lavacon 2014: but will it fit in my bathroom? creating a single interface for product presale data

@MarkPeterson4 #LavaCon

But will it fit in My Bathroom?Creating a single interface for product presale data

Mark Peterson

Kohler Co.


Why am I here

• We help users buy more of our stuff

• We built a portal to take down silos/barriers

• We let content owners do their own data

• We built structure to enforce consistency

• We increased accessibility to the data

• I’m sure it could be done better


The “napkin drawing” that got people to get it

Single Source of Truth

for Product Presale Data

A DE

C

B D = Automation of the Process

E = Integration of Content

systems


What’s cool about our latest system

• Role-based access

• Lights-out updating with SAP manufacturing data

• Mass update tools

• Feeds to downstream systems

• Automated generation of formatted data

• Flexibility adding fields and new canned values

• Build-your-own and pre-formatted searching


Your preferences for a “case study”

1. Demo

2. Worst “mistakes”

3. Greatest scoring moments

4. Financial justification

5. Attacking silos

6. Tools and architecture

7. Searches and reporting

8. Establishing customer needs

9. Building what nobody could

articulate

10. Automated workflow

11. Automated output

12. Being a “radical” who always talks

about “structure”

I can tailor this to your top items


Our DataMart

• The DataMart is a data superstore upstream of

Kohler.com and the “web builder”

Web-based input interface

Data owners and data lockdown for each field

Powerful searching tools for any user

Reports aligned to the needs of downstream users

•


DataMart Project Goals

• Single source of truth for pre-sale product data

Internal access to all pre-sale data before general customer access at product launch

No more opening “documents” to answer a question

Change roll-out and change tracking

Reliability of data as a key trust factor

Incremental sales

Net cost reduction

Aligns with mobile needs


Reasons

• When data changed, the right people and

systems were not notified

Data lacked consistency

There was too much time spent proofing

Current systems could not add fields fast enough and keep them

aligned

Searches could only be done by a small set of people


Consumers are now in control

•Average # information sources used to get information and/or advice regarding the specific plumbing

products you needed for this specific project:

For considering/exploring options:

For narrowing choices:

2.6 3.0

2012 2013

4.2 3.9

2012 2013


How customers interact with us

• Customers spend more time planning details of their kitchen and

bathroom than any other rooms

• Matching the brand, color, and details matters to them

• And they plan rooms around a few key fixtures

25%33%

2012 2013

68%75%

2012 2013

68%75%

2012 2013

Important that all bathroom plumbing

products are the same brand

Extremely/Very Important

Important that all bathroom plumbing

products have the same color/finish


Important that all kitchen plumbing

products have the same color/finish



What we gave them

• Full, but lacking colors and cross-selling

Customer-facing data lacked consistency

•


Proof and reproof and never locked down

• Specification Sheets were proofed by four different areas

• People spent more time marking up and proofing changes than just

making live changes themselves

• Other silos manually pasted spec info, which then needed more

proofing

• Catching stale data generated another proof cycle

• No method to notify all silos of specific data changes


Cost savings beyond incremental sales

• Proofing time

• Time spent looking for data

• Pasting time

• PM time

Cu

rren

t

Pro

posed

Savin

gs

2010 Total Cost AllSpec Sheets

EngrArt/TP

Text/TP

Proj Man/TP

Prf/Engr

Prf/Codes

Prf/Mrkt

Prf/TP MrktComm PCI/DS


The business value and long-term potential

• Customers are less confused by our conflicting data

• We don’t turn on a fire hose when they ask for a drink

• Reduced internal support costs via:Creating a central authority for technical answers

Reducing the number of times engineers get asked the same question

Eliminating multiple data entry points for any one piece of data

The request form is the data entry form…there is no retyping to proof

No stale data

Eliminating labor-intensive formatting of tables within our current spec sheets

Reduced language support costs and new-language


What changes for internal users

• Content owners type into a user interface…there

is no retyping to proof

Eliminates Paper/PDF mark-ups for spec sheets

Gatekeepers by content ownership area

Internal users can access data by queries rather than by opening

spec sheet PDFs


Scale

• 20,000 products x 10 colors x 4 changes/year

Historically this was partially-captured in 4,000 spec sheets

Product changes several times right before/after launch due to ongoing enhancements

Multiple silos grabbed that data manually

Multi-month lead time for the simple changes…requestors just gave up

People were sure certain sources were the original/master, but they were not

There was more mythology than proof about how our people used our publications

Most legacy data was not field-based nor in a format suited to automated capture


Timing

• One year from approval to launchLive one year as of Oct 2014

One year’s worth of data pre-loaded (eat our own cooking)

