sentrana ifma board_meeting_final

The Impact of “Big Data” on Foodservice

Transforming Data into Actionable Insights

© 2013 Sentrana Inc. All rights reserved. Do not copy or redistribute.

Agenda

1. Who we are

2. Industry Point of View

3. The Importance of Big Data

4. Opportunities for Leveraging Big Data in Foodservice

5. How to Get There

6. Summary / Questions


Introduction to Sentrana

1. Sentrana’s Foodservice experience goes back

to 2006 when we began piloting software to

deliver predictive analytics and optimized prices

with the Sysco the nation’s largest foodservice

distributor

2. Our MarketMover® suite combines predictive

recommendations and analytical tools to help

Sysco:

Optimize prices for all “street” accounts every day

Deliver specific cross-sell opportunities to each

Sales Associate for their accounts

Design and execute corporate promotions, with

targeted products and prices as well as optimized

timing

3. Our expansion into the manufacturer space

was motivated by an opportunity to uncover

insights in manufacturers’ existing data that

can be immediately translated into market-

facing actions

1. Rapid Time to Value – Our domain expertise

and existing software-as-a-service (SaaS)

infrastructure puts tools and insights in users’

hands quickly without deep IT integration

2. Domain Expertise – Our experience in the

foodservice industry lets us go beyond simply

providing a repository of information.

3. Proven Data Management Experience –

Sentrana created hosted data warehouse

solutions for large enterprises comprised of

billions of records sourced from multiple,

disparate systems.

4. Advanced Analytics Capabilities – At its

core, we are a predictive analytics company

with the expertise and ongoing R&D to

maximize insights from data (especially

imperfect or “messy” data)

5. Continuous Improvement – We are

continuously innovating and improving the

products and services to make the insight

execution process more seamless

Deep Foodservice Expertise Unique Solution Values


Category Management poses

collaboration opportunities, but

not everyone can win

Efficiency targets may further

compress margins

Whether you are direct or

broker sales force time in front

of operators is limited

Need to maximize and prioritize

opportunities

Distributors’ margin pressure is

partially pushed to suppliers

Food shows, earned

income/shelter and other

obligations remain in place

Minimal industry growth makes deep market awareness critical as competition for market

share and distributor obligations both intensify

Implications for Foodservice 2013 & Beyond:

Manufacturers Need to Change the Game …..

Distributor Obligations Limited Sales Force Category Management

Where are we

gaining vs.

losing share?

How do we get

opportunities out

to brokers and

field sales?

Where are our

best sales

opportunities?

How do our

Trade and

Marketing

investments

influence P&L?

Foodservice

Manufacturers

GPOs are proliferating as

operators look for ways to save

More street accounts are turning

to Cash & Carry’s, adding to

margin pressures

Operator Changes


In Case You Haven’t Noticed…


Big Data in Brief…

Big data (also spelled Big Data) is a general term used to describe the voluminous

amount of unstructured and semi-structured data a company creates -- data that would

take too much time and cost too much money to load into a relational database for

analysis.

Although Big data doesn't refer to any specific quantity, the term is often used when

speaking about petabytes and exabytes of data.

A primary goal for looking at big data is to discover repeatable business patterns. It’s

generally accepted that unstructured data, most of it located in text files, accounts for at

least 80% of an organization’s data. If left unmanaged, the sheer volume of

unstructured data that’s generated each year within an enterprise can be costly in terms

of storage. Unmanaged data can also pose a liability if information cannot be located in

the event of a compliance audit or lawsuit.

Big data analytics is often associated with cloud computing because the analysis of

large data sets in real-time requires a framework to distribute the work among tens,

hundreds or even thousands of computers.

-Margaret Rouse, Editorial Director, WhatIs.com

http://searchsqlserver.techtarget.com/definition/relational-database

http://searchstorage.techtarget.com/definition/petabyte

http://searchstorage.techtarget.com/definition/exabyte

http://searchbusinessanalytics.techtarget.com/definition/unstructured-data

http://searchstorage.techtarget.com/definition/storage

http://searchcompliance.techtarget.com/definition/compliance-audit

http://searchcloudcomputing.techtarget.com/definition/cloud-computing

http://whatis.techtarget.com/definition/data-set

http://searchcrm.techtarget.com/definition/real-time-analytics




Big Data’s Impact on Foodservice Partners

1) Using their transactional data, distributors

can Optimize Prices to for every customer,

every SKU, every day

2) Sales data reveals Cross-sell

Opportunities that can be passed to the

DSR

3) Customer tendencies and preferences

can be inferred through transactional

attributes

4) Distributors can infer the customer’s total

purchase basket from all suppliers to make

more relevant offerings

5) Distributors have the ability of using their

transaction and program data to inform

Category Management initiatives

1) Ability to identify non-contracted

opportunities (both new and existing)

and gain additional revenue at DCs

2) Quickly identify unit compliance issues

and how business is trending at the unit

level

3) Improve vendor relations by providing

information on the latest consumer habits

and trends

4) Improve Unit Performance by identifying

opportunities across different geographies

or concepts and sharing the knowledge

Distributors GPOs and Contract Management Cos.


1. Spot Opportunities - Discover which customers have unmet needs and

determine the size of the volume opportunity at each customer

2. Manage Contract Buyer Relationships

Identify “white space” in contracted business

Break down performance trends by geography, product, segment

Identify and communicate double dips to field sales for resolution

3. Understand the Street - Use loyalty program and food show data to

understand the “street”

4. Arm the Brokers & Field Sales - Provide guidance as to priority and cross-

sell opportunities to sales without HQ effort

5. Know the Distributors’ Value-Add – Negotiate trade spend with knowledge

of where your business is, and how much is contracted in each region

Applications of Big Data for Manufacturers

Harmonizing customer information across your different feeds provides a more

granular view of the customer and makes it easier to execute against new insights


Manufacturers receive information about who their customers are and what they are

buying from numerous sources:

Mapping units and cases across these feeds is difficult and time-consuming

― The same unit will be recorded differently in every data feed you receive

― A single case might show up in four or more data feeds!

