technology data & analytics solutions solutions guide

A comprehensive listing of solution

providers thAt support the collection,

AggregAtion, storAge, AnAlysis And

integrAtion of vAluAble dAtA.

technology solutions guideA R e s o u R c e s u p p l e m e n t t o c G t m A G A z i n e

d ata & a n a ly t i c s s o l u t i o n s

2013®

sponsored by:

2 tsg | April 2013 technology solutions guide | consumergoods.com

1010data www.1010data.com

1010data

• Clorox

• Colgate-Palmolive

• SC Johnson

1010data helps optimize promotions, merchan-dising, operations, pricing, loyalty and more using data-driven insights.


customers experience measurable increases in promotional effectiveness, higher levels of sales, improved loss prevention and more efficient supply chain operations.

customers typically go live with all of their data in less than 5 weeks.

AFS Technologies www.afsi.com

aFs discovery g2

• 200 companies, including manufacturers, distribu-tors and broker/sales agencies

sales, trade Promotion management, Warehouse efficiency, Financial Performance, category management


uncovers the most profitable selling and promotional activities, customer and vendor profitability, assess cost-to-serve, operational efficiency, and expose emerging business issues.

implementation in as little as 45 days; implementation varies by customer.

Applied Predictive Technologies www.predictivetechnologies.com

test & learn management system

• American Greetings

• Anheuser-Busch InBev

• Johnson & Johnson

aPt arms cg companies and their retail partners with the capability to rapidly and reliably test vari-ous in-store initiatives (e.g. new product intro-ductions, retail servicing, merchandising/display changes etc.).


aPt’s clients are typically able to generate $10m to $50m in profit improvements by accurately understanding which new ideas work, which don’t and which could work if fine-tuned.

clients can implement aPt’s test & learn system within 3 to 4 weeks, and recommendations are immedi-ately actionable.

Hybrid Intelligence www.hybridintelligence.com

cPg-focused ad hoc reporting, analysis, data warehousing and application software

• ConfidentialFit-for-purpose, data-driven business analysis applications focused on Brand Finance, sales and supply chain


500% productivity improvements combined with analysis innovation that helps facilitate rapid data-driven and fact-based decision making

depending on level of integration, 30 to 90 days: Benefits upon go live

IBM Corporation www.ibm.com/consumerproducts

iBm cognos

• 60 of the 65 Fortune 1000 CPG companies are IBM customers based upon 2012 data

iBm cognos impacts workforce management, supply chain, sales and operations planning, financial processes and more.


clients can attain revenue and margin goals, plant-specific cost budgets and P&l statements can articulate the optimum balance between meet-ing your customer demand and profitability.

the roi models for iBm cognos generate compelling business justification.

Interactive Edge www.interactiveedge.com

XP3 suite

• Georgia-Pacific

• Mars Chocolate

• Nestlé USA

XP3 allows sales, category management and shopper marketing to turn data into actionable insights quickly and easily.


XP3 reduces the effort of developing and maintaining customer-specific reporting from days to hours, allowing more time for more effective customer engagement and collaboration.

implement within days or weeks depending on data sources requiring integration

JDA Software Group, Inc. www.jda.com

Performance management and Business analysis

• Associated Wholesale Grocers

• GPI/CarQuest

• Harris Teeter

Jda’s integrated solutions span the supply chain from materials to the consumer, planning to execution.


increases visibility for supply chain metrics, dashboards and predictive analytics; provides analytic views not available in traditional reporting; enables labor savings from consolidated data collection and reporting infrastructure; a complete solution from problem identification to plan or execution actions

typical implementation time is 3 to 9 months based on company size/complexity

LumiData www.lumidata.com

solys demand intelligence solutions

• Unilever

• Procter & Gamble

• L’Oreal

demand data analysis for sales teams and senior execs in sales, customer management, supply chain and s&oP functions


improved execution/strategy across retailers, channels, store segments and consumers through reporting and analysis that is directly aligned with the individual requirements of each retailer

implementation approaches range from 60 to 90 days, roi realized in 3 to 6 months

nuevora www.nuevora.com

nuevora’s Big data analytics & applications Platform cg (nBaaP™)

• Confidential

nuevora’s big data analytics and apps platform enables marketers to make better business deci-sions across the customer and product lifecycles via continuous, near real-time and predictive insights.

Nuevora www.nuevora.com

nuevora’s big data analytics solutions power smarter marketing and product innovation. the solutions typically generate greater than 10% improvement across key metrics related to growth, profitability, cus-tomer equity and marketing optimization.

typical implementations are done in 1 to 2 weeks from data to decision.

