Her_APPGE Company_NN1 Spells_VVZ Success_NN1 in_II More_DAR Than_CSN 100_MC Languages_NN2 It_PPH1 was_VBDZ an_AT1 international_JJ drug_NN1 trafficking_NN1 case_NN1 ,_, one_PN1 that_CST involved_VVD a_AT1 lot_NN1 of_IO money_NN1 and_CC a_AT1 lot_NN1 of_IO violence_NN1 ._. 
Undercover_JJ agents_NN2 who_PNQS had_VHD infiltrated_VVN the_AT cartel_NN1 had_VHD worn_VVN wires_NN2 and_CC collected_JJ evidence_NN1 for_IF years_NNT2 ._. 
A_AT1 conviction_NN1 depended_VVN on_II an_AT1 accurate_JJ translation_NN1 of_IO their_APPGE tape_NN1 recordings_NN2 ._. 
"_" Five_MC languages_NN2 were_VBDR involved_VVN ,_, "_" says_VVZ Liz_NP1 Elting_NP1 ,_, 44_MC ,_, one_MC1 of_IO the_AT owners_NN2 of_IO TransPerfect_NP1 ,_, the_AT translation_NN1 company_NN1 chosen_VVN for_IF the_AT job_NN1 ._. 
"_" The_AT slightest_JJT mistake_NN1 could_VM mean_VVI the_AT criminals_NN2 would_VM go_VVI free_JJ ._. "_" 
For_IF weeks_NNT2 ,_, company_NN1 linguists_NN2 worked_VVD closely_RR with_IW prosecutors_NN2 and_CC agents_NN2 to_TO help_VVI win_VVI a_AT1 conviction_NN1 ._. 
When_CS Elting_NP1 launched_VVD her_APPGE business_NN1 18_MC years_NNT2 ago_RA with_IW Phil_NP1 Shawe_NP1 ,_, both_DB2 were_VBDR attending_VVG New_NP1 York_NP1 University_NN1 's_GE Stern_JJ School_NN1 of_IO Business_NN1 ._. 
Neither_RR realized_VVN just_RR how_RGQ many_DA2 situations_NN2 would_VM require_VVI their_APPGE services_NN2 ._. 
"_" We_PPIS2 've_VH0 transcribed_VVN black_JJ box_NN1 data_NN after_II plane_NN1 crashes_NN2 ,_, "_" says_VVZ Elting_NP1 ._. 
"_" We_PPIS2 've_VH0 done_VDN mergers_NN2 and_CC acquisitions_NN2 ._. 
Translating_VVG Hooked_VVN on_II Phonics_NP1 into_II eight_MC languages_NN2 was_VBDZ especially_RR challenging_JJ because_CS we_PPIS2 were_VBDR doing_VDG sounds_NN2 ,_, not_XX words_NN2 !_! "_" 
Elting_NP1 had_VHD once_RR worked_VVN for_IF a_AT1 translation_NN1 company_NN1 ,_, and_CC she_PPHS1 knew_VVD that_CST the_AT industry_NN1 was_VBDZ essentially_RR lots_PN of_IO tiny_JJ outfits_NN2 delivering_VVG patchy_JJ quality_NN1 ._. 
She_PPHS1 also_RR knew_VVD how_RGQ important_JJ it_PPH1 was_VBDZ to_TO get_VVI things_NN2 right_JJ --_NN1 like_II the_AT instructions_NN2 for_IF medical_JJ devices_NN2 ._. 
Ad_NN1 companies_NN2 ,_, too_RR ,_, needed_VVD accurate_JJ translations_NN2 that_CST took_VVD cultural_JJ differences_NN2 into_II account_NN1 ._. 
She_PPHS1 and_CC Shawe_NP1 were_VBDR certain_JJ that_CST if_CS they_PPHS2 delivered_VVD a_AT1 quick_JJ ,_, reliable_JJ service_NN1 ,_, they_PPHS2 could_VM build_VVI an_AT1 international_JJ business_NN1 that_CST would_VM stand_VVI out_RP ._. 
They_PPHS2 set_VV0 up_RP shop_NN1 in_II Shawe_NP1 's_GE dorm_NN1 room_NN1 ._. 
(_( The_AT two_MC were_VBDR engaged_VVN until_II 1997_MC ._. 
Though_CS the_AT wedding_NN1 never_RR happened_VVD ,_, the_AT company_NN1 forged_VVD ahead_RL ._. )_) 
While_CS Shawe_NP1 finished_VVD his_APPGE MBA_NN1 ,_, Elting_VVG recruited_JJ freelance_NN1 linguists_NN2 and_CC made_VVD hundreds_NNO2 of_IO cold_JJ calls_NN2 seeking_VVG clients_NN2 ._. 
