was the ability to improve business processes and decisions by increasing the types of data that can be analyzed.
Arun Gupta, Customer Care Associate and Group Chief Technology Officer, Shoppers Stop presented at the Premier Business Leadership Series 2010, http://www.sas.com/theserieshk.
With many retailers worldwide struggling to maintain revenues, how do you grow in such a tough competitive landscape? As a leading Indian retailer and pioneer in using technology, especially business analytics, Shoppers Stop is not only thriving but has helped revolutionise the retail sector. Gupta will share insights on using analytics to drive business value, reduce operational costs and provide better products and customer experience.
The document discusses key questions to consider when evaluating a marketing intelligence platform. It begins by explaining that most marketers still rely on multiple disconnected data sets and analytics tools that are difficult to use. The top questions to ask are: 1) Can the platform consolidate all marketing data? 2) Can it clean and standardize the data? 3) Can it deliver accurate customer segmentation based on long-term customer behavior? For most companies, a third-party cloud-based marketing intelligence platform is the best option to gain valuable customer insights.
How Pharma Can Fully Digitize Interactions with Healthcare ProfessionalsCognizant
This document discusses how pharmaceutical companies can fully digitize their interactions with healthcare professionals (HCPs). It notes that HCPs are increasingly using digital technologies and prefer engaging with pharmaceutical companies through digital channels. The document recommends that pharmaceutical companies build an end-to-end digital platform to facilitate various types of virtual interactions with HCPs, including web conferences, email marketing, e-detailing apps, social media management, and more. It emphasizes the importance of collecting and analyzing HCP interaction data across channels to develop a unified, customer-centric view of each HCP in order to better understand and serve their needs and preferences for digital engagement over time.
Analytical CRM - Ecommerce analysis of customer behavior to enhance sales Shrikant Samarth
Task: You are required to choose a dataset (or related datasets) in an area of interest suitable for analyzing customer relationships.
Approach: Topic is chosen – Customer behavior Analysis in Ecommerce Industry for Enhancing Sales. Brazilian E-commerce public dataset was downloaded, cleaned and performed multiple regression in SPSS to check the relationship between the dependent variable and multiple independent variables.
Findings: Customer can be retained if the product delivered in time and if there is a delay in the product delivery, it is a duty of a seller to inform the customer for the same. The payment method has proven to be an important parameter to enhance sales over a period of time. analysis suggests on-time delivery, flexibility in payment method and good customer service would help the seller to gain customer trust which would help them to convert more sales.
Tools: IBM SPSS , Excel (pivot tables and charts), Tableau
Analytics For Retail Banking - MarketelligentMarketelligent
MarketIntelligent provides analytic services to help clients make better business decisions. They offer expertise in credit risk and marketing analytics across various banking products. Their services include developing scorecards to predict customer behavior, maximize profits from assets and fees, reduce losses, acquire profitable customers, increase activation and cross-sell revenues.
How Artificial Intelligence is Impacting Marketing Today and How Smart Market...Mark Osborne
Overview of Artificial Intelligence AI and Machine Learning technologies that are impacting marketing today, and how marketers can plan their career and build the relevant computer science / engineering / statistics / and data-driven decision-making skills to excel in the future. Covers relevant algorithms, and marketing strategies like segmentation, targeting, and positioning, and how marketers can prepare
When_will_Marketers_be_promoted_to_the_boardroomJo Lane
Marketers are well positioned to benefit from big data due to their skills and focus on customers, but they need to establish ownership over big data analysis to fully capitalize. Currently big data ownership is shared across marketing, IT, and dedicated big data teams. For marketers to gain influence, they must be specifically trained in big data analysis and clearly communicate how it will meet business objectives. As more companies adopt big data, it will become central to strategic decision making and increase marketers' status within their organizations.
The document summarizes predictions from retail analysts for key trends in 2011. Mobile technologies like mobile web, coupons, and apps will be important for retailers. Customer data analytics will also be crucial to help retailers better understand customers and optimize inventory, merchandising and marketing. Social media and customer relationship management tools will be further integrated into retailers' cross-channel strategies to improve the customer experience. Business intelligence applications will also help retailers make more customer-centric decisions using customer data.
Whitepaper: Ventana Research - Sales Compensation ManagementIconixx
Ventana Research undertook this benchmark research to determine the attitudes, requirements and future plans of those who engage in sales compensation management and to identify the best practices of organizations that are the most mature in it.