COMPANy / WEB SITEDATA / ANALyTICS product

Key cg customers most impActed business process COMPANy / WEB SITE QUANTIFIABLE BUSINESS BENEFITSAverAge implementAtion CyCLE / TIME-TO-BENEFIT

2 0 1 3 D ATA & A N A Ly T I C S s o l u t i o n s c h A rt

technology solutions guide

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1010data

• Clorox


• SC Johnson

1010data helps optimize promotions, merchan-dising, operations, pricing, loyalty and more using data-driven insights.


customers experience measurable increases in promotional effectiveness, higher levels of sales, improved loss prevention and more efficient supply chain operations.

customers typically go live with all of their data in less than 5 weeks.


aFs discovery g2

• 200 companies, including manufacturers, distribu-tors and broker/sales agencies

sales, trade Promotion management, Warehouse efficiency, Financial Performance, category management


uncovers the most profitable selling and promotional activities, customer and vendor profitability, assess cost-to-serve, operational efficiency, and expose emerging business issues.

implementation in as little as 45 days; implementation varies by customer.


test & learn management system

• American Greetings



aPt arms cg companies and their retail partners with the capability to rapidly and reliably test vari-ous in-store initiatives (e.g. new product intro-ductions, retail servicing, merchandising/display changes etc.).


aPt’s clients are typically able to generate $10m to $50m in profit improvements by accurately understanding which new ideas work, which don’t and which could work if fine-tuned.

clients can implement aPt’s test & learn system within 3 to 4 weeks, and recommendations are immedi-ately actionable.


cPg-focused ad hoc reporting, analysis, data warehousing and application software

• ConfidentialFit-for-purpose, data-driven business analysis applications focused on Brand Finance, sales and supply chain


500% productivity improvements combined with analysis innovation that helps facilitate rapid data-driven and fact-based decision making

depending on level of integration, 30 to 90 days: Benefits upon go live


iBm cognos

• 60 of the 65 Fortune 1000 CPG companies are IBM customers based upon 2012 data

iBm cognos impacts workforce management, supply chain, sales and operations planning, financial processes and more.


clients can attain revenue and margin goals, plant-specific cost budgets and P&l statements can articulate the optimum balance between meet-ing your customer demand and profitability.

the roi models for iBm cognos generate compelling business justification.


XP3 suite

• Georgia-Pacific

• Mars Chocolate

• Nestlé USA

XP3 allows sales, category management and shopper marketing to turn data into actionable insights quickly and easily.


XP3 reduces the effort of developing and maintaining customer-specific reporting from days to hours, allowing more time for more effective customer engagement and collaboration.

implement within days or weeks depending on data sources requiring integration


Performance management and Business analysis

• Associated Wholesale Grocers

• GPI/CarQuest

• Harris Teeter

Jda’s integrated solutions span the supply chain from materials to the consumer, planning to execution.


increases visibility for supply chain metrics, dashboards and predictive analytics; provides analytic views not available in traditional reporting; enables labor savings from consolidated data collection and reporting infrastructure; a complete solution from problem identification to plan or execution actions

typical implementation time is 3 to 9 months based on company size/complexity


solys demand intelligence solutions

• Unilever


• L’Oreal

demand data analysis for sales teams and senior execs in sales, customer management, supply chain and s&oP functions


improved execution/strategy across retailers, channels, store segments and consumers through reporting and analysis that is directly aligned with the individual requirements of each retailer

implementation approaches range from 60 to 90 days, roi realized in 3 to 6 months

nuevora www.nuevora.com

nuevora’s Big data analytics & applications Platform cg (nBaaP™)

• Confidential

nuevora’s big data analytics and apps platform enables marketers to make better business deci-sions across the customer and product lifecycles via continuous, near real-time and predictive insights.

Nuevora www.nuevora.com

nuevora’s big data analytics solutions power smarter marketing and product innovation. the solutions typically generate greater than 10% improvement across key metrics related to growth, profitability, cus-tomer equity and marketing optimization.

typical implementations are done in 1 to 2 weeks from data to decision.






