Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
よいプロダクトをつくるためのよいチームのつくられかた
Search
Yusuke Kokubo
June 18, 2019
Business
3
6k
よいプロダクトをつくるためのよいチームのつくられかた
よいプロダクトをつくるためにはよいチームが必要です。
よいチームがつくられるためのステップをとあるプロジェクトの事例をまじえて紹介します。
Yusuke Kokubo
June 18, 2019
Tweet
Share
More Decks by Yusuke Kokubo
See All by Yusuke Kokubo
マネージャーゼロでマネジメントする組織
yusukekokubo
0
71
エンジニアが長く働ける会社とは
yusukekokubo
0
140
わかりやすい正解を捨てて、コトに向き合う - スクラムフェス金沢2024 スポンサーセッション
yusukekokubo
1
1.6k
BacklogがSlackやChatworkと連携したときのチームのようす
yusukekokubo
0
150
20180218BacklogWorld.pdf
yusukekokubo
2
2.6k
名古屋に住みながら毎週京都に通う生活
yusukekokubo
2
210
チーム開発を支える情報共有とそれを支えるesa
yusukekokubo
5
5.3k
Sketch入門
yusukekokubo
0
270
AgileJapan2016 島根サテライト session1
yusukekokubo
0
2.3k
Other Decks in Business
See All in Business
40代データ人材のキャリア戦略
pacocat
4
3.8k
採用向け会社紹介資料_20260105.pdf
yoshikatsu0423
0
450
「2025年のAI」と「2026年のAI」
masayamoriofficial
1
1.3k
Company Profile
katsuegu23
2
12k
LW_brochure_engineer
lincwellhr
0
40k
イークラウド会社紹介 ~挑戦で、つながる社会へ~
ecrowd
1
4.7k
Sreake事業部説明資料
3shake
0
290
続・もっと!「契約交渉よりも顧客との協調を」 〜成果報酬型やってみた結果とその先の挑戦〜
sasakendayo
0
1.7k
採用ピッチ資料
s_kamada
0
260
経営管理について / About Corporate Planning
loglass2019
0
4.6k
Morght 会社紹介資料_LAST UPDATED 2026.1
morght
1
7.6k
YassLab (株) サービス紹介 / Introduction of YassLab
yasslab
PRO
3
41k
Featured
See All Featured
Gemini Prompt Engineering: Practical Techniques for Tangible AI Outcomes
mfonobong
2
270
How to Create Impact in a Changing Tech Landscape [PerfNow 2023]
tammyeverts
55
3.2k
Chrome DevTools: State of the Union 2024 - Debugging React & Beyond
addyosmani
9
1.1k
Future Trends and Review - Lecture 12 - Web Technologies (1019888BNR)
signer
PRO
0
3.2k
Thoughts on Productivity
jonyablonski
74
5k
Leadership Guide Workshop - DevTernity 2021
reverentgeek
1
200
Exploring the relationship between traditional SERPs and Gen AI search
raygrieselhuber
PRO
2
3.6k
Designing Powerful Visuals for Engaging Learning
tmiket
0
210
Test your architecture with Archunit
thirion
1
2.1k
Getting science done with accelerated Python computing platforms
jacobtomlinson
1
110
The State of eCommerce SEO: How to Win in Today's Products SERPs - #SEOweek
aleyda
2
9.5k
AI Search: Where Are We & What Can We Do About It?