Intelligent Integrated Marketing for Car DealersRalph Paglia
The document describes Left Brain Marketing Planning, a new approach to marketing resource allocation that is customer-focused, data-driven, and aims to deliver high returns on investment. It notes that traditional marketing planning fails to account for changing consumer behaviors and media consumption. Left Brain Marketing Planning uses analytical tools and experimental design principles to determine which marketing resources best influence customers at different points in their purchase journey, rather than focusing primarily on media buys. Examples of companies adopting aspects of this approach are provided.
Business analytics has many applications across different business functions and sectors including finance, marketing, HR, customer relationship management, manufacturing, and credit card companies. Some key uses of business analytics include using financial data to determine pricing and advise on investment performance, analyzing customer behavior and demographics to improve marketing strategies, predicting employee retention and attrition rates to inform HR practices, and examining customer transactions to help retail and credit card companies target customers. Marketing analytics specifically helps evaluate the effectiveness of marketing efforts, optimize campaigns, improve customer targeting, and support real-time decision making. While business analytics provides benefits, organizations also face challenges of data integration, selecting appropriate metrics, and ensuring privacy. HR analytics applications include measuring employee performance, informing promotion and salary decisions
Business analytics can help organizations make better decisions by applying analytical techniques to business problems. While many organizations collect large amounts of data, few systematically analyze this data to improve decision making. Common approaches used by organizations to enhance decisions include analytics, testing hypotheses with data, and improving data quality. Business analytics frameworks provide tools to leverage more information for strategic and operational decisions.
Business analytics can be useful in personal decision making, like choosing a chair for the home. Factors like price, style, comfort, and reviews can be analyzed to identify the best option. Customer ratings and comments give insights into other people's experiences. This helps make an informed choice accounting for preferences and needs. Analytics provides objectivity that improves decision quality compared to relying only on subjective opinions.
The document discusses the rise of prescriptive analytics and its importance. Prescriptive analytics provides recommendations on what actions companies should take based on insights generated from descriptive and predictive analytics. It uses optimization and simulation algorithms to find solutions and recommend actions. There is high demand for prescriptive analytics as it allows companies to take quick actions based on data instead of just analyzing past data. The document then provides examples of industries using prescriptive analytics like oil and gas to optimize fracking and healthcare to improve facilities and reduce costs.
Business intelligence (BI) provides employees with information to make better business decisions. By giving employees access to strategic information from across the organization through a single access point, they can improve the quality of their decisions. This leads to lower costs through improved operational efficiency, reduced inventory costs, and leveraging existing IT investments. Revenue can also be increased by negotiating better contracts and identifying the most profitable customers and products. Overall, BI empowers employees and creates an agile organization that can more effectively meet business objectives.
MKT574 v1Strategic Marketing PlanMKT574 v1Page 6 of 6IlonaThornburg83
This document contains a strategic marketing plan for an unnamed company. It includes an analysis of internal and external data sources to evaluate the company's performance and market opportunities. It also outlines objectives to expand into a new target market segment and increase sales and customer loyalty. Marketing tactics are proposed, including customized products, promotions, and customer relationship programs. Metrics are defined to monitor progress towards the objectives.
Best Metrics to Optimize B2B Demand GenAsad Haroon
B2B marketers who need to do more than simply create brand awareness through outbound marketing have adopted Account Based Marketing (ABM) in order to focus on key accounts. Successful ABM campaigns can produce highly qualified, valuable prospects.
- The document discusses the growing importance of data analytics and business intelligence for organizations. It notes that most companies now see analytics as critical to their success.
- It also discusses the shift towards decentralizing analytics and giving more business users direct access to data and insights. This allows leaders across departments to make more informed, data-driven decisions.
- Specifically, the document focuses on how enhanced analytics can help improve channel management strategies. It notes that channel operations are often complex with data residing in different systems, making performance difficult to analyze. Better analytics is needed to understand channel performance and costs.
Marketing Assignment Help | Marketing Assignment Help with Onlineassignemnt.net Online
The document provides guidelines for conducting an online survey for a DVD rental company. It begins by outlining the objective of the survey, which is to determine the level of competition in the DVD rental market and customer satisfaction with existing services. It then designs a survey with questions about how respondents first learned about the company, how many times they have used the rental service, and their satisfaction levels. The document concludes by stating the survey will be emailed to 25 respondents and the results will be analyzed.
