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Big Data: turnover analysis in
a contact center
2016
Big data
Volume
Variety
Velocity
Анализ текучки в контактном центре
Анализ текучки в контактном центре
• 5,893 оператора,
• которые работали в Global Bilgi с 1/1/2010 по сегодняшний
день (6.5 лет)
Disclaimer
• Full-time
• Part-time
• Part-time 2
• Загрузка данных
• Подготовка данных
Средний срок работы
оператора в контактном
центре
(6 месяцев или 3 месяца)
7
Средний срок
работы
оператора в
контактном
центре
Mean = 6.75 мес
Median = 3 мес
Сезонность
9
Сезонность
набора
10
Сезонность
текучки
11
Сезонность
набора и текучки
• В мае увеличивается
отток, а набор в мае и
июне маленький
• В августе увеличивается
отток, а набор в
августе и сентябре
маленький
• Отток перед Новым
Годом можно восполнить
в январе
Что влияет на текучку?
13
Локации
14
Тим-лидеры
15
Full-time / part-
time
Ответ – кластерный
анализ
17
18
Кластерный
анализ
19
Кластерный
анализ
Кластер 1 Кластер 2
Средний стаж 4.33 мес 13.3 мес
Средняя зарплата 719 грн 1762 грн
Neural networks model
21
Neural networks
model
Агент Стаж Тим-лидер Локация Вероятность ухода
 53 atraKaravaDnipropetrovsk 70%
 11 rholoa Sumy 60%
 42 atraKaravaDnipropetrovsk 70%
 40 rholoa Sumy 67%
 37 astasaUovchoKyiv 57%
 19 lsaaso Dnipropetrovsk 79%
 25 rholoa Sumy 76%
 25 NatalaMaoo Kharkiv 72%
 23 Ialoo Sumy 61%
 23 IraKrasovsaaDnipropetrovsk 79%
 16 astasaUovchoKyiv 80%
 14 OlsarhpatsvSumy 57%
 14 Ialoo Sumy 74%
 14 KaraChrooovaKharkiv 77%
 13 NatalauaovaSumy 57%
 13 rholoa Sumy 77%
 13 vtlaarubovaDnipropetrovsk 73%
 13 NatalauaovaSumy 65%
 12 rDhtaro Dnipropetrovsk 80%
 12 rDhtaro Dnipropetrovsk 61%
 12 OlsarhpatsvSumy 73%
 12 NatalauaovaSumy 72%
 12 KaraChrooovaKharkiv 72%
 12 KaraChrooovaKharkiv 72%
 12 vroov Kharkiv 61%
 11 uslaur Sumy 58%
 10 rtmlsarov Dnipropetrovsk 78%
 10 rtmlsarov Dnipropetrovsk 60%
 10 uslaaoroh Dnipropetrovsk 74%
• 146 операторов в зоне
риска (вероятность
ухода от 56 до 80%)
• 49% ушло в следующем
месяце
Thank you

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Global Bilgi. Big Data: turnover analysis in a contact center

  • 1. Big Data: turnover analysis in a contact center 2016
  • 3. Анализ текучки в контактном центре
  • 4. Анализ текучки в контактном центре • 5,893 оператора, • которые работали в Global Bilgi с 1/1/2010 по сегодняшний день (6.5 лет)
  • 5. Disclaimer • Full-time • Part-time • Part-time 2 • Загрузка данных • Подготовка данных
  • 6. Средний срок работы оператора в контактном центре (6 месяцев или 3 месяца)
  • 11. 11 Сезонность набора и текучки • В мае увеличивается отток, а набор в мае и июне маленький • В августе увеличивается отток, а набор в августе и сентябре маленький • Отток перед Новым Годом можно восполнить в январе
  • 12. Что влияет на текучку?
  • 17. 17
  • 19. 19 Кластерный анализ Кластер 1 Кластер 2 Средний стаж 4.33 мес 13.3 мес Средняя зарплата 719 грн 1762 грн
  • 21. 21 Neural networks model Агент Стаж Тим-лидер Локация Вероятность ухода  53 atraKaravaDnipropetrovsk 70%  11 rholoa Sumy 60%  42 atraKaravaDnipropetrovsk 70%  40 rholoa Sumy 67%  37 astasaUovchoKyiv 57%  19 lsaaso Dnipropetrovsk 79%  25 rholoa Sumy 76%  25 NatalaMaoo Kharkiv 72%  23 Ialoo Sumy 61%  23 IraKrasovsaaDnipropetrovsk 79%  16 astasaUovchoKyiv 80%  14 OlsarhpatsvSumy 57%  14 Ialoo Sumy 74%  14 KaraChrooovaKharkiv 77%  13 NatalauaovaSumy 57%  13 rholoa Sumy 77%  13 vtlaarubovaDnipropetrovsk 73%  13 NatalauaovaSumy 65%  12 rDhtaro Dnipropetrovsk 80%  12 rDhtaro Dnipropetrovsk 61%  12 OlsarhpatsvSumy 73%  12 NatalauaovaSumy 72%  12 KaraChrooovaKharkiv 72%  12 KaraChrooovaKharkiv 72%  12 vroov Kharkiv 61%  11 uslaur Sumy 58%  10 rtmlsarov Dnipropetrovsk 78%  10 rtmlsarov Dnipropetrovsk 60%  10 uslaaoroh Dnipropetrovsk 74% • 146 операторов в зоне риска (вероятность ухода от 56 до 80%) • 49% ушло в следующем месяце