aleyda
0
6.9k
Transcript
QNKQTMBDLDPNΦϑձ +6/ ʮΑ͍ϓϩμΫτΛͭ͘ΔͨΊͷ ɹΑ͍νʔϜͷͭ͘ΒΕ͔ͨʯ גࣜձࣾψʔϥϘখٱอ༞հ
ΑΖ͓͘͠Ͷ͕͍͠·͢ɻ
#"$,-0(("5)&3*/(8*/5&3 50$ ▸ ࣗݾհձࣾհ ▸ ͱ͋ΔϓϩδΣΫτͷ ▸ ϓϩδΣΫτൃ࣌ ▸ νʔϜͷൃੜ
▸ Ͳ͏ͬͯղܾ͔ͨ͠ ▸ ͦͯ͠ແࣄʹϦϦʔε ▸ ڭ܇ 8ϲ݄͘Β͍ ͷ
ࣗݾհ
ࣗݾհ ࣗݾհ ▸ !ZVTVLF@LPLVCP ▸ ໊ݹࢢࡏॅ ▸ 4*FSˠϑΝϯτϜλΠϓ .JTPDB ˠψʔϥϘ
▸ גࣜձࣾψʔϥϘژࣄॴॴଐ ▸ ि ࣗͰϦϞʔτϫʔΫɺ ژPS౦ژPSԬʹग़ࣾ ▸ #BDLMPHνʔϜͷੜ࢈ੑΛ࠷େԽ͢ΔͨΊͷΈͮ͘ ΓΛͬͯ·͢ɻ
ژͰ͜ΜͳࣸਅΛࡱͬͯ·͢ɻ 貴船神社 鴨川 嵐⼭ 下鴨神社
ψʔϥϘͱ#BDLMPH ʹ͍ͭͯ
▸ Ԭ ຊࣾ ɺژɺ౦ژʹ։ൃڌ ▸ /FX:PSLɺ"NTUFSEBNɺ4JOHBQPSFʹ
▸ νʔϜͰͨΒ͘ɺͯ͢ͷਓͷͨΊͷϓϩδΣΫ τཧπʔϧͰ͢ ▸ 8FC੍࡞ɺιϑτΣΞ։ൃɺେखࠂཧళɺશࠃ൛৽ฉࣾͳ ͲͳͲͨ͘͞ΜͷۀछͰΘΕ͍ͯ·͢ ࣗݾհ #BDLMPHͱ ˞݄࣌
͔͜͜Βຊ
͔͜͜Βຊ ࠓͷ͓ ▸ #BDLMPHͷͱ͋Δ։ൃϓϩδΣΫτͰͷνʔϜͷʹ͍ͭ ͯɺλοΫϚϯϞσϧʹԊͬͯղઆ͠·͢ɻ νʔϜ͕ύϑΥʔϚϯεΛൃش͢Δ·Ͱʹ ͕͔͔࣌ؒΔΑɺͱ͍͏
͔͜͜Βຊ 5-%3 ▸ Α͍ϓϩμΫτΛͭ͘ΔͨΊʹΑ͍νʔϜ͕ඞཁ ▸ Α͍νʔϜΛͭ͘ΔͨΊʹ͕࣌ؒඞཁ ▸ ૣ͘Α͍νʔϜΛͭ͘ΔͨΊʹଞਓͷཧղɺ ଞਓͱͷڑײͷऔΓํΛΔ͜ͱ͕େ
#BDLMPHͷνϟοτ ΠϯςάϨʔγϣϯ ͱ͋ΔϓϩδΣΫτ
νϟοτΠϯςάϨʔγϣϯ νϟοτΠϯςάϨʔγϣϯͱ Backlogͷߋ৽Λ͓Βͤ