The Most Important Metrics You’re Not Tracking (Yet).pdfMussadaq Rauf
A growing number of organizations are becoming more customercentric
by adopting, measuring, and optimizing CPIs — Customer Performance
Indicators. These are the metrics that customers care about, as opposed to the
ones that the company cares...
The new ‘A and B’ of the Finance Function: Analytics and Big Data - -Evolutio...Balaji Venkat Chellam Iyer
Published in 2013, this White Paper discusses how the finance function would evolve with the combined forces of Big Data and Analytics and the levers that could help catalyze the change and has drawn upon the Global Trend Study conducted by Tata Consultancy Services (TCS) on how companies were investing in Big Data and deriving returns from it.
Business analytics refers to using data, statistics, and business intelligence tools to gain insights into past business performance and drive business planning. In banking and finance, analytics can be used to improve operational efficiencies, products and services, marketing, customer retention, develop new investment strategies, and reduce risk. Some examples of how analytics helps banking and finance include analyzing customer-facing employee performance to improve customer experience, tracking revenue streams to determine profitable products and services, using customer data to tailor offerings to better meet customer needs and promote loyalty, and detecting fraudulent activities to reduce risk.
1. Retail businesses can boost customer loyalty by leveraging customer data insights from business intelligence tools and advanced analytics to create personalized shopping experiences.
2. These tools allow retailers to better understand customer purchasing behaviors and trends in order to develop targeted marketing strategies, promotions, and loyalty programs.
3. Implementing analytics helps retailers identify their most profitable customers, improve customer retention, and control costs of loyalty programs.
Demand forecasting is becoming more data-driven and accurate due to improvements in data storage, processing, and predictive analytics technologies. Companies can now better sense consumer demand patterns, shape future demand through marketing strategies, and respond accordingly. This new approach of sensing, shaping, and responding to demand is called demand-driven forecasting. It allows companies to more precisely measure the impact of factors like price, advertising, and promotions on demand.
Giving and Getting provides an online platform for people to help each other through favors in exchange for tokens. This report proposes marketing strategies to target specific audiences for Giving and Getting's three products: Free registration, Data Option, and White Label Option. The strategies aim to increase visibility, engagement, and retention. Tactics include optimizing the website, email marketing, and using social media. Key performance indicators such as conversion rate, visitor loyalty, and response speed will help measure the effectiveness of the strategies. Implementing the recommendations could help Giving and Getting establish itself more prominently.
How to Leverage the Power of Data Analytics in Sales?Shaily Shah
Data is the DNA behind the robust analytics and insights supporting modern organizations to recognize new products, determine how to serve customers better, and enhance operational efficiencies.
The Role Of Data Analytics In Franchise Management SoftwareMeetbrandwide
1) Franchise management software provides analytics capabilities that allow franchises to identify trends and patterns in order to optimize performance and drive profitability.
2) Analytics help both franchisors and franchisees by providing insights into key metrics, benchmarks, and opportunities for growth based on financial and operational data.
3) Regular collection and analysis of various data sources through franchise management software enables timely decision-making and implementation of changes to enhance business performance.
Revenue Operations Analytics: A Strategic BlueprintKwanzoo Inc
The true value in your KPIs is understanding how they complete the bigger picture of the customer journeys that drive the most impact for your business.
How to Predict Buying Behavior using Machine Learning PythonDiagsense ltd
Forecasting and predicting buying behavior using machine learning Python fosters strategic decision-making and customer-centric approaches. With implements like Diagsense, businesses can amplify predictive capabilities, refining marketing strategies, and foster customer satisfaction. This dynamic synergy equips companies to navigate evolving markets successfully, ensuring sustained growth and adaptability.
Business intelligence (BI) is a system of tools and methods that aid in strategic planning and informed decision-making. This involves collecting data from internal and external sources, analyzing the data to gain insights, and visualizing insights for decision makers. BI helps organizations understand customer behavior, improve products and efficiency, gain competitive advantages, improve sales and marketing, and gain visibility across the organization. Determining if an organization needs BI involves assessing if the organization has data but no useful information, relies solely on IT for reports, or uses spreadsheets without dedicated BI software. Tracking the right metrics like quantitative vs qualitative, actionable vs vanity, reporting vs exploratory, correlated vs causal, and lagging vs leading metrics helps organizations focus on what
Similar to Expanding BIs role by including Predictive Analytics (20)
El documento presenta un modelo de administración de capacidad propuesto por CAM-I. El modelo clasifica la capacidad en tres categorías: ociosa, no productiva y productiva. Además, divide cada categoría en subcategorías específicas. El modelo integra mediciones operativas con métricas financieras para proveer una visión completa de la capacidad y apoyar la toma de decisiones.