One_MC1 of_IO their_APPGE first_MD jobs_NN2 was_VBDZ to_TO translate_VVI an_AT1 800-page_JJ feasibility_NN1 study_NN1 of_IO a_AT1 Russian_JJ gold_NN1 mine_NN1 in_II 30_MC days_NNT2 ._. 
Once_CS the_AT partners_NN2 were_VBDR out_II21 of_II22 survival_NN1 mode_NN1 ,_, they_PPHS2 hired_VVD people_NN to_TO help_VVI grow_VVI the_AT company_NN1 and_CC told_VVD them_PPHO2 to_TO run_VVI their_APPGE area_NN1 as_CS21 if_CS22 it_PPH1 were_VBDR their_APPGE own_DA business_NN1 ._. 
"_" If_CS they_PPHS2 did_VDD well_RR ,_, "_" says_VVZ Elting_NP1 ,_, "_" they_PPHS2 owned_VVD that_DD1 success_NN1 ._. "_" 
Elting_VVG and_CC Shawe_NP1 paid_VVD themselves_PPX2 $9,000_NNU a_AT1 year_NNT1 each_DD1 and_CC plowed_VVD everything_PN1 else_RR back_RP into_II the_AT business_NN1 ._. 
Their_APPGE ambition_NN1 and_CC navete_NN1 ,_, however_RR ,_, at_II times_NNT2 threatened_VVD the_AT company_NN1 's_GE growth_NN1 ._. 
In_II 2000_MC ,_, a_AT1 major_JJ retailer_NN1 promised_VVD $15_NNU million_NNO in_II business_NN1 --_NN1 more_RRR than_CSN double_RR their_APPGE revenue_NN1 ._. 
They_PPHS2 opened_VVD an_AT1 office_NN1 in_II Miami_NP1 ,_, but_CCB when_RRQ the_AT Internet_NN1 bubble_NN1 burst_NN1 ,_, says_VVZ Shawe_NP1 ,_, "_" the_AT client_NN1 pulled_VVD out_RP ._. 
Today_RT we_PPIS2 get_VV0 money_NN1 up_RL21 front_RL22 ;_; we_PPIS2 share_VV0 risk_NN1 ._. 
Commonsense_JJ things_NN2 ._. "_" 
TransPerfect_NP1 's_GE 4,000_MC linguists_NN2 cover_VV0 more_DAR than_CSN 100_MC languages_NN2 ._. 
Last_MD year_NNT1 ,_, the_AT company_NN1 had_VHD revenues_NN2 of_IO $225_NNU million_NNO ;_; the_AT average_JJ annual_JJ growth_NN1 rate_NN1 is_VBZ 30_MC percent_NNU ._. 
Elting_VVG and_CC Shawe_NP1 still_RR work_VV0 together_RL as_CSA co-CEOs_NN2 ._. 
"_" Phil_NP1 is_VBZ good_JJ at_II developing_JJ systems_NN2 and_CC creative_JJ sales_NN ideas_NN2 ,_, "_" says_VVZ Elting_NP1 ._. 
"_" I_PPIS1 focus_VV0 on_II operations_NN2 and_CC making_VVG sure_JJ our_APPGE clients_NN2 are_VBR happy_JJ ._. "_" 
Shawe_NP1 's_GE take_NN1 is_VBZ a_RR21 little_RR22 different_JJ :_: "_" Liz_NP1 is_VBZ more_RGR risk-averse_JJ ,_, and_CC I_PPIS1 'm_VBM more_RGR risk-tolerant_JJ ._. "_" 
With_IW more_DAR than_CSN 1,100_MC employees_NN2 ,_, and_CC offices_NN2 in_II 57_MC cities_NN2 in_II 18_MC countries_NN2 on_II four_MC continents_NN2 ,_, they_PPHS2 still_RR focus_VV0 on_II the_AT details_NN2 ._. 
They_PPHS2 keep_VV0 a_AT1 meticulous_JJ list_NN1 of_IO client_NN1 preferences_NN2 :_: soda_NN1 or_CC soft_JJ drink_NN1 ,_, sofa_NN1 or_CC couch_NN1 ._. 
Even_RR now_RT ,_, at_II the_AT top_NN1 of_IO the_AT world_NN1 's_GE largest_JJT privately_RR held_VVN language_NN1 company_NN1 ,_, Elting_NP1 refuses_VVZ to_TO be_VBI complacent_JJ and_CC would_VM prefer_VVI a_AT1 slightly_RR different_JJ translation_NN1 :_: "_" We_PPIS2 want_VV0 to_TO be_VBI the_AT world_NN1 's_GE premier_JJ language_NN1 company_NN1 ._. "_" 
Getting_VVG Ahead_RL with_IW Liz_NP1 Elting_NP1 What_DDQ inspired_VVD you_PPY to_TO start_VVI TransPerfect_NN1 ?_? 