Oracle www.oracle.com

oracle Business analytics solutions

• Land O’Lakes

• Hormel Foods

• Reckitt Benckiser

Broad and deep support spanning consumer en-gagement, retail demand signals, and complete sales, trade management, category and opera-tions insights


insight-based, demand-driven planning and action-oriented market execution with enhanced customer collaboration driven by deep understanding of the consumer, shopper and customer

Prebuilt analyses, dashboards and insights enable benefits within 6 to 8 weeks

Orchestro (formerly Vision Chain) www.orchestro.com

orchestro insights, shelfsense, Promo-sense, demandsense, Basketsense

• Del Monte Foods

• General Mills

• Newell Rubbermaid

orchestro shelfsense delivers improvements in on-shelf availability and facilitates better new product introductions. orchestro Promosense greatly improves promotion compliance.


orchestro helped one manufacturer save $2.5m on dc inventory due to Pos-driven forecasts, and another uncovered $404,622 in lost sales from a single promotion in just 1 month.

standard – 4 weeks, Premium – 8 weeks; enterprise – 12 weeks (including omnichannel, social and sentiment data)

Predictix www.predictix.com

Predictix adaptive Platform for intelligent decisions

• Crate & Barrel

• M.Video

• Toys”R”Us

Predictix’ merchandising solutions impact demand forecasting, replenishment, assortment, item and financial planning, and promotional pricing.


significantly more accurate forecasts result in improved inventory turns and margins; a common forecasting engine produces consistent reports across silos.

though projects vary, the standard implementation cycle is 6 months.

Relational Solutions, Inc. www.relationalsolutions.com

Posmart Bluesky analytics

• GlaxoSmithKline

• J.M. Smucker

• Lindt

category management, trade marketing, supply chain, sales, Vmi, executive reporting, Business intelligence, Pos integration for it


roi is greatly increased by streamlining employee productivity with Posmart but also by improving trade spend by quickly identifying effective promotions.

several retailers can be up and running within 1 month.

Retail Solutions Inc. www.retailsolutions.com

retail intelligence, part of retail solutions’ retail execution management suite

• Nestlé


• Unilever

retailer-supplier collaborate Business Pro-cesses (cBP) impact forecasting, replenishment, marketing, category management and promo execution.


through its cBP, customers gain invaluable relationships with the retailer and, in effect, experience improved margins, higher revenues, increased roi on trade spend, improved planning and reduced oos.

implementation in 4 to 6 weeks, roi in 3 to 6 months

Salient Management Company www.salient.com

salient collaborative intelligence suite

• Ace International Hard-ware Corporation

• Bimbo Bakeries USA

• M.A. Gedney Company

salient’s primary impact is in sales and revenue management and secondarily across all other functions of the enterprise impacted by sales activity.


software precisely quantifies where the money goes, what is being gained in return, why something is worth more (or less) than before, and who’s responsible: solution can save 3%-5% on a company’s gross revenues, or 10%-15% on margins

From contract to roi in less than 3 months

sAp www.sap.com/consumer

saP Businessobjects Business intelligence solutions


• Kraft Foods


saP Businessobjects business intelligence solutions enable business functions, including marketing, product development, sales, supply chain, finance and more.


With saP Businessobjects, consumer products companies can be first to market with innovative products, maximize promotion roi and optimize supply chain efficiency across the entire business network.

Widely variable based on scope and objectives; time-to-value can be immediate

SAS Institute Inc. www.sas.com

sas demand-driven Forecasting

• Amway China

• Grandi Salumifici Italiani

• Nestlé Direct Store Delivery

sas demand-driven Forecasting drives develop-ment of the consensus forecast in conjunction with s&oP.


improve forecasting accuracy across your product hierarchy; reduce finished goods inventory and stock-outs; enhance accuracy with forecast-value-added (FVa) and reporting

4 to 6 months’ time-to-benefit is typical

Sequoya www.sequoya.com

Promotion optimizer

• Georgia-Pacific


• Mars

sequoya optimizes the trade/sales planning process and gives category management visibility to category impact.


sequoya implementations usually generate 27% increased trade efficiencies and a 12%-18% reduction in trade spending.

Benefits begin within 60 days from start of implementation.







oracle Business analytics solutions

• Land O’Lakes

• Hormel Foods


Broad and deep support spanning consumer en-gagement, retail demand signals, and complete sales, trade management, category and opera-tions insights


insight-based, demand-driven planning and action-oriented market execution with enhanced customer collaboration driven by deep understanding of the consumer, shopper and customer

Prebuilt analyses, dashboards and insights enable benefits within 6 to 8 weeks


orchestro insights, shelfsense, Promo-sense, demandsense, Basketsense

• Del Monte Foods

• General Mills


orchestro shelfsense delivers improvements in on-shelf availability and facilitates better new product introductions. orchestro Promosense greatly improves promotion compliance.


orchestro helped one manufacturer save $2.5m on dc inventory due to Pos-driven forecasts, and another uncovered $404,622 in lost sales from a single promotion in just 1 month.

standard – 4 weeks, Premium – 8 weeks; enterprise – 12 weeks (including omnichannel, social and sentiment data)


Predictix adaptive Platform for intelligent decisions

• Crate & Barrel

• M.Video

• Toys”R”Us

Predictix’ merchandising solutions impact demand forecasting, replenishment, assortment, item and financial planning, and promotional pricing.


significantly more accurate forecasts result in improved inventory turns and margins; a common forecasting engine produces consistent reports across silos.

though projects vary, the standard implementation cycle is 6 months.