Activity Based Profitability ManagementMiguel Garcia
Activity Based Profitability Management (ABPM) and Activity Based Budgeting (ABB) offers organizations a complete tool to gain a competitive advantage and provides crucial information to support the process of making strategic and operational decisions in the current business environment. It might seem that having this type of information for the management of profits, costs and budgets is not necessary to implement Digital Transformation solutions because the implementation of new technologies does not require an evaluation of this type, and it is assumed that it must be implemented independently of what it implies and at any cost, but this is an error because it will always require business processes, products or services, customers or users, service channels, etc. that must be evaluated from the financial and business process point of view, implemented, measured and improved within a competitive and market environment. In this sense, the profitablitiy, cost and budget information provided by the approach of ABPM and ABB will lead to better business decisions that significantly increase the performance and profits of the companies.
Activity Based Profitability Management and Budgeting as a support tool for D...Miguel Garcia
The business world is faced with the pace of unprecedented changes and a disruptive and innovative transformation in all industries. The context of the current economy, the emergence of new business and operational models with increasingly more cost and profitability structures, the increase in technological innovations such as the Internet of Things, Artificial Intelligence, Machine Learning, Advanced Analytics, Mobile apps, etc., which enable Digital Transformation and improve the experience of customers or users of organizations. The reduction in the life cycle of products and services, the incremental trend of mergers and acquisitions aimed at obtaining the benefits of economies of scale, as well as the pressures of low-wage countries or models of offshore outsourcing are just some of the factors of the changing environment of today.
Activity Based Profitability Management (ABPM) and Activity Based Budgeting (ABB) offers organizations a complete tool to gain a competitive advantage and provides crucial information to support the process of making strategic and operational decisions in the current business environment. It might seem that having this type of information for the management of costs and budgets is not necessary to implement Digital Transformation solutions because the implementation of new technologies does not require an evaluation of this type, and it is assumed that it must be implemented independently of what it implies and at any cost, but this is an error because it will always require business processes, products or services, customers or users, service channels, etc. that must be evaluated from the financial and business process point of view, implemented, measured and improved within a competitive and market environment. In this sense, the cost and budget information provided by the approach of ABPM and ABB will lead to better business decisions that significantly increase the performance and profits of the companies.
Este documento presenta una serie de artículos sobre la dirección de proyectos. Incluye un artículo sobre cómo analizar los requisitos del proyecto para guiar el éxito, otro sobre cómo los proyectos de autos eléctricos están ingresando al mercado, y uno más sobre cómo mejorar el desempeño de los miembros del equipo con bajo rendimiento. También presenta varias columnas de opinión de expertos en dirección de proyectos.
El documento describe 10 aspectos esenciales de una solución financiera efectiva. Estos incluyen capacidades principales como contabilidad, gestión de flujo de caja, reconocimiento de ingresos e informes financieros, así como también gestión de inventario, costos, pedidos, recursos humanos, inteligencia empresarial y adaptación a diferentes modelos de negocio. Un sistema financiero efectivo proporciona funciones contables sólidas, visibilidad del flujo de caja, y soporte para reconocimiento de ingresos recurrentes y cumplimiento norm
The document discusses how to build a credible business case for social CRM investments that will convince a CFO to fund the project. It recommends focusing on benefits that can be quantified, such as direct cost savings, increased revenues, and productivity gains. These are classified into four orders from most direct (first order) to most indirect (fourth order). First and second order benefits are most credible, while third and fourth order benefits involving productivity or indirect gains require more justification. The key is to identify measurable benefits, such as specific cost reductions or revenue increases, that can prove the return on investment.
The document discusses opportunities for growth in analytics, big data, and in-memory databases from 2013 to 2017. It finds that the global market for analytics and big data will grow to $220 billion by 2017, with North America representing $90 billion of that total. It also reports that for every $1 of revenue SAP makes from in-memory databases or analytics and big data, SAP partners will make $10.86 and $2.71 in revenue, respectively, presenting significant opportunities for partners through 2017. Customers need help with analytics and big data strategies, skills, and technologies as 90% of future IT industry growth will be driven by technologies in these areas.