When_CS I_PPIS1 was_VBDZ eight_MC ,_, my_APPGE dad_NN1 bought_VVD a_AT1 KFC_NP1 franchise_NN1 in_II Portugal_NP1 ._. 
Unfortunately_RR ,_, the_AT Portuguese_NN1 did_VDD n't_XX want_VVI anything_PN1 American_JJ after_II the_AT Communist_JJ revolution_NN1 ._. 
They_PPHS2 thought_VVD my_APPGE dad_NN1 was_VBDZ a_AT1 CIA_NP1 spy_NN1 !_! 
That_DD1 taught_VVD me_PPIO1 how_RGQ fast_JJ things_NN2 can_VM change_VVI ._. 
I_PPIS1 've_VH0 studied_VVN in_II Spain_NP1 and_CC worked_VVN in_II Venezuela_NP1 ._. 
This_DD1 business_NN1 is_VBZ the_AT perfect_JJ combination_NN1 of_IO my_APPGE passions_NN2 for_IF languages_NN2 ,_, cultures_NN2 ,_, and_CC business_NN1 ._. 
Is_VBZ the_AT staff_NN multilingual_JJ ?_? 
Many_DA2 are_VBR ._. 
I_PPIS1 speak_VV0 French_JJ and_CC Spanish_JJ ._. 
My_APPGE partner_NN1 ,_, Phil_NP1 ,_, who_PNQS is_VBZ American_JJ ,_, likes_VVZ to_TO say_VVI he_PPHS1 speaks_VVZ English_NN1 on_II a_AT1 good_JJ day_NNT1 ._. 
What_DDQ languages_NN2 are_VBR requested_VVN most_RGT often_RR ?_? 
Spanish_JJ and_CC Japanese_NN1 ._. 
Chinese_NP1 ,_, Middle_JJ Eastern_JJ ,_, Indic_NP1 (_( South_ND1 Asia_NP1 )_) ,_, and_CC Eastern_JJ European_JJ languages_NN2 are_VBR on_II the_AT rise_NN1 ._. 
How_RGQ difficult_JJ is_VBZ it_PPH1 to_TO manage_VVI such_DA a_AT1 diverse_JJ workforce_NN1 ?_? 
Our_APPGE challenge_NN1 is_VBZ to_TO be_VBI culturally_RR appropriate_JJ in_II every_AT1 country_NN1 ._. 
When_CS we_PPIS2 hand_VV0 out_RP year-end_JJ bonuses_NN2 in_II the_AT U.S._NP1 ,_, for_REX21 example_REX22 ,_, we_PPIS2 have_VH0 to_TO remember_VVI that_CST in_II India_NP1 ,_, bonuses_NN2 are_VBR distributed_VVN in_II the_AT fall_NN1 ._. 
How_RGQ important_JJ was_VBDZ your_APPGE early_JJ training_NN1 in_II finance_NN1 ?_? 
The_AT No._NN1 1_MC1 reason_NN1 companies_NN2 fail_VV0 is_VBZ that_CST they_PPHS2 run_VV0 out_II21 of_II22 money_NN1 ,_, so_CS you_PPY have_VH0 to_TO be_VBI very_RG aware_JJ of_IO the_AT numbers_NN2 ._. 
I_PPIS1 've_VH0 learned_VVN that_CST doing_VDG a_AT1 great_JJ job_NN1 is_VBZ more_RRR about_II the_AT soft_JJ skills_NN2 --_NN1 going_VVG with_IW your_APPGE instincts_NN2 ,_, acting_VVG with_IW integrity_NN1 ,_, appreciating_VVG clients_NN2 and_CC employees_NN2 ,_, and_CC dealing_VVG with_IW them_PPHO2 effectively_RR ._. 
Do_VD0 these_DD2 things_NN2 well_RR ,_, and_CC the_AT rest_NN1 will_VM follow_VVI ._. 
An_AT1 aspiring_JJ singer_NN1 in_II her_APPGE mid-20s_MC2 was_VBDZ shopping_VVG around_RP for_IF health_NN1 insurance_NN1 after_II doing_VDG without_IW for_IF five_MC years_NNT2 ._. 
The_AT sudden_JJ revelation_NN1 that_CST she_PPHS1 needed_VVD coverage_NN1 came_VVD after_II her_APPGE boyfriend_NN1 crashed_VVD his_APPGE motorcycle_NN1 and_CC ended_VVD up_RP with_IW $75,000_NNU in_II doctor_NN1 bills_NN2 ._. 
Health-care_NN1 expenses_NN2 cause_VV0 more_DAR than_CSN half_DB of_IO all_DB bankruptcies_NN2 ._. 