νϟοτΠϯςάϨʔγϣϯ νϟοτΠϯςάϨʔγϣϯͷػӡ ▸ ֎෦ͷνϟοταʔϏεͱͬͱ࿈ܞ͢Δͧʂ ▸ ͱ͍͏ʹͳΔ ʢৄ͍͠লུʣ
νϟοτΠϯςάϨʔγϣϯ νϟοτΠϯςάϨʔγϣϯΔͧʂ ▸ ͦͯ͠ϝϯόʔ͕টू͞Εͨ
ܗظ ΩοΫΦϑ
νϟοτΠϯςάϨʔγϣϯ ΩοΫΦϑ ▸ Ԭຊࣾʹ͋ͭ·ͬͯΩοΫΦϑ ▸ ϝϯόʔߏ ▸ ϓϩμΫτΦʔφʔ໊ژ ▸ ΤϯδχΞ໊Ԭ
▸ σβΠφʔ໊ژ
ΤϯδχΞA ϓϩμΫτΦʔφʔ ΤϯδχΞB ΤϯδχΞC σβΠφʔ BacklogͷதʹҰ൪͘Θ͍͠ɻ ϓϩδΣΫτʹΕͯࢀՃɻ ϓϩμΫτͷ༷ΛܾΊͨΓɺ εςʔΫϗϧμʔͱͷௐΛ͢ Δਓɻίʔυॻ͔ͳ͍ɻ
ೖࣾͯ͠·ͳ͍ɻ ψʔϥϘͰॳΊͯͷνʔϜ։ൃɻ νʔϜߏ ژ Ԭ
νϟοτΠϯςάϨʔγϣϯ λοΫϚϯϞσϧͰݴ͏ͱ ࠓ͜͜ TIME P E R F O R
M A N C E νʔϜര
νϟοτΠϯςάϨʔγϣϯ ͜ͷͱ͖ͷνʔϜͷঢ়گ ▸ ΈΜͳͰؤு͍ͬͯ͜͏ͱ͍͏งғؾ ▸ ͨͩɺҰ൪༷ʹཧղ͕͋ΔΤϯδχΞ͕Εͯࢀ Ճ͢Δͷ͕ؾ͕͔Γ ▸ Ͳ͏͍͏ϓϩηεͰࣄΛ͍͔ͯ͘͠ෆ໌
ࠞཚظ ͡·ͬͨͷ ͷʜ
νϟοτΠϯςάϨʔγϣϯ ΩοΫΦϑ͚ͨ͠ΕͲʜ ▸ ΤϯδχΞ໊ͷ͏໊ͪνʔϜ։ൃະܦݧ ▸ Δ໊ผͷϓϩδΣΫτͰɺ͙͢ʹ߹ྲྀͰ͖ͳ͍ʜ ▸ νʔϜͷ։ൃϓϩηεͷΛ͕ͯ͠·ͳ͍ʜ ▸ ΠϯςάϨʔγϣϯ։ൃҎ֎ͷอकͷΦγΰτʜ
νϟοτΠϯςάϨʔγϣϯ ΩοΫΦϑ͚ͨ͠ΕͲʜ ▸ ΤϯδχΞ໊ͷ͏໊ͪνʔϜ։ൃະܦݧ ▸ Δ໊ผͷϓϩδΣΫτͰɺ͙͢ʹ߹ྲྀͰ͖ͳ͍ʜ ▸ νʔϜͷ։ൃϓϩηεͷΛ͕ͯ͠·ͳ͍ʜ ▸ ΠϯςάϨʔγϣϯ։ൃҎ֎ͷอकͷΦγΰτʜ
ࠓ͔ͩΒݴ͑Δ͚Ͳ࣌ͷงғؾ ͋Μ·ΓΑ͘ͳ͔ͬͨ…ʂʂ
BacklogͷதʹҰ൪͘Θ͍͠ɻ ϓϩδΣΫτʹΕͯࢀՃɻ ೖࣾͯ͠·ͳ͍ɻ ψʔϥϘͰॳΊͯͷνʔϜ։ൃɻ ࣄͷਐΊํʹޱ͚ͩ͢Ͳɺࣗ·ͩϝϯ όʔ͡Όͳ͍ͷͰɺ͏·͘ΘΒͳ͍ ?? ??