After years of incremental improvement in financial management, Corporate Performance Management is quickly transforming due to factors like increased enterprise application integration, greater business intelligence capabilities, improved ease of use and implementation, and a shift to cloud-based solutions and mobile clients. The document evaluates various CPM vendors and places them in categories of Leaders and Experts based on their usability, functionality, and ability to provide value to customers.
Este documento describe cómo los directores financieros pueden desarrollar una organización financiera del siglo XXI. Explica que deben sentar unas buenas bases mediante la estandarización de procesos, tener una perspectiva más estratégica alineando la tecnología y la estrategia empresarial, y convertirse en catalizadores del cambio modernizando los sistemas y procesos. También destaca la importancia de aprovechar las tecnologías de la nube, móviles y analítica avanzada para impulsar la innovación y
Value of Exalytics for Oracle full stack CustomersMiguel Garcia
The document discusses a study by Nucleus Research on the benefits of Oracle Exalytics In-Memory Machine for business analytics. Key findings include:
1) Customers saw lower total cost of ownership through optimized hardware and software pricing, and needed fewer resources for support.
2) Time to value was accelerated by up to 4 times through a preconfigured engineered system requiring less deployment time.
3) Users experienced increased productivity from accelerated query times and improved visualization tools.
4) Decision making was improved by adding depth, breadth and dimensionality to the data available for analysis.
Cloud for Busieness Managers: the Good, the Bad and de UglyMiguel Garcia
This document summarizes the findings of independent market research on business managers' use of cloud applications. Some key findings include:
- 71% of large companies have adopted cloud apps, with motivation being quick access to software. However, 54% report staff downtime and missed deadlines due to integration issues.
- 83% feel they cannot get the full benefits of their cloud apps, often due to poor integration. Three-quarters say innovation has been hindered by integration problems.
- Over half of companies have abandoned at least one cloud app in the last three years due to integration issues. However, 81% feel full integration is important.
Forrester Study about Total Economic Impact of BI AppsMiguel Garcia
This document summarizes a Forrester Consulting study on the total economic impact of implementing Oracle Business Intelligence Applications (BI Apps). Key findings from customer interviews include lower costs through procurement savings, duplicate payment avoidance, and labor efficiencies. Additional benefits are increased sales, prices, and inventory reductions. Costs include internal implementation labor, professional services, hardware/software, training, and support. The composite organization realized a 97% ROI over three years through $18.6 million in benefits and $9.5 million in costs.
From big data overload to business impactMiguel Garcia
The document summarizes the key findings of a survey of 333 North American C-level executives about their organizations' preparedness to manage big data and leverage it effectively. The following were among the main findings:
- Organizations have seen an 86% average increase in data volume in the last 2 years, especially customer, operations, and sales/marketing data.
- However, 60% of executives rated their organizations as unprepared (C or lower), with 29% giving a D or F. Healthcare executives were least confident.
- Top frustrations included lacking the right systems to gather data and inability to give managers timely access to information.
- 93% of executives believe they are losing an average of
User survey analysis customers rate their CPM vendors, 2012 GartnerMiguel Garcia
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- Among the large vendors, SAP improved satisfaction ratings relative to Oracle and IBM, but all three still have room for improvement.
- Software-as-a-service solutions are not significantly less expensive than traditional on-premises offerings when considering total cost of ownership.
- Specialist CPM vendors like Tagetik and Longview scored higher than the large vendors like SAP, Oracle, and IBM in many areas related to customer satisfaction.
A new report from Dynamic Markets shows that – far from improving agility and effectiveness – 52 percent of organizations have missed deadlines and 75 percent have damaged their ability to innovate due to poor integration between cloud applications and other operational systems.
This document discusses the role of the CFO as a corporate catalyst for change through process excellence. It argues that process excellence, rather than technical innovation alone, provides a sustainable competitive advantage. The document identifies several key processes that can give companies an edge, including shared services centers, centers of excellence, centralized procurement, and performance management. It provides examples of companies like Oracle, Experian, and Guohua Electric Power that have leveraged process excellence in these areas to improve efficiency, support global expansion, reduce costs, and gain competitive advantages.
Mastering Big Data strategies for CFO'sMiguel Garcia
This document discusses the role of big data and analytics for CFOs and finance organizations. It defines big data as large volumes of diverse data that is growing rapidly. It provides examples of how big data is creating value for retailers through personalized offers, for healthcare through remote patient monitoring, and for financial services through new insurance products. The document argues that CFOs should play a leadership role in assessing big data initiatives to help drive growth and decision making.