A_AT1 five-day_JJ hospital_NN1 stay_NN1 can_VM easily_RR cost_VVI $9,000_NNU ._. 
Yet_RR about_RG 2.4_MC million_NNO people_NN have_VH0 lost_VVN their_APPGE insurance_NN1 during_II the_AT recession_NN1 ,_, and_CC the_AT number_NN1 rises_VVZ daily_RR ._. 
Every_AT1 member_NN1 of_IO your_APPGE immediate_JJ family_NN1 needs_VVZ to_TO be_VBI covered_VVN ,_, no_RGQV31 matter_RGQV32 how_RGQV33 young_JJ or_CC old_JJ ._. 
The_AT drill_NN1 --_NN1 If_CS you_PPY ca_VM n't_XX find_VVI a_AT1 job_NN1 that_CST offers_VVZ affordable_JJ health_NN1 coverage_NN1 ,_, do_VD0 n't_XX give_VVI up_RP ._. 
Young_JJ people_NN may_VM be_VBI able_JK to_TO continue_VVI on_II their_APPGE parents_NN2 '_GE plan_NN1 as_CSA dependents_NN2 until_CS they_PPHS2 're_VBR well_JJ into_II their_APPGE 20s_MC2 ,_, depending_II21 on_II22 where_RRQ they_PPHS2 live_VV0 (_( check_VV0 statehealthfacts.org_NNU )_) ._. 
Once_CS they_PPHS2 age_VV0 out_II21 of_II22 that_DD1 plan_NN1 ,_, they_PPHS2 may_VM have_VHI to_TO buy_VVI an_AT1 individual_JJ policy_NN1 ,_, unless_CS they_PPHS2 qualify_VV0 for_IF a_AT1 state_NN1 program_NN1 (_( covertheuninsured.org_NNU )_) or_CC there_EX 's_VBZ a_AT1 trade_NN1 group_NN1 they_PPHS2 can_VM join_VVI ._. 
Monthly_JJ premiums_NN2 for_IF coverage_NN1 that_CST carries_VVZ a_AT1 higher_JJR deductible_NN1 tend_VV0 to_TO be_VBI cheaper_JJR ,_, but_CCB deductibles_NN2 can_VM run_VVI as_RG high_JJ as_CSA $10,000_NNU a_AT1 year_NNT1 ._. 
Think_VV0 long_JJ and_CC hard_RR before_II purchasing_VVG a_AT1 policy_NN1 that_CST requires_VVZ an_AT1 enormous_JJ out-of-pocket_JJ payment_NN1 before_CS it_PPH1 kicks_VVZ in_RP ._. 
If_CS you_PPY 're_VBR running_VVG out_II21 of_II22 options_NN2 ,_, there_EX are_VBR short-term_JJ plans_NN2 that_CST will_VM protect_VVI a_AT1 relatively_RR healthy_JJ person_NN1 from_II the_AT worst_JJT medical_JJ situations_NN2 ._. 
These_DD2 policies_NN2 --_NN1 from_II companies_NN2 like_II Assurant_JJ Health_NN1 and_CC United_JJ Health_NN1 One_MC1 --_NN1 last_MD six_MC months_NNT2 to_II a_AT1 year_NNT1 but_CCB can_VM cost_VVI as_RG little_DA1 as_CSA $30_NNU a_AT1 month_NNT1 ._. 
Compare_VV0 plans_NN2 at_II ehealthinsurance.com_NNU ._. 
The_AT payoff_NN1 --_NN1 It_PPH1 's_VBZ a_AT1 no-brainer_NN1 ._. 
According_II21 to_II22 research_NN1 from_II the_AT Kaiser_NNB Family_NP1 Foundation_NN1 ,_, a_AT1 think_NN1 tank_NN1 in_II Menlo_NP1 Park_NN1 ,_, California_NP1 ,_, people_NN with_IW health_NN1 coverage_NN1 tend_VV0 to_TO live_VVI longer_RRR ,_, healthier_JJR lives_NN2 because_CS they_PPHS2 do_VD0 n't_XX put_VVI off_RP their_APPGE medical_JJ care_NN1 ._. 
By_II 2030_MC ,_, experts_NN2 like_II Alicia_NP1 Munnell_NP1 of_IO Boston_NP1 College_NN1 's_GE Center_NN1 for_IF Retirement_NN1 Research_NN1 predict_VV0 ,_, the_AT "_" replacement_NN1 rate_NN1 "_" will_VM drop_VVI to_II 30_MC percent_NNU ._. 
Like_VV0 it_PPH1 or_CC not_XX ,_, we_PPIS2 're_VBR all_RR going_VVGK to_TO have_VHI to_TO save_VVI more_RRR for_IF retirement_NN1 ._. 