νϟοτΠϯςάϨʔγϣϯ λοΫϚϯϞσϧͰݴ͏ͱ ࠓ͜͜ TIME P E R F O R
M A N C E
νϟοτΠϯςάϨʔγϣϯ λοΫϚϯϞσϧͰݴ͏ͱ ࠓ͜͜ TIME P E R F O R
M A N C E
νϟοτΠϯςάϨʔγϣϯ λοΫϚϯϞσϧͰݴ͏ͱ νʔϜͱͯ͠ύϑΥʔϚϯεΛग़ͨ͢Ίʹʁ ࠓ͜͜ TIME P E R F O
R M A N C E
ૣ͘Ͳ͏ʹ͔͠ ͳ͍ͱʜ
νϟοτΠϯςάϨʔγϣϯ ࠞཚظͱ ▸ ϝϯόʔؒͷظՁ؍ͷ͢Ε͕͍ͪ ▸ ࣗͷׂɺ૬खͱͷؔੑ ▸ ૬खʹظ͢Δ͜ͱظ͞Ε͍ͯΔ͜ͱ ▸ ͕ࣗ͞Εͯخ͍͜͠ͱݏͳ͜ͱ
νϟοτΠϯςάϨʔγϣϯ ࠞཚظͱ ▸ ϝϯόʔؒͷظՁ؍ͷ͢Ε͕͍ͪ ▸ ࣗͷׂɺ૬खͱͷؔੑ ▸ ૬खʹظ͢Δ͜ͱظ͞Ε͍ͯΔ͜ͱ ▸ ͕ࣗ͞Εͯخ͍͜͠ͱݏͳ͜ͱ
૬ޓཧղ͕ෆ͍ͯ͠Δ ʢͬͯΈͯ͡ΊͯΘ͔Δ͜ͱͳͷͰωΨ ςΟϒͳͰͳ͍ʣ ʢͨͩ͠ɺ͜ͷঢ়ଶ͕Ҿ͘ͱةݥʂʂʣ
νϟοτΠϯςάϨʔγϣϯ ࠞཚظͷνʔϜʹඞཁͳ͜ͱ
νϟοτΠϯςάϨʔγϣϯ ࠞཚظͷνʔϜʹඞཁͳ͜ͱ ▸ ϝϯόʔؒͷظՁ؍ͷ͢Ε͕͍ͪΛຒΊΔ
νϟοτΠϯςάϨʔγϣϯ ࠞཚظͷνʔϜʹඞཁͳ͜ͱ ▸ ϝϯόʔؒͷظՁ؍ͷ͢Ε͕͍ͪΛຒΊΔ ▸ ࣗͷׂɺ૬खͱͷؔੑ
νϟοτΠϯςάϨʔγϣϯ ࠞཚظͷνʔϜʹඞཁͳ͜ͱ ▸ ϝϯόʔؒͷظՁ؍ͷ͢Ε͕͍ͪΛຒΊΔ ▸ ࣗͷׂɺ૬खͱͷؔੑ ▸ ࣗͲ͏͍͏ਓͳͷ͔
νϟοτΠϯςάϨʔγϣϯ ࠞཚظͷνʔϜʹඞཁͳ͜ͱ ▸ ϝϯόʔؒͷظՁ؍ͷ͢Ε͕͍ͪΛຒΊΔ ▸ ࣗͷׂɺ૬खͱͷؔੑ ▸ ࣗͲ͏͍͏ਓͳͷ͔ ▸ ૬खʹظ͢Δ͜ͱظ͞Ε͍ͯΔ͜ͱ
νϟοτΠϯςάϨʔγϣϯ ࠞཚظͷνʔϜʹඞཁͳ͜ͱ ▸ ϝϯόʔؒͷظՁ؍ͷ͢Ε͕͍ͪΛຒΊΔ ▸ ࣗͷׂɺ૬खͱͷؔੑ ▸ ࣗͲ͏͍͏ਓͳͷ͔ ▸ ૬खʹظ͢Δ͜ͱظ͞Ε͍ͯΔ͜ͱ
▸ ࣗԿΛظ͍ͯ͠Δʁ૬खʹԿΛظ͍ͯ͠Δʁ
νϟοτΠϯςάϨʔγϣϯ ࠞཚظͷνʔϜʹඞཁͳ͜ͱ ▸ ϝϯόʔؒͷظՁ؍ͷ͢Ε͕͍ͪΛຒΊΔ ▸ ࣗͷׂɺ૬खͱͷؔੑ ▸ ࣗͲ͏͍͏ਓͳͷ͔ ▸ ૬खʹظ͢Δ͜ͱظ͞Ε͍ͯΔ͜ͱ
▸ ࣗԿΛظ͍ͯ͠Δʁ૬खʹԿΛظ͍ͯ͠Δʁ ▸ ͕ࣗ͞Εͯخ͍͜͠ͱݏͳ͜ͱ