Posmart Bluesky analytics

• GlaxoSmithKline

• J.M. Smucker

• Lindt

category management, trade marketing, supply chain, sales, Vmi, executive reporting, Business intelligence, Pos integration for it


roi is greatly increased by streamlining employee productivity with Posmart but also by improving trade spend by quickly identifying effective promotions.

several retailers can be up and running within 1 month.


retail intelligence, part of retail solutions’ retail execution management suite

• Nestlé


• Unilever

retailer-supplier collaborate Business Pro-cesses (cBP) impact forecasting, replenishment, marketing, category management and promo execution.


through its cBP, customers gain invaluable relationships with the retailer and, in effect, experience improved margins, higher revenues, increased roi on trade spend, improved planning and reduced oos.

implementation in 4 to 6 weeks, roi in 3 to 6 months


salient collaborative intelligence suite

• Ace International Hard-ware Corporation

• Bimbo Bakeries USA

• M.A. Gedney Company

salient’s primary impact is in sales and revenue management and secondarily across all other functions of the enterprise impacted by sales activity.


software precisely quantifies where the money goes, what is being gained in return, why something is worth more (or less) than before, and who’s responsible: solution can save 3%-5% on a company’s gross revenues, or 10%-15% on margins

From contract to roi in less than 3 months


saP Businessobjects Business intelligence solutions


• Kraft Foods


saP Businessobjects business intelligence solutions enable business functions, including marketing, product development, sales, supply chain, finance and more.


With saP Businessobjects, consumer products companies can be first to market with innovative products, maximize promotion roi and optimize supply chain efficiency across the entire business network.

Widely variable based on scope and objectives; time-to-value can be immediate


sas demand-driven Forecasting

• Amway China

• Grandi Salumifici Italiani

• Nestlé Direct Store Delivery

sas demand-driven Forecasting drives develop-ment of the consensus forecast in conjunction with s&oP.


improve forecasting accuracy across your product hierarchy; reduce finished goods inventory and stock-outs; enhance accuracy with forecast-value-added (FVa) and reporting

4 to 6 months’ time-to-benefit is typical


Promotion optimizer

• Georgia-Pacific


• Mars

sequoya optimizes the trade/sales planning process and gives category management visibility to category impact.


sequoya implementations usually generate 27% increased trade efficiencies and a 12%-18% reduction in trade spending.

Benefits begin within 60 days from start of implementation.






SetSight www.setsight.com

setsight

• General Mills

• Dial/Henkel

• Elizabeth Arden

chain- and store-level sales, category analysis, supply chain management and forecasting


setsight provides an end-to-end solution for analyzing downstream data from multiple retail partners that doesn’t interfere with existing it teams or infrastructure.

Proof of concept using live data in evaluation process, implementation in 4 to 8 weeks

Shiloh Technologies www.shilohtech.com

shiloh dsr - software Platform, retail services and solutions: data management, analytics, merchandising

• Hershey

• Nestlé


Forecasting and demand planning, sales, Vmi, replenishment, category management, reporting, retail execution, retailer relationships, new item introductions, promotion and price planning


gain efficiencies across the enterprise, increase sales and margin, im-prove in-stock and forecast, reduce inventory, and enhance retail execu-tion and promotion roi

implementation in 4 to 6 weeks, payback in 3 to 6 months

Silvon Software, Inc. www.silvon.com

stratum

• HarperCollins Publishers

• Sorrento Lactalis

• Red Gold

demand forecasting and supply chain analysis of sales, category, inventory, supplier, produc-tion, other operational data


reduced inventory up to 25%; improved on-time delivery by as much as 40%; improved fill rates by nearly 10%; and 1% to 3% contribution to net profitability

30 to 60 days

SymphonyIRI Group, Inc. www.symphonyiRi.com

Price and trade advantage

• Hillshire Farms

• ConAgra Foods

• Starbucks

assessing marketplace price dynamics, develop-ing profitable price strategies, driving effective promotion plans and evaluating performance of Pos marketing and promotions


Price realization & margin management; Volume & dollar growth; Better roi on Pos promotion programs