Harmonizing these disparate data silos drastically reduces the human cost of performing

analysis

This isn’t data mining it’s Data Fracking!

Manufacturers Don’t Have a Data Problem - They Have a

Data Aggregation Problem!

Foodservice Rewards

Loyalty Programs

Contracted

Rebates

CHD Expert

LTO Coupons

Velocity Data

Distributor Deviated

(Contracted and Foodshow)


Benefits of a Big Data Strategy:

Using knowledge to drive actionable insights

1. Prioritize Opportunities: BSRs or Field

Sales see which units have the most “un-met

case volume” and compliance voids

2. Market Visibility: Spot shifts and emerging

trends in your contracted business to

“protect the base” and double-down on

growth areas

3. Greater Accountability: Give Sales

leadership clarity around Field Sales and

Broker performance

4. “True View” of the Customer: Stop double-

counting cases across different claims; see

which units actually bought which products

and how they are trending

5. Information is relayed directly to the right

audience without HQ interaction

1. Correlate Trade Investment with Sales

Performance: Quantify the link between trade

spend and case volume across distributors

and customer segments

2. Identify Your Distributor Leverage:

Determine the distributor branches in which

your contracted/street business mix points to

adjusting trade funds

3. Spot and Resolve Double Dips: Identify

units that are double-dipping on redemptions

and push this information to Field Sales to

resolve

4. Integrate Trade with Other Spend: Analyze

trade within the context of all spending

designed to move cases (marketing, loyalty

incentives, etc.)

Sales Advantages Trade Advantages


Cross-sell

recommendations pushed

out directly to Territory

Sales through a

Dashboards

While Campaign Marketing

analysts use Big Data for

Demand Creation, Territory

Sales can also monetize

the customer-level insights

in parallel

Making Data Actionable in the Field Should Not Create

Additional Work at Corporate

Cross-Sell Opportunities by Customer/Territory


Data Warehouses Must Integrate Data rather than

Simply Collapse It

1. Putting the data into one system

provides some convenience

2. We still cannot look across all sources

to understand the business as a whole

3. It is not clear when there is

overlapping volume for a single unit

4. At best, we only have a partial view of

each customer and redundancy across

sources, and no ability to correlate

anything

1. Using intelligent matching techniques,

we are able to match customer records

across information sources allowing us

to create a better market and product(s)

picture

2. We can then collapse transaction data

across buying groups and other

information sources to provide a richer

and customizable view of customer

behavior

Velocity

Data

Dist.

Deviated

Operator

Rebates

Foodservice

Rewards

Manufacturer

ERP Velocity Data

Dist. Deviated

Operator Rebates

Foodservice Rewards

Manufacturer ERP

Integrated

Transaction View

Integrated

View of

Customer

Collapse Data Deliver an Integrated View


Bringing Data Together is Not Enough

Different Audiences Need Information Tailored to Their Needs

Make it easy for analysts to

identify patterns and

investigate outliers in the

data

Field Sales needs easy-to-

interpret sales plans and

target lists


Big Integrated Data and Analytics Capabilities Anchor

Continuous Improvement (not “One and Done”)

1 Consolidate & Integrate Data

Integrate all transactions and unify customer

IDs in MarketMover’s data warehouse

2 Refresh Analytics and Predictions

Update summary statistics and opportunity

predictions with latest sales and customer

data

3 Push Updates to Analytics Tools

Update summary statistics and opportunity

predictions with latest data

4 Measure Program Effectiveness

Gauge effectiveness of ongoing programs

and key decisions

6 Protect Base & Capture Opportunities

Field Sales and Brokers follow-up on targeted

leads identified by Management and software

Lost 120 cases

with three

Sodexo units

Compliance

voids with 6

Aramark units

5 Customize Sales & Marketing Plans

Tailor marketing plans for Field Sales &

Brokers; change underperforming

programs 450 incremental monthly

case opportunity in K-12

Logo

Logo


1. Diverse industry shifts are simultaneously forcing

manufacturers to get smarter about their

customers (operators & distributors)

2. You already possess significant data assets, but

the valuable information is scattered across

different files, formats, and systems

3. A system-based solution to harmonize these

disparate data sources makes it easier to access

information about your customers and

performance as well as incorporate new

information over time

4. Different types of users need tools that let them

interact with data in ways that fit with their skills

and responsibilities

5. Successful deployment requires managerial

engagement and a vision for building a

foundational business capability

Summary


“Big data as a technological opportunity and big data as a management theory

are two separate things. However much big data can yield, information will

never be perfect.

As efficient as these data models become, managers will still have to make

decisions with limited certainty about the outcomes.

Data helps and has since the scouts of ancient armies returned with reliable

numbers. Eisenhower at D-Day had more data than Hannibal at Cannae, but

waging war remained a beast of a task.

The challenge for managers has always been the human mind and heart,

which seems punier than ever in the shadow of the terabyte.”

- Philip Broughton

author of "The Art of the Sale

Conclusion

1725 Eye St. NW, Suite 900

Washington DC, 20006

OFFICE 202.507.4480

FAX 866.597.3285

WEB sentrana.com

Jim Klass

[email protected] 704.562.9794

mailto:[email protected]

sentrana ifma board_meeting_final

Technology

update summary

big data

rights reserved

continuous

integrate

unstructured

optimize prices

field sales