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Cover Story - China's Investment Leader - Dr. Alyce SUmsthrill
In World Expo 2010 Shanghai – the most visited Expo in the World History
https://www.britannica.com/event/Expo-Shanghai-2010
China’s official organizer of the Expo, CCPIT (China Council for the Promotion of International Trade https://en.ccpit.org/) has chosen Dr. Alyce Su as the Cover Person with Cover Story, in the Expo’s official magazine distributed throughout the Expo, showcasing China’s New Generation of Leaders to the World.
The Steadfast and Reliable Bull: Taurus Zodiac Signmy Pandit
Explore the steadfast and reliable nature of the Taurus Zodiac Sign. Discover the personality traits, key dates, and horoscope insights that define the determined and practical Taurus, and learn how their grounded nature makes them the anchor of the zodiac.
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NIMA2024 | De toegevoegde waarde van DEI en ESG in campagnes | Nathalie Lam |...BBPMedia1
Nathalie zal delen hoe DEI en ESG een fundamentele rol kunnen spelen in je merkstrategie en je de juiste aansluiting kan creëren met je doelgroep. Door middel van voorbeelden en simpele handvatten toont ze hoe dit in jouw organisatie toegepast kan worden.
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The report *State of D2C in India: A Logistics Update* talks about the evolving dynamics of the d2C landscape with a particular focus on how brands navigate the complexities of logistics. Third Party Logistics enablers emerge indispensable partners in facilitating the growth journey of D2C brands, offering cost-effective solutions tailored to their specific needs. As D2C brands continue to expand, they encounter heightened operational complexities with logistics standing out as a significant challenge. Logistics not only represents a substantial cost component for the brands but also directly influences the customer experience. Establishing efficient logistics operations while keeping costs low is therefore a crucial objective for brands. The report highlights how 3PLs are meeting the rising demands of D2C brands, supporting their expansion both online and offline, and paving the way for sustainable, scalable growth in this fast-paced market.
Prescriptive analytics BA4206 Anna University PPTFreelance
Business analysis - Prescriptive analytics Introduction to Prescriptive analytics
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Non Linear Optimization
Demonstrating Business Performance Improvement
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Introduction to the Panel on: Pathways and Challenges: AI-Driven Technology in Agri-Food, AI4Food, University of Guelph
“Enhancing Adoption of AI in Agri-food: a Path Forward”, 18 June 2024
Enhancing Adoption of AI in Agri-food: Introduction
Expanding BIs role by including Predictive Analytics
1. Sponsored by
Expanding BI’s role
by including Predictive Analytics
In today’s economic downturn, organizations are looking for
ways to improve the way they do business to keep ahead of
the competition and grow revenue.
In a 2009 CIO Insight survey of senior managers and
IT executives, respondents listed their top priorities as
improving business processes, delivering better customer
service, generating more business from new and current
customers, and differentiating the company from
competitors via IT. But faced with the challenging economic
environment and reduced funding for new initiatives, how do
organizations focus on meeting these prioritized objectives?
The path to success in all of these areas, traditionally, has
been to use business intelligence (BI) information to make
decisions. Increasingly, organizations are finding that the
benefits of BI can be enhanced when complemented by
predictive analysis. Specifically, more insight can be gained,
and even better decisions made, by coupling business-
relevant information with an easy-to-use predictive analytics
solution.
A Natural Extension to BI
Business intelligence provides valuable insight into the
state of affairs within an organization. The information
is critical to decision-making. But when combined with
predictive analysis, synergies can be leveraged to improve
business and operations.
Many industry analysts like to make an analogy between BI
and predictive analytics by citing a quote from the famous
hockey player Wayne Gretzky, who said: “A good hockey
player plays where the puck is. A great hockey player plays
where the puck is going to be.”
Comparably, BI tools help users know what has happened
and what is happening, while predictive analytics tools
help to elicit more from this information by providing
an understanding of why these things happened and in
predicting what will happen.
For example, BI tools can report which sales region had
the highest sales, how many widgets were sold in stores
in different ZIP codes, the average spending per online
customer vs. in-store customer, and how many customers
stopped doing business with your company last year. All
of this information is essential for developing new product
and services, allocating resources, investing in marketing
campaigns, and so on.
