Projects and Resources Optimization for IT Enterprises Cipriano

Projects and Resources Optimization for IT Enterprises Cipriano

Projects and Resources Optimization for IT Enterprises Cipriano (Pano) Santos (Homo Habilis) Deep Analytics Distinguished Technologist HP-IT Global Program Management Office In preparing for battle, I have always found that plans are useless, but planning is indispensable Dwight D. Eisenhower Practice of mathematical Optimization: A personal view Practice of mathematical Optimization Reality Perceived Problem Modeling Stage Mathsmith Slide 3 Copyright 2015 Hewlett Packard Enterprise | Reformulation Stage Algorithm Stage OR-Practitioner

(Applied Mathematician) Computer-Scientist Mathematician Global Information Technology (GIT) Polyhedra Combinatorics In Polyhedra Combinatorics the art of modeling is 1) to translate a business problem into a set linear inequalities 2) and the LP model should be tight (good representation) Polyhedra Combinatorics enables a declarative approach 1) Formulate your problem as an LP (MILP), and Linear Programming solution techniques solves your problem 2) If your problem change, modify formulation but same Linear Programming solution techniques solves your problem 3) Polyhedra Combinatorics are easier to develop and maintain Slide 4 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT)

Workforce Planning and Polyhedral Combinatorics 5 Workforce Planning People is the most important asset in the Knowledge Economy, in particular in the Services Industry such as IT companies/organizations Large IT organizations employ thousands of IT professionals to deliver a wide variety of services (jobs) to customers, consequently labor is the IT Industry most expensive cost Resource supply-demand matching in large IT organizations is challenging when one considers that there are thousands of employees, with thousands of skills to be optimally mapped to thousands of services (jobs). Slide 6 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) It is clear that the manual spread-sheet-driven approaches used today in Workforce Planning for IT organizations attrition SDLCM IT Service Demand Slide 7 Project Tasks Projects

Portfolio Process Flow Service Demand Forecast Contact Centers Calls, or Transactions Big Data Mining BoL Labor Requirements Forecast Big Data Mining Copyright 2015 Hewlett Packard Enterprise | Sup/Dem Matching: = Optimal Gap Closing Global Information Technology (GIT) Labor Fulfillment

Plan IT Labor Supply Labor Transformation & Procurement Plans Big Data Mining Vision Workforce Planning Hierarchical Architecture Workforce Planning Hierarchical Planning Architecture Strategic Project Staffing Strategy Inputs Revenue/Headcount Demand Forecaster Pyramids TCOW or margin targets Local labor content rules Bill-of-Labor Estimation Account level ($) Portfolio/offering level ($) Job level (HC) Revenue Forecast

Bill-of-Labor templates Labor Inventory (Supply) Vital Data Labor Strategy Optimizer(LSO) Assignments Inventory Attrition rate Learning curve Attrition Attrition rate Forecaster forecast Aggregated Project Staffing Project Win Probability Correction Tactical Operational Detailed Project Staffing Project winning probabilities HPL Modules Ready HPL Module Q12014 Input Slide 9

PPMC Hiring bounds Labor Pyramids Demand: SOW/RFQ, .. Supply: Resume (SABA/Linkedin) Project Portfolio Optimization (PPO) Opportunities Funnel Resource Planner (RMO) Structured supply/demand information RP-Miner Processing Unstructured Info Account/Project Execution Optimizer(PPMC) Structured supply/demand information Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Hierarchical Planning Strategy model Given a Target revenue of business units of the Service Enterprise determine budgets for Location Strategy: onshore/offshore, Labor mix strategy: RWF/CWF (role & capability) and 3PP , and Labor Transformation strategy: Training/re-skilling, hiring/Layoffs, Promotions/demotions