6 to 8 weeks – based on number of brands, geographies and client customizations

TABS Group, Inc. www.tabsgroup.com

taBs WorldView

• Unilever

• Wyeth Nutrition (a division of Nestlé)

• Energizer Personal Care

global sales and marketing analytics, global strategy


optimal resource allocation for global markets; c-suite discussions with Wall street

4 weeks per category

Teradata Corporation www.teradata.com/industry- expertise/consumer-goods/

teradata unified data architecture


• Coca-Cola

• Hershey

Product innovation and introduction, r&d, digi-tal/consumer/Brand/shopper marketing, sales/trade relationships/Promotion/Pricing, supply chain/demand Planning/distribution/traceabil-ity/Food safety


Higher performing product introductions, greater marketing roi, optimal trade promotion, higher margins and sales volumes, more efficient production, optimized distribution

typically 90 days, scalability means investment protection for follow-on projects

TIBCO Spotfire http://spotfire.tibco.com/

tiBco spotfire analytics

• GE

• General Mills


global insights and forecasts of category/prod-uct performance, consumer behaviors/sentiment and pricing, promotion and campaign success


identify categories/products generating highest return; structure pricing/promotions to maximize profitability; save on promotion/campaign spend: millions in top- and bottom-line value

rapid implementation in hours/days; fastest roi with proven best practices

Retail Velocity (formerly Vendor Managed Technologies, Inc.) www.RetailVelocity.com

Velocity solution suite (on-Premise or Hosted)

• Hanesbrands

• Mattel

• Revlon

enterprise coverage, including category man-agement, account management, marketing, demand Forecasting, merchandising, replenish-ment, retail execution and beyond


5%-20% incremental sales growth; 5%-10% decrease in Finished goods inventory (Fgs)

1 to 6 months depending on the implementation parameters

Verix Inc. www.verix.com

Verix ls and Verix cPg

• Nielsen


• Tnuva

sales: performance analysis, goal projection, educated decision supportcategory management: out-of-stocks, revenue, market/share, inventory


early detection of problems (cannibalization, out-of-stock, etc.) saves millions; significant time saving (couple of hours instead of several days)

Pre-packaged analytical application configured per user with specific role, process and organization’s needs; 3 to 5 weeks to initial implementation







setsight

• General Mills

• Dial/Henkel

• Elizabeth Arden

chain- and store-level sales, category analysis, supply chain management and forecasting


setsight provides an end-to-end solution for analyzing downstream data from multiple retail partners that doesn’t interfere with existing it teams or infrastructure.

Proof of concept using live data in evaluation process, implementation in 4 to 8 weeks


shiloh dsr - software Platform, retail services and solutions: data management, analytics, merchandising

• Hershey

• Nestlé


Forecasting and demand planning, sales, Vmi, replenishment, category management, reporting, retail execution, retailer relationships, new item introductions, promotion and price planning


gain efficiencies across the enterprise, increase sales and margin, im-prove in-stock and forecast, reduce inventory, and enhance retail execu-tion and promotion roi

implementation in 4 to 6 weeks, payback in 3 to 6 months


stratum

• HarperCollins Publishers

• Sorrento Lactalis

• Red Gold

demand forecasting and supply chain analysis of sales, category, inventory, supplier, produc-tion, other operational data


reduced inventory up to 25%; improved on-time delivery by as much as 40%; improved fill rates by nearly 10%; and 1% to 3% contribution to net profitability

30 to 60 days


Price and trade advantage

• Hillshire Farms

• ConAgra Foods

• Starbucks

assessing marketplace price dynamics, develop-ing profitable price strategies, driving effective promotion plans and evaluating performance of Pos marketing and promotions


Price realization & margin management; Volume & dollar growth; Better roi on Pos promotion programs

6 to 8 weeks – based on number of brands, geographies and client customizations


taBs WorldView

• Unilever

• Wyeth Nutrition (a division of Nestlé)

• Energizer Personal Care

global sales and marketing analytics, global strategy


optimal resource allocation for global markets; c-suite discussions with Wall street

4 weeks per category


teradata unified data architecture


• Coca-Cola

• Hershey

Product innovation and introduction, r&d, digi-tal/consumer/Brand/shopper marketing, sales/trade relationships/Promotion/Pricing, supply chain/demand Planning/distribution/traceabil-ity/Food safety