Predictive analytics tools, though, can give deeper insight
into why these things happened. For example, knowing
the average customer spends $100 per visit to a store
is one thing. Knowing that a certain 20 percent of the
customers are responsible for 80 percent of all revenues
and that they are more likely to buy particular products
bundled together is much more valuable. Also, identifying
which products influenced the purchase of others or the
strength of the relationship between products purchased
together would give more insight into specific buying
patterns. This added level of analysis can yield valuable
results. It helps you understand how that prized segment
of your customer base would respond to very targeted
promotions.
Similarly, knowing that the average response rate to a
direct-mail marketing campaign is, say, 4 percent, an
organization can decide how often to run these campaigns
factoring in mailing costs and the revenue generated by
a campaign’s sales. Knowing the types of customers and
2. Sponsored by
being able to correlate that with what they purchased and
when they are likely to purchase again would allow an
organization to target those customers at the right time
with the right offerings. This would allow the company to
while ensuring customers are offered a product or service
they would actually be interested in.
That’s the difference between BI and the power of BI
combined with predictive analytics.
MANy ApplicAtioNs
Predictive analytics helps organizations look forward
and make educated decisions that anticipate the future
needs of customers. It combines known information
about customers, sales, operations, or finances, with
critical insight that helps solve problems, achieve business
objectives, and uncover hidden patterns not easily
identifiable through reports or dashboards. The combined
knowledge is used to take actions that can improve
business.
A traditional example of predictive analysis’use would be
to identify trends like poor customer service or customer
dissatisfaction and correlate complaints to customer churn.
Having insight into why customers are leaving or why they
stay, an organization can take action to retain them. For
instance, by surveying customers, an organization might
find that 30 percent of their customers consider the price
of the service to be the most important factor in choosing
a company. Another 30 percent might love to receive perks
and consider such offerings a distinguishing factor that
keeps them coming back. And the rest might simply feel
that timely and courteous service is essential.
Having this level of insight into customer likes and dislikes
can help an organization make predictions about the future
actions of these customers. Correlating this information
with actual customer actions allows an organization to
take action. For example, having identified a segment of
the customer base that attaches importance to pricing, an
organization might offer discounts or reduced rates if the
customer signs a multi-year contract. Those who love perks
might be offered free shipping, a free music download, or
an extra day at a hotel.
In another area, an organization might use predictive
analytics to cross-analyze sales data and marketing
spending, perhaps finding that 80 percent of the sales in
response to direct mail or e-mail campaign come from only
group of 20 percent in future campaigns, the organization
can significantly increase the ROI of these campaigns.
Additionally, an organization might use purchasing
information tied to a customer loyalty program to
understand which products are purchased together, by
whom, and when. Having this information, the organization
can try to increase revenues by cross-selling distinct
bundles to select customers. For instance, a retailer might
find that customers who bought the highest-priced suits
also bought shoes to match and a protective trench coat.
Having that information, a store might selectively place
trench coats next to the high-end suits. Or it might develop
a marketing campaign that offers discounts on shoes and
trench coats when a customer buys a suit valued over a
certain price.
With such success from traditional predictive analytics
usage, organizations are looking to expand its influence to
more areas of operations and to more users. In particular,
predictive analytics is increasingly being used to help
identify key influencers in customer satisfaction, employee
retention rates, customer churn, and other areas.
For example, Human Resources (HR) might use predictive
analytics to help select job applicants. Specifically,
employers want to predict which job applicants are going
to make a commitment to their job. Predictive analytics
can be used to show which personality traits are better
predictors for worker productivity and turnover.
Predictive analytics might also be used to retain talented
employees by helping predict if an employee is likely to
leave based on the types of services they consume from
the company such as training, taking advantage of 401k
plans, or the number of vacation days taken. Armed with
this information HR managers can target top performers
with programs designed to increase their investment in the
company and hence their likelihood of staying.
Predictive analytics can also bring value to other areas
of operations, such as manufacturing. For example,
organizations could use predictive analytics to help identify
and predict equipment maintenance for it products,
ultimately increasing customer satisfaction. By analyzing
Predictive analytics tools can give deeper
insight into why these things happened
increase the effectiveness of their marketing promotions 20 percent of its customer base. By selectively targeting this
3. Sponsored by
data collected by systems such as an aircraft’s health
and usage monitoring system and flight maintenance
log records, an aircraft manufacturer can determine the
relationships between how the aircraft is being operated
and maintained and the consumption of parts. The
deeper understanding of these correlations will allow
the manufacturer to take proactive action to reduce
direct maintenance costs or even improve manufacturing
processes.