Soft-launch 90 days before full launch

90-days to a functional prototype

Lengthy licensing approval

Financial approval

Pilot project

Content analysis

Needs analysis


Before setting the costs

1. Customer data needs analysis and modeling

– What new data fields/content needed, what can go away, who uses what

– What is the source of the data, who owns it, who else links to or copies it

2. Data flow and storage

– What can accomplish the above needs and model

– How is new data received and vetted

– How to feed any necessary systems while retaining one master data source

– When is a data set considered ‘released for use’, either internal or external

3. Consumer formats and output tools

– Who generates internal data reports and what format serves their online needs

– Appearance of the main external “pub” format to meet short-term needs

– Accommodation of future language outputs

– Testing of capability for additional formats as they are defined

•

Data from current spec sheet page 1Proposed Data Source

(uses stay same as current)Current Data Source

Owner/originator: Marketing

How its received: Mark-up, E-mail

Where stored: Word, SAP, Contenta, CPDB

Who else uses it: Web Page, EQ Spec,

K-800 Design Manual,

Price Book, Resellers


How its received: Mark-up

Where stored: SAP, Contenta, CPDB

Who else uses it: Web Page, EQ Spec,



Owner/originator: Codes & Standards


Where stored: Word/Excel file, Contenta

Who else uses it: (Partial) Web, EQ Spec,



Owner/originator: Engineering, Marketing


Where stored: Contenta

Who else uses it: N/A

Owner/originator: Engineering (with Pubs

clean-up)

How its received: ASM file

Where stored: Windchill (ASM and

pubs file)

Who else uses it: Price Book


How its received: DataMart interface

Master/central storage: DataMart or SAP

Owner/originator: Engineering


Master/central storage: DataMart or SAP

Owner/originator: Codes & Standards


Master/central storage: DataMart



Master/central storage: DataMart

*Replaced with web photo when avail.

Owner/originator: Communications

How its received: Data file from CPDB

(for image file number)

Master/central storage: DAM (Digital

Asset Management System)


Basic process flow

Data Mart Store

Interface

Codes and StandardsEngineeringMarketing

Staging Area

Not Released

Released

Report of missing info to each Interface group

Add infoor

override

Add Override

Search

Field-based

Full-text

Exact matches

Greater-than, less-than

By role

Custom

Publish

1-Page pdf

Dynamic Spec Sheets

Code listing

RSS Feed – Mobile

Field-Based Data

Report

Changes over time

Difference list

Retail data file

Price book file

Etc.


Worst mistakes

• Listening to “don’t worry about money now just be on time”

• Having the wrong people spec/approve design changes

• Not having enough test plans

• Underestimating how much people will work for a workaround

• Letting the data drift due to other issues


Highlight reel moments

• From scratch to live in less than a year

• Saying yes to “can it do this?”

• Playing “stump the search guy”

• Management giving us money because of a demo

• 20+ launch presentations in one week

• Fields requested by users doubled scope (reduced silos)

• New internal customers we’d never heard of


Thoughts on attacking silos

• Show the inconsistencies

• Find the true upstream source

(it can be like trying to find the fountain of youth)

• Connect, don’t compete

• Focus on getting the data out and their maintenance issues

• Get several silo owners together in a lock-in (several times)

• Focus on the outside users

• Show a vision and a really great demo, then let them talk


Thoughts on searches and reporting

• The search sells the rest

• Reducing cycle time for things like price books opened other doors

• One “free” byproduct saved somebody 20 hours a week

• All management groups were pre-motivated to reduce time their staff

spend looking for data

• All management groups were pre-motivated to reduce time their staff

spend answering repeated questions


Thoughts on establishing customer needs

• Question the old stale anecdotes

• Being a customer

• Watching customers

• Monitoring social

• Popular search terms

• Competitive evaluation

• Parallel industries (such as kitchen appliances for us)


Contact

• [email protected]

• @MarkPeterson4

• 920-918-5361

• Vendor partner info also available upon request

• Experience Gracious Living online at: http://www.KOHLER.com

• Experience "Destination Kohler" for yourself online at

http://www.DestinationKohler.com.

http://www.kohler.com/

http://www.destinationkohler.com/


About the Speaker

• Mark is a quarter-century member of one company, having navigated through

typesetting to desktop publishing to early adoption of XML and content

management.

• Formerly a staff and department manager, he now focuses on identifying and

implementing technical solutions to meet trending consumer needs.

• Before settling in “technical publications,” he was in electronics sales, journalism,

training, and even a little building construction.

• Working with a major international plumbing manufacturer with thousands of

products, he sees lots of data to connect and silos to decommission.

• He also gets an excuse to spend time in Home Depot and to play with new

computer technology.