in such a way Enterprise total gross margin is maximized while satisfying resources and business constraints. Tactical model For a given labor mix strategy (RWF/CWF), labor location strategy (onshore/offshore), labor transformation, and a given collections of projects (recommended, in-flight, on-hold, etc.), select and schedule a portfolio of projects that optimizes the trade-offs of conflicting business objectives while considering budgets, labor resources, and other business constraints. This model determines the labor resource requirements to fill the jobs of selected projects Operational model Given the resource requirements that fill the jobs of selected projects during the duration of the projects, determine best resources (by name) available to fill the resource requirements of jobs of selected projects in optimal portfolio. Execution Track execution and provide feedback loops to Operational/Tactical/Strategy models Slide 10 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Labor Strategy Optimization LSO Labor Strategy Optimization (LSO) model Operational framework: Inputs (continue) Business Unit Geography: Global, Region, Country, Planning Horizon and time period Period Rolling horizon and Frozen window Demand: Apps Service Lines Labor Nomenclature: Job function or role, JAI Level Costs (Onshore/offshore, RWF/CTW), : Salary & Benefits, hiring/on-boarding costs, severance costs,

training costs Output: Location ([Onshore, Offshore] current & new ), Labor Mix (RWF, Off_On_shore Temporal relocation, CTW), Workforce Transformation (Training, Career Path, Hiring, WFR), Attrition Replacement Management and Planned Labor Pyramids Inputs: Demand signal forecast: Revenue (ASPIRE). Funnel of project opportunities. . Ongoing projects Attrition Replacements Execution: Inputs for Labor Tactical Optimization: Service Line target labor pyramids. Labor financial & time productivity HR Corp TCOW reduction strategies: Onshore/offshore RWF inventories. Training & career path rules Planned Planned Planned Planned capacity of RWF onshore/offshore

inventory/budget of CTW onshore/offshore inventory/budget for training and career path inventory/budget for hiring Inputs for demand planning Onshore/offshore quotas for sales and pursue teams Inputs for supplier consolidation Planned inventories and reserved price for total CTW based on labor nomenclature Slide 12 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) CCP algorithm REVPM = $3.5M/PM Revenue: $14.706M ASO% = 18% 3PP% = 14% 1-ASO% - 3PP% = 68% $RATE = $10K/day $10M NbDays Sold 1000 Billable days $2.647M HP &CTW Revenue

$2.058M 3PPartners Revenue ASO Revenue [ CORE%*(1 -- CTW%) + (1 BID)*CTW% -- RISK% ] = 0.64 1562.5 working days Number of FTE needed NbDays Needed WDAYS = 130 days/person Internal HP FTE 4.202 SA 4 1 3 Slide 13 0.287 0.962 PM PM

0 9.62 FTE 1 2.4 FTE TC 4 0 GAP = FTE_Req --- FTE_Inv SA 2015 Hewlett BC Packard Enterprise TC Copyright 1 CTW 4.369 FTE Requirements BC 0 0 12.02 FTE 0 6 |

Global Information Technology (GIT) FTE Inventory Work Utilization CORE% = 70% CTW% = 20% BID% = 10% RISK% = 10% SA% = 10% BC% = 3% CCP Linear Programming model Max GM = Revenue (3PP + Offshr + CTW) costs CTW cost = ctwcost*XCTWREQ Offshr cost = XOffshr*offshrcst% 3PP cost = X3PP*ppcost% (Cross train costs) Revenue: $14.706M Rev = XHPCTW+XOffshr+X3PP Labor Strategy XHPCTW NbDays Sold HP &CTW Revenue 3PPartners Revenue ASO Revenue

XOffshr> Rev*Offshr% (18%) X3PP > Rev*3PP% (14%) WDAYS*[ CORE%*XHPREQ + (1 BID%)*XCTWREQ ]*$RATE = XHPCTW Number of FTE needed NbDays Needed XFTEREQ = XHPREQ + XCTWREQ Labor split rates: REVPM*XPMREQ = Rev Internal HP FTE XSAREQ = XHPREQ*SA% XBCREQ = XHPREQ*BC% FTE Requirements CTW XCTWREQ > XFTEREQ*CTW% (20%) XHPREQ = XPMREQ + XSAREQ + XBCREQ + XTCREQ HP FTE Requirements PM Slide 14 SA PM BC