νϟοτΠϯςάϨʔγϣϯ ࠞཚظͷνʔϜʹඞཁͳ͜ͱ ▸ ϝϯόʔؒͷظՁ؍ͷ͢Ε͕͍ͪΛຒΊΔ ▸ ࣗͷׂɺ૬खͱͷؔੑ ▸ ࣗͲ͏͍͏ਓͳͷ͔ ▸ ૬खʹظ͢Δ͜ͱظ͞Ε͍ͯΔ͜ͱ
▸ ࣗԿΛظ͍ͯ͠Δʁ૬खʹԿΛظ͍ͯ͠Δʁ ▸ ͕ࣗ͞Εͯخ͍͜͠ͱݏͳ͜ͱ ▸ ࣗͲ͏͍͏ͱ͖ʹςϯγϣϯ্͕Δʁͦͷٯʁ
νϟοτΠϯςάϨʔγϣϯ ਓؒؔڑײ͕େ
νϟοτΠϯςάϨʔγϣϯ ͦ͜Ͱͨͪߟ͑ͨ ▸ ݸਓͷਓؒੑΛΔ͜ͱ ▸ ͓ޓ͍ͷؔੑΛΔ͜ͱ
νϟοτΠϯςάϨʔγϣϯ ͬͨ͜ͱ ▸ ϝϯόʔͱͷPO ▸ ݸਓϨϕϧͰͷҙࣝʹ͍ͭͯͷڞ༗ ▸ ϝϯόʔ͕͓ޓ͍ͷਓؒੑΛཧղ͢Δ ▸ υϥοΧʔ෩ΤΫααΠζ
̋̋ͬͯΔͱ͖͕ Ұ൪ςϯγϣϯ͕͋Δʂʂ ˚˚ۤखͳͷͰ Ίͯ΄͍͠…
▸ ϝϯόʔͲ͏͕͠૬खͷ͜ͱΛΔ͜ͱ͕Ͱ͖ͨ ▸ ීஈ͕ࣗԿؾͳ͘ݴͬͯͨ͜ͱ͕ɺ૬खΛই͚͍͔ͭͯͨ͠ Εͳ͍ɺͱࣗવͱলΛଅ͢Α͏ʹͳͬͨ νϟοτΠϯςάϨʔγϣϯ ͦͷ݁Ռ ීஈԿؾͳ͘ݴͬͯͨ͜ͱ ͕ই͚͔ͭͯͨ… ࢥ͍ͬͯͨϞϠϞϠΛ͑
Δ͜ͱ͕Ͱ͖ͯεοΩϦʂ
▸ ϝϯόʔͲ͏͕͠૬खͷ͜ͱΛΔ͜ͱ͕Ͱ͖ͨ ▸ ීஈ͕ࣗԿؾͳ͘ݴͬͯͨ͜ͱ͕ɺ૬खΛই͚͍͔ͭͯͨ͠ Εͳ͍ɺͱࣗવͱলΛଅ͢Α͏ʹͳͬͨ গͣͭ͠ίϛϡχέʔγϣϯΛ औΕΔΑ͏ʹͳ͖ͬͯͨ νϟοτΠϯςάϨʔγϣϯ ͦͷ݁Ռ ීஈԿؾͳ͘ݴͬͯͨ͜ͱ
͕ই͚͔ͭͯͨ… ࢥ͍ͬͯͨϞϠϞϠΛ͑ Δ͜ͱ͕Ͱ͖ͯεοΩϦʂ
౷Ұظ زଟͷࠞཚΛܦ ͯʜ
νϟοτΠϯςάϨʔγϣϯ ঃʑʹνʔϜʹͳ͖ͬͯͨ ࠓ͜͜ TIME P E R F O R
M A N C E
νϟοτΠϯςάϨʔγϣϯ νʔϜͱͯ͠ػೳ͢ΔΑ͏ʹ ▸ ேձޙͷϞϒϓϩͱ͔ϓϧϦΫͷϨϏϡʔ ▸ ؾʹͳΔ͜ͱ͕͋ΕϖΞϓϩ ▸ ຖिͷ;Γ͔͑ΓͰ։ൃϓϩηεͷݟ͠
νϟοτΠϯςάϨʔγϣϯ νʔϜͱͯ͠ػೳ͢ΔΑ͏ʹ ▸ ேձޙͷϞϒϓϩͱ͔ϓϧϦΫͷϨϏϡʔ ▸ ؾʹͳΔ͜ͱ͕͋ΕϖΞϓϩ ▸ ຖिͷ;Γ͔͑ΓͰ։ൃϓϩηεͷݟ͠ ҆ఆͯ͠ਐḿΛग़ͤΔΑ͏ʹͳͬͨʂʂ
νϟοτΠϯςάϨʔγϣϯ νʔϜͱͯ͠ػೳ͢ΔΑ͏ʹ ▸ ேձޙͷϞϒϓϩͱ͔ϓϧϦΫͷϨϏϡʔ ▸ ؾʹͳΔ͜ͱ͕͋ΕϖΞϓϩ ▸ ຖिͷ;Γ͔͑ΓͰ։ൃϓϩηεͷݟ͠ ୭͔ٳΜͰɺ ଞͷਓͰΧόʔͰ͖ΔΑ͏ʹͳͬͨ☺ʂʂ
҆ఆͯ͠ਐḿΛग़ͤΔΑ͏ʹͳͬͨʂʂ
ࣗવͱձ͕ੜ·ΕΔؔੑ ΈΜͳͰҰͭͷࣄΛਐΊΒΕΔΑ͏ʹͳͬͨ!!