Higher performing product introductions, greater marketing roi, optimal trade promotion, higher margins and sales volumes, more efficient production, optimized distribution

typically 90 days, scalability means investment protection for follow-on projects


tiBco spotfire analytics

• GE

• General Mills


global insights and forecasts of category/prod-uct performance, consumer behaviors/sentiment and pricing, promotion and campaign success


identify categories/products generating highest return; structure pricing/promotions to maximize profitability; save on promotion/campaign spend: millions in top- and bottom-line value

rapid implementation in hours/days; fastest roi with proven best practices


Velocity solution suite (on-Premise or Hosted)

• Hanesbrands

• Mattel

• Revlon

enterprise coverage, including category man-agement, account management, marketing, demand Forecasting, merchandising, replenish-ment, retail execution and beyond


5%-20% incremental sales growth; 5%-10% decrease in Finished goods inventory (Fgs)

1 to 6 months depending on the implementation parameters


Verix ls and Verix cPg

• Nielsen


• Tnuva

sales: performance analysis, goal projection, educated decision supportcategory management: out-of-stocks, revenue, market/share, inventory


early detection of problems (cannibalization, out-of-stock, etc.) saves millions; significant time saving (couple of hours instead of several days)

Pre-packaged analytical application configured per user with specific role, process and organization’s needs; 3 to 5 weeks to initial implementation



Editor’s NotE : solution providers were asked to identify only their primary solution to the consumer goods industry. Visit their respective web sites for information on additional solutions/services.


consumergoods.com | april 2013 | cgt 2 3

Define “Big Data” and explain how it differs from existing data and analytics projects?

S h u m a n : simply stated, Big data is more than your existing systems and processes can han-dle. Big data is large record sets (Volume), in real time or frequently updated (Velocity), and broad in scope (Variety). Any one of these three can tip the scale from data to BIg data. What gets lost in the conversation about Big data is the fourth “V”: Value. With the scope of available data growing, the lit-

mus test for value is determining what insights can be derived from the data and what actions can be taken with those insights. this dif-fers from traditional reporting and analytics projects, which typically are time-phased or time series ap-proaches. deriving value from Big data is dependent on the harmo-nization of data that has differing granularity, frequency and entity definitions, and the application of adaptive algorithms to that data to identify opportunities and in-sights. the value is often found in the “guilty silences” where these

different data elements fail to in-tersect as they should, indicating missed opportunities and poor ex-ecution. the solution is not a data mart or even a series of data marts. using Big data calls for refining the insights out of the raw data, and empowering systems and process-es to take action on those insights.

Golovin: Big data, analytical tools and everyday delivery of ac-tionable insights are important for many businesses, but an imperative in the consumer packaged goods (cPg) industry. Big data is both

unstructured, which is focused on social data relating to shoppers and consumers, and structured which is focused on retailer inventory re-porting, point-of-sale (Pos), and internal data on shipments, inven-tories, promotional plans, pricing, etc. Although some vendors label the current volume and velocity of structured data as Big data, we see the separation as being between existing quantitative data, which typically is focused on plans and what did happen, versus additional qualitative sources of data that track shopper behaviors and may indi-

The State of Data Insights


Data and analytics experts from Orchestro, Retail Solutions Inc.,

Shiloh Technologies and TIBCO Software offer thought leadership

for consumer goods manufacturers that are trying to find business

opportunities through Big Data, demand signal insights and

analytical tools.

continued on page 25

Dave Shuman Co-Founder and VP Products, Orchestro

BRITT FOgg Founder and CTO Shiloh Technologies

LeSLIe mILLeR Spotfire Product Marketing TIBCO Software

JOn gOLOvIn CEO Retail Solutions Inc.

R O u n D Ta B L e Pa R T I C I Pa n T S :

2 0 1 3 D ata & a n a ly t i c S S o l u t i o n S


CliCk here for Chart

cate what is likely to happen and so can be used predictively. Big data in cPg includes multiple data types — from actual sales to likes on Face-book to blog postings to the senti-ment of current tweets. Big data can be 100 to 1,000 times larger in size than existing data — especially as we look at more granular levels of data, even down to the individual characteristics of shoppers/con-sumers and their behavior. As a re-sult, Big data systems have moved from existing technology — rela-tional databases and cube technol-ogy — to newer technology that can scale to the new levels of data.

