Business Intelligence & Analytics as a Service. Warehouse logistics

Transcription

1 Business Intelligence & Analytics as a Service Warehuse lgistics

2 Business Intelligence & Analytics Business Intelligence Analytics Business Intelligence (BI) incrprates the cllectin, strage, elabratin and analysis f data, as a frm f supprt fr business decisins Frm data t infrmatin Analytics represent the analytical steps and instruments necessary t cnduct BI KPI, alerting, frecasting mdels Warehusing BI Warehusing BI is a series f activities used t cnvert data riginating frm warehuses int infrmatin which is useful fr business lgistics decisins 2

3 The prject: areas f analysis Prductivity and Quality Prductivity represents the area f analysis used t assess the utput f warehuse peratrs and their prductivity based upn an hurly basis. Principal KPIs are calculated n the basis f the times indicated fr each assignment and fr the mvement and equipping f warehuse peratrs. The quantities mved by each peratr are als indicated. Quality represents the area f analysis used t mnitr the breakage and lss f bjects and inefficient peratins. Principal KPIs are calculated upn measuring the number f bjects (packages and items) brken r lst. Other KPIs indicate the number f specific peratins cnsidered t be inefficient (eg. quta picking). Prductivity Quality 3

4 The prject: areas f analysis Gds in Stck & Space Fcus n analysis f gds in stck and space is used t mnitr the saturatin f space within warehuses. Principal KPIs indicate the percentage f saturatin, measured in terms f the cmpartments, spaces and vlumes within each warehuse. Other KPIs are used t measure quantities in terms f packages, pallets, lading units and quintals f stck in each warehuse. Gds in Stck & Space 4

5 The prject: areas f analysis Lifecyle f Orders and LUs Analysis f rders and dcuments is generally intended fr the assessment f rder dispatch times. Principal KPIs are used t measure the duratin f each phase r phases f the rder dispatch prcess. These times are then cmpared with estimated times in rder t assess time discrepencies and relative punctuality. Orders Analysis f LUs is intended fr the mnitring f the lading unit lifecycle. Principal KPIs are used t measure the duratin f the varius phases f the Lading Unit lifecycle, which are then cmpared with the varius estimated times, in rder t assess the efficiency and punctuality f the prcesses. LU (Lading Unit) 5

6 Definitin f Analytics Analytics is the prcess f btaining an ptimal r realistic decisin based n existing data 6

7 Analytics Summary indicatrs f the phenmena and dimensins f interest available in the database r calculated by the user. Traffic light mechanisms which prmptly indicate when predetermined r definable safety threshlds are exceeded. The pssibility t simulate scenaris and bjectives depending n the cnditins selected by the user, fr the purpse f ptimising the use f resurces and supprting business decisins. 7

8 Alerting and What If (1/2) Prductivity Quality What If Hw can resurces be best distributed in rder t reduce waiting times? Hw wuld prductivity levels benefit frm the imprved allcatin f items in cmpartments? Hw many units need t be added t the wrkfrce in rder t facilitate increased prductivity? Hw wuld the prductivity rate vary if mvement times were reduced? What wuld be the impact f a reductin in resurces in terms f hurly prductivity? What advantages wuld be gained in terms f prductivity by ptimising and reducing inefficient activities? What impact wuld the reductin r zering f inefficient activities have n the number f resurces required? What advantages wuld a reduced number f breakages have n the general qualitative index? What advantages wuld the eliminatin f defects in the checking prcess have in terms f peratr prductivity? Operatr activity mnitring Timely and fcused studies in rder t Alerting understand the reasn fr anmalies such as: decline in the quality f an peratr s wrk incrrect displacement f gds in cmpartments 8

9 Alerting and What If (2/2) Gds in Stck & Space Orders and LUs What If Map simulatin f gds in each cmpartment and assessment f relative efficiency based n: varius distributin f gds during strage/exit phase ptimisatin f wrk and wrker assignments ptimised distributin f resurces frecast f time savings and increase in prductivity subsequent t imprved rganisatin f space Hw wuld an increase in qualified staff numbers benefit the respect f planned times? Hw wuld imprved peratr prductivity benefit the punctuality f rder dispatches? Hw wuld mre efficient management f LUs benefit the respect f planned times? By hw much wuld the punctuality rate increase as a result f cmpressed waiting times? Alerting Assessment f warehuse stck levels Mnitring instances where the maximum times freseen fr each phase are exceeded. 9

10 Architecture: SaaS/Clud fcus Architecture n client interfacing Clients Database Internet Files Virtual Private Netwrk (VPN Cnnectin) Infrmatin is extracted frm cnnected client systems n a daily basis r several times per day, depending n applicatin requirements and the vlume f data t be transferred. These peratins are carried ut using an internet cnnectin within a virtual private netwrk with a high level f security. Data extracted frm client systems is depsited int the Reply clud and is subsequently subjected t cnversin and upladed t structures suitable t user reprting and analysis. 10 Reply Clud

11 Reply Supply Integratin with SaaS/Clud architecture System prvided by Reply Data Mdel Structures Frnt-End Prjects Alerting systems and What-if analysis (Analytics) Persnalisatin prvided by Reply Prcedures fr extractin frm client s remte perating systems Prcedures fr the cnversin f extracted data and the ppulatin f the data mdel Client Systems Warehuse Operating Systems 11

12 Thanks