νϟοτΠϯςάϨʔγϣϯ ͪͳΈʹ͜ͷͱ͖ͷ#BDLMPHͷ͍ํ ▸ ՝ʮ'FBUVSFʯ ▸ ϢʔβʔετʔϦʔ ▸ ड͚ೖΕ݅ ▸ ࢠ՝ʹʮ5BTLʯ
▸ ࣮ ▸ ςετ ▸ FUD ͜ͷεϥΠυͰ།ҰͷBacklogͷ
ػೳظ ͜͜·ͰདྷͨΒແ ఢ
νϟοτΠϯςάϨʔγϣϯ ͖ͦͯ͠ʜ ࠓ͜͜ TIME P E R F O R
M A N C E
νϟοτΠϯςάϨʔγϣϯ زଟͷࠔΛܦͯʜ ▸ ʢ͢ͱ͘ͳΔͷͰলུʣ
ϓϩηεͷվળΈΜͳͰҙݟΛग़͠߹͑ΔΑ͏ʹ ҆ఆͨ͠ਐḿΛग़ͤΔΑ͏ʹͳ͖ͬͯͨ
νϟοτΠϯςάϨʔγϣϯ ͍ͭʹϦϦʔεʂʂ
νϟοτΠϯςάϨʔγϣϯ Ԡྑ͍ײ͡
νϟοτΠϯςάϨʔγϣϯ ڭ܇ ▸ νʔϜͷܗʹ͕͔͔࣌ؒΔ ▸ εέδϡʔϧʹΓࠐΜͰߟ͑Α͏ ▸ νʔϜ͕ࠞཚظʹೖͬͯ͜Θ͕Βͳ͍ ▸ ͲΜͳνʔϜͰඞͣ௨Δಓ
▸ ਓؒؔڑײ͕େ ▸ ݸਓͷਓؒੑΛΔ͜ͱ ▸ ͓ޓ͍ͷؔੑΛΔ͜ͱ
·ͱΊ Α͍ϓϩμΫτΛͭ͘Δ ʹ Α͍ϓϩμΫτΛͭ͘ΔνʔϜΛͭ͘Δ ʹ νʔϜΛͭ͘ΔʹਓؒੑΛཧղ͢Δ ʹ ϓϩμΫτΛͭ͘ΔͱਓΛཧղ͢Δ͜ͱ
νϟοτΠϯςάϨʔγϣϯ ':*(PPHMFSF8PSL ৺ཧత҆શੑ͔Γ͕ڧௐ͞ΕΔ͚Ͳɺ ϝϯόʔ͕͓ޓ͍ʹ૬ޓ৴པͰ͖Δ ؔͮ͘Γͱͯେͩͱࢥ͏ɻ
νϟοτΠϯςάϨʔγϣϯ ͦͯ͠ղࢄʜ ▸ ମ੍มߋʹΑΓνʔϜ੯͠·Εͭͭղࢄʜ ▸ ΄Μͱͬͱ৭ʑΓ͍ͨ͜ͱ͕͕͋ͬͨʜ ▸ ͦΕͰΈΜͳͰ͜ͷϓϩδΣΫτΛ௨ͯ͠νʔϜ ։ൃͷૉΒ͠͞ΛΕͨͷوॏͳࡒ࢈ʹͳͬ ͨ
͋Γ͕ͱ͏͍͟͝·ͨ͠ɻ