good data gone bad slide 1 the national association of stock plan professionals

GOOD DATA GONE BAD

Slide 1

The National Association of Stock Plan Professionals

Speakers

Paula Woodman, Director, Client Services, Charles Schwab & Co.

Nicole Dmitruchina, Financial Reporting Specialist, EASi

Steve Madeira, VP of Operations, EASi

Marianne Snook, SOS

Jim Vincent, CEP (Moderator)Manager, Consulting Services – E*TRADE

Slide 2The National Association of Stock Plan Professionals

Why this panel? Why now?

Background on each speaker’s perspective Data issues are NOT seasonal! With the economy in flux, companies may be

Downsizing Considering other vendors Hiring in cheaper, less experienced help

All contribute to potential data issues down the road


Impact of “Bad” Data

Report errors – some may require assistance of your vendor to understand impact

Incorrect shares available for grant Brokerage participants may be allowed to exercise shares

they are not entitled to exercise Incorrect reporting to brokerage participants Incorrect information appears in participant accounts on their

brokerage site


Impact of “Bad” Data

Incorrect/missing disposition or tax reporting (for ISO/NQ data confusion)

Incorrect information displayed on financial reports Some data issues may result in system performance issues



Common Causes

Mergers & acquisitions

Repricings

Exchanges (especially options to restricted stock)

Stock splits (especially reverse)

409A tender offers (fixing “back-dated” options)

Improper table set-up (e.g., Tax Table)

Conversion from one vendor to another

Past stock administrators

Inserting data in back-end through scripts

Slide 6


Common Causes

Consultants

Granting ISOs to non-U.S. participants

Partially canceling grants

Changing Account IDs

Layoffs and rehires

Forgetting to process valuations for option grants

Improperly deleting records

Slide 7

System Transition/Outsourcing

Recordkeeping data review and clean up items most commonly seen when making a change:

Missing data Participant information Tax rates and or jurisdictions Missing term dates

Bad or inaccurate data Grant or transaction information Vesting information Plan rules Share balances

Historical data All data needs to be as accurate as possible


Transition/Outsourcing (continued)

Be willing to accept change

Identify current workarounds to determine how to be use new system/provider

Data flow make work differently

Plan for major events if at all possible Historical data: Identify major events

Communication is key Identify project manager and department contacts Audit thoroughly during implementation


Corporate Actions & Events

What should you watch out for when preparing and what lessons have we learned from our multiple experiences in these areas:

Mergers and Acquisitions

Define what history you will need to keep Define how you will identify plans, participants, grants, etc. Can your recordkeeping system support your needs How and who will communicate to employees. Very

detailed information Work closely with all contacts (stock admin, broker, TA) at

other company


Actions & Events (continued)

Option exchanges/Tender offers

Define the population offered the exchange Analyze pros/cons from employees’ and company’s

perspective Identify what data will be provided and to who How and who will communicate to participants Can you do this or will you need vendor Understand all of the rules around the type of offer Accounting/Tax effects of modifying awards

Slide 11


Performance Shares

What have we seen and what should you know about issuing and administering:

Understand how they will work and how will you administer Who will receive them? How will they be measured? How will you educate the participants? How will you inform the participant of achievement or lack of

Identify what your systems can support Issuance and Vesting Reporting Probability tracking Accounting impact


Identifying “Bad” Data

Spring cleaning – make time for it

Be VERY familiar with your database

Watch for information that doesn’t look right on reports

If you have a stock administration team, then have well documented procedures for auditing data periodically

Audit data after consultant covers stock administration

Have a second set of eyes look at the information

Sometimes the errors are not obvious and others can help you find it




Run audit and validation reports

Search database for missing, inconsistent or illogical transactions and print a summary of each transaction

Sorted by severity and by message Documentation for the report shows:

Error message language What may be causing the issue How severe the issue is Reports that may be impacted by issue Steps for correcting the issue

Slide 14



Issues that might not be found by audit/data check/validation reports

Non-alphanumeric or unexpected values in grant Number field (e.g., “-”)

Lost links between Parent and Child grants from old cancel/ regrants

Slide 15


Common Errors

Grant date is after cancel date

Missing FMVs

Shares exercised exceed shares granted

Option exercise after vest cancel date

Vest dates are out of order

Release date before grant date or after expire date

Zero shares granted

Disposition shares exceed shares exercised

DDs for non-ISO records

Slide 16


Fixing “Bad” Data

Get management approval before “fixing” any data Manual correction Export data, fix it and then re-import If data issues cannot be fixed by you and they are preventing

system from running properly, get help Consultants Peers in Equity Compensation

Slide 17

Auditing Data

Tools Run Data Check/audit/validation reports often

(especially after each import) Best Practices

Have a centralized person auditing entire database for the entire company

Carefully monitor import activity Run appropriate audit report after each import – don’t

assume everything is complete or correct


Auditing Data

Have audit processes well documented Once identified, fix issue as soon as possible

Especially during implementation or when there are changes in stock administration

If not fixing an issue, document the reason why


Good Data Gone Bad

Paula Woodman, Director, Client Services, Charles Schwab & Co.

Nicole Dmitruchina, Financial Reporting Specialist, EASi

Steve Madeira, VP of Operations, EASi

Marianne Snook, SOS

Jim Vincent, Manager - Consulting Services – E*TRADE

good data gone bad slide 1 the national association of stock plan professionals

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