FoGG: In the industry of retail data analytics, Big data is the cap-ture and accumulation of every piece of data about every sKu, from the point it leaves the manu-facturing facility throughout the entire supply chain to every point of distribution all the way through to check out. that is A Lot of data. shiloh technologies has been

working with Big data for almost 20 years. In the early 1990s retail-ers began sharing their Pos data with their partners, adding a mas-sive amount of information to the company’s existing data. getting this wealth of data in a manage-able format was, and still is, quite a challenge for many. commonly, existing data has been simplified, summarized or aggregated, losing valuable details contained at the lowest level recorded. this data will simply not meet the needs of today’s sophisticated analytic re-quirements, the type of analysis that drills down to the heart of the retail business and finds impactful opportunities.

miller: For cg organizations, the goal is to become more nimble and intelligent with the decision-making process — to keep up with the fast pace and fiercely competi-tive marketplace. the promise of Big data analytics is about creat-ing a collaborative environment of intelligent, agile, cross-enterprise decision making, providing a per-vasive data-driven culture that al-lows employees to make imme-diate decisions to affect positive change on the business.

the idea is to move beyond the slow pace of traditional business intelligence tools and to break down the departmental siloes of

data that have brought us single-perspective-only insights. We need to bring together disparate pieces of intelligence that come from a very wide variety of internal and external sources, to create a comprehensive, interconnected picture of business performance.

the opportunity, or promise of Big data analytics, is that orga-nizations that become agile and data-driven will enjoy a competi-tive advantage. A combination of interactive, visual, descriptive and predictive analytics, with self-service guided and collaborative workflows for the masses, and in-line deployment in real-time event systems, is the future.

Which business process-es can be most improved using demand insights from downstream data?

Shuman: our customers are rapidly expanding the use of


Big data systems have moved from existing technology — relational databases and cube technology — to newer technology that can scale to the new levels of data.

— JOn gOLOvIn, ReTaIL SOLuTIOnS InC.continued on page 27




downstream data as more broad demand signals are being shared. typical use cases are improved speed to shelf, promotion execu-tion, productive inventory and on-shelf availability. Improved cus-tomer and shopper service levels are achieved through short-term replenishment, demand and pro-motion planning. retail execution is achieved by demand-enabling applications and business process-es with inventory and consumption data in a context and form that is immediately relevant. the scope of demand data is growing as more value is derived from the correla-tion of the expanded data universe. this is an evolutionary journey for both consumer product companies and retailers — data sharing fosters conversations and insights that would not be possible without a common framework. data leads to insights, insights lead to conversa-tions, conversations develop into action plans, action plans become part of the business process.

Golovin : Almost all current processes can be enhanced with demand insights. some examples:• Pos-Based Forecasting: Fore-

casting orders/demand from retailers based on the current inventory levels and what is selling in each store, versus forecasting based on previous orders received from the re-tailer (especially as personal-ized offers increase, making de-mand by store more variable).

• new Product Introductions: In-stead of waiting a week or more for syndicated data results, current sales and inventory by store can be used to find stores prior to launch that have not yet stocked the product; to find stores not scanning within the first two to three days of launch; to determine the actual distribu-tion or split of package sizes or flavors for manufacturing and dc stocking plans; to better es-timate the eventual on-going

sales rate versus the original forecast — to again align manu-facturing and dc inventory lev-els to the actual sales level.

• out of stocks: By analyzing the sales and reported inventory lev-els by store, algorithms can sta-tistically predict which items are likely to run out of stock before a replenishment cycle and which items are currently out of stock — due to phantom inventory, voids or other issues with shelf tags, stocking or inventory counts — and need to be addressed.

FoGG: the value of pinpointing actionable demand insights gained

from the analysis of downstream data can be realized throughout the entire supplier/retailer organization. our experience has shown that one of the first significant impacts can be made when you identify early signals of change in demand and quickly communicate this change back through the supply chain. even a few days extra notice of the swings in consumer demand, often makes a significant difference in the ability for the supply chain components to adjust and respond, resulting in more sales. this is even truer for manufacturers with VmI responsi-bilities and those in collaborative positions with the retailer.


this is an evolutionary journey for both consumer product companies and retailers — data sharing fosters conversations and insights that would not be possible without a common framework. —Dave Shuman, ORCheSTRO





When retailers and manufactur-ers share data, odds of success are greatly improved. We are now see-ing collaborative efforts between retailers and manufacturers, fo-cusing on the use of downstream data to discover the significant opportunities found by improv-ing performance at the shelf, often referred to as on-shelf availability (osA). the improvement of osA has an enormous impact on the consumer experience in the store, which leads to store and brand loyalty, therefore, ensuring their repeat business.

miller: using self-service an-alytics to combine downstream data with internal sales, market-ing and distribution sources with external syndicated data, and con-sumer demographics and social media intelligence, we can pro-vide rich insights across the board, down to the individual store level and characteristics that influence performance. It’s very powerful.