TC SA 2015 Hewlett BC Packard Enterprise TC Copyright 1 1 0 XPMREQ (+ XTOUT) < pminv (+ XTIN) XSAREQ (+ XTOUT ) < sainv (+ XTIN) XBCREQ (+ XTOUT) < bcinv (+ XTIN) XTCREQ (+ XTOUT) < tcinv (+ XTIN) | Global Information Technology (GIT) 6 FTE Inventory Project Portfolio Optimization PPO Problem Description LSO provides planned labor capacity of resources (and associated budgets) to support target revenues of BUs BUs in turn generates projects to match the target revenues Then the question is How to optimize the selection and scheduling of a portfolio of HP-IT projects such that the trade-offs among various objectives are optimized While satisfying resource constraints FTE (differentiated by skills and role) and budget (differentiated by various types of IT costs such as Labor IT costs, Non-Labor IT costs, Total IT costs, Business costs, Total costs) constraints Other business constraints Project precedence constraints

Project Release date and due date Project composition Mix Logical constraints Copyright 2015 Hewlett Packard Enterprise Slide 16 Pre-select and de-select decisions | Global Information Technology (GIT) PPO Tool PPO is a decision support tool That automates current manual number crunching process And provides What if analysis capabilities PPO helps planners (users) To shape a project portfolio that optimize the trade-offs of the various objectives and constraints (Project Ranking, Project Score, Project Benefit, Project ROI, Budget limits, and Resource utilization) Slide 17 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Why This Matters Slide 18 Data driven decisions

User completely drives optimization engine Powerful scenario analysis Team Optimization Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) The Project Portfolio Optimization tool is a multi-objective decision support tool for choosing the optimal portfolioSet constraints for optimization, these could include: Project Release and due date Budget (& Labor) capacity constraints Portfolio Shaping ensure that at least 20% of the HC of selected projects corresponds Load project and resource data from PPM and value data from BVP 0. Load portfolio & value data 1. Set constraints & Optimization Mechanism 3. Review

output and select Review output and repeat process using different models or constraints as necessary Repeat steps 1 through 3 until portfolio decision reached Optimization Mechanisms: BOM: In this optimization mechanism, the decision-maker considers a single objective for optimization 2. Run PPO model The model can find inconsistencies in the data and make recommendations about how to correct the data inconsistencies Slide 19 to R&D investment area Planners (user) preference guidelines Select/de-select project constraints Fix (flexible) start time of project XOR logical constraints Select at most 1 option among several alternatives (FTE, Budget) of deploying same project) IFF logical constraints For a Program of projects either select all projects in program or none of them Project precedence constraints Project P2 can start after completing 80% of project P1 Copyright 2015 Hewlett Packard Enterprise

| MCRM: In this optimization mechanism, the decision-maker considers multiple objectives for optimization The decision-maker has a priority order for the set of objectives POM: In this optimization mechanism, the decision-maker is interested on a pair of conflicting criteria and wants to optimize the tradeoffs between these pair of conflicting criteria Global Information Technology (GIT) # Yp variables # Xpt variables # Zpt variables # Zipto variables Total # of variables Total # of constraints Gurobi solving time Gurobi solving time no presolve Coin-OR Slide 20 Regular PPO formulation Optimized PPO formulation 108 108 3062 3062 3062 0 3062 0 9307 3183 6461 337 8.53 s 7.97 s 156.1 s 19.9 s 40291.24 s

82.3 s Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) PPO Stories: other ways PPO technology can help #0 Project portfolio optimization #1 Projects Scheduling #2 There are many ways to get a project done #3 React to change #4 Next generation What-if analysis #5 Top-Down portfolio optimization Slide 21 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Resource Matching Optimization RMO Resource Planning Assume an Optimized Project Portfolio: you know which projects to pursue and when the projects starts. Each project has a set of jobs to be done, each job has duration and labor resource requirements Then the question that Resource Planning address is