Limitations Stymie Usage
Such potential benefits derived from predictive analytic
solutions are getting the attention of many organizations. In
fact, a 2008 IDC BI and Analytics Survey found that predictive
analysis tools were the number-two priority for purchasing
within the next 12 months (second only to business activity
monitoring tools).
Why the growing interest? According to IDC, the median ROI
for BI projects using predictive technologies was 145 percent,
compared with a median ROI of 89 percent for projects
without them.
Forrester Research recently forecasted predictive analytics
and data mining will also grow at a rapid pace, more than
doubling in growth to nearly $2.2 billion within the next five
years.
While many have noticed the synergies that might be gleaned
by combining BI and predictive analysis, predictive analytics
tools have not been as widely embraced as BI tools. There are
several reasons for this.
Predictive analytics tools are often designed for analysts. They
assume a high-level knowledge of statistical analysis methods.
In particular, an analyst would be needed to determine which
mathematical tools to apply to a problem: linear regression, a
chi-squared distribution, something else? As such, many tools
are difficult for business managers and others to use.
Additionally, many predictive analytics tools require special
programming skills. Users must not only know which formulas
are appropriate for doing a specific analysis, they must then
know how to create and enter the formula to analyze the
relevant data. Some tools require the use of programming
languages like C or C++; others might rely on the statistical
analysis programming language R. This puts these tools out
of the reach of the majority of business users. And in some
cases, IT must get involved, making many predictive analytics
efforts rigid and not flexible enough to meet rapidly changing
market conditions.
Another shortcoming with many predictive analysis tools is
that they are standalone tools. This complicates matters in two
ways.
First, getting access to information can be difficult. BI solutions
often provide a means to access relevant information for
decision-making. If the predictive analytics tool does not
integrate well with a complete BI solution or does not
accommodate data access and data mining, the user will have
to obtain the information for analysis in a brute-force manner.
Second, if the tool is standalone, it might not provide an easy
way for the results of the analysis to be shared, viewed, or
made part of a decision-making workflow. But being part of a
solid BI infrastructure makes it easier to share the results with
the right users who need the information to transform the
business.
Bringing Predictive Analytics into the
Fold
SAP offers a way to overcome these limitations and make
predictive analytics a part of the normal business decision
making process.
Its SAP BusinessObjects Predictive Workbench helps uncover
trends and patterns to solve business problems, anticipate
business changes, and make forecasts.
SAP BusinessObjects Predictive Workbench integrates
with your existing data environment – as well as SAP
BusinessObjects Enterprise environments – and it allows for
efficient discovery of important and predictive findings.
At the heart of the offering is an easy-to-use visual workflow
interface. Using Predictive Workbench, business users
can quickly create analysis routines that draw on specific
Organizations are looking to expand predic-
tive analytics influence to more areas of
operation and to more users
4. Sponsored by
datasets. The interface is point-and-click; no coding is
required. The tool can help you determine the best model
to use for a particular project. Additionally, the Workbench
supports the entire data-mining process, making it easier to
put this solution in the hands of more data analysts.
The results of a predictive analysis routine can be easily
shared with users who need the information to make
business decisions. And in turn, these models created by
an organization’s analysts can be run by users themselves
so they might apply the analysis routinely to new data as it
is acquired. As an example, the results can be visualized in
dashboards, reports or mobile devices making it easier to
share these insights across an organization.
SAP BusinessObjects Predictive Workbench can easily be
added to a company’s repertoire for business decision-
making. In particular, it does not necessitate the rip-and-
replace approach some other predictive analytic solutions
require. SAP BusinessObjects Predictive Workbench works
with existing BI solutions and can output findings in a format
that is easily used and shared.
When combined with the SAP BusinessObject XI platform,
SAP BusinessObjects Predictive Workbench gives
organizations the predictive analytic muscle needed to stay
competitive in today’s economy.
In particular, SAP BusinessObjects Predictive Workbench
allows organizations to:
• Overcome the limitations of traditional solutions and
make predictive analytics a part of the normal business
decision making process
• Uncover trends and patterns to solve business problems,
anticipate business changes, and make forecasts
• Efficiently discovery important and predictive findings by
way of an easy-to-use visual workflow interface
• Enable easy sharing of information with those who must
make timely decisions. n
For more information, go to:
http://www.sap.com/
The results of a predictive analysis rou-
tine can be easily shared with users who
need the information to make business
decisions