In cg, this plays out across all core functional areas including:• category insights (value share

analysis, product mix analysis, market forecasts)

• Pricing/promotion optimization (including lifetime value)

• sales lift analysis (test and learn)• dynamic segmentation (treating

different segments differently)• Acquiring and growing con-

sumer base (customer cloning, cross-sell/up-sell)

• sentiment analysis (social me-dia, surveys, loyalty)

• marketing attribution (advertis-ing/campaign effectiveness)

• trigger-based marketing (in-cluding mobile- and location-based offers)

• Inventory management (de-mand forecasting and distribu-tion optimization)

• Fraud and risk analytics (opera-tional execution and enterprise analysis)

these deep insights allow for a greater partnership between cg

manufacturers and retailers, which ultimately helps in developing stron-ger demand forecasts that shorten the window of just-in-time inventory replenishment, formulate trade pro-motions that inspire greater shopper consumption and loyalty, and create stronger, more effective marketing campaigns that garner attention and optimize spend.

how can cG companies ensure that insights pro-vided by analytics tools become actionable?

S h u m a n : Archimedes said, “give me a place to stand with a lever and I will move the whole world”. While the insights we de-rive from Big data are the meta-phorical lever, it is equally impor-tant to find a place to stand. the best platform is to infuse exist-ing systems and processes with insights from Big data to create immediate value. this can range

from pushing alerts to handhelds to enable retail execution; from integrating with the retailer’s store ordering systems to push-ing inventory to the store; from integrating aggregated demand at pre-defined planning levels into forecasting systems to pushing short-term requirements into VmI systems; from modeling new item velocity into space planning tools to pushing new item alerts to the field. the fastest path to value is leveraging existing infrastructure and processes with the insights generated from adaptive analyt-ics. critical to that integration is measuring the value delivered. the determination of success is achieved by measuring business benefits, whether through im-proved execution and increased revenues or leaner execution and reduced costs.

Golovin : the key to making these insights actionable are agreed upon collaborative business pro-






cesses (cBP) developed in partner-ship with the retailer that state the responsibilities/actions to be taken by each partner for any given busi-ness process or issue, including the metrics for how performance will be evaluated. As examples: • out of stocks: the cBP would

specify how they will be detect-ed and by whom (is detecting them the responsibility of the supplier or retailer or both) — and when they are detected — who will verify the situation and then take action (the retailer’s store operations associates or the supplier’s merchandisers or the retailer’s dc), and how is the actual return from improving out-of-stock rates measured?

• Promotions execution: the cBP would specify who is re-sponsible for determining the store-by-store allocations (and how the allocations will be de-termined), who is responsible for ensuring that the correct in-ventory is at the store prior to

the promotion and what actions are taken if it isn’t. If the suppli-er is responsible and inventory is insufficient, do they call the buyer or the store manager? or send a dc push request to the dc? or send a merchandiser to the store? If the promotional sales rate exceeds the planned level, does the retailer or sup-plier send/request additional shipments to their dcs? How will promotion execution per-formance be measured?

FoGG: the power of sophisticat-ed analytics software often reveals insights where you could be sell-ing more, but that is only the first step. the industry has historically been relatively good at describing what has already happened, and to a lesser extent, predicting what is going to happen.

the key to leveraging these in-sights is to delve a little deeper to determine WHY something hap-pened, then prescribe the changes

that will positively impact what happens next.

more often than not, there are multiple “prescriptions” for a single problem. the prescrip-tions must be systematically implemented; initiating the most impactful and cost effective oppor-tunity first, measure the results, and continue as necessary.

In reality, there are additional factors that come in to play that may not be contained in the data. each situation is unique and there are large variations in what busi-ness partners are either able or willing to execute in order to re-solve problems.

miller: It is a cultural transfor-mation that needs to be led from the executive level. the ultimate goal is for pervasive, enterprise readiness that promotes rigorous and real analysis of the business that includes: • An end-user community fully

enabled with always-available

self-service analytics, that pro-vide access to a myriad of requi-site data sets, (while at the same time providing centralized It governance to ensure right-level access to sensitive information)

• Inbuilt guided applications for collaborative analyses across all relevant functional areas in the enterprise

• Analytics solutions that span the analytics value chain, from descriptive, diagnostic and pre-dictive analytics, and can be in-tegrated into in-line event anal-ysis systems (e.g., for real-time, individualized in-store offers)

• experienced analysts to build and evaluate models that de-scribe and/or predict the mea-sured response, and to build and evaluate new features, dashboards and challenger models for evolution of the guided analyses

• solutions with elastic architec-tures to efficiently meet enter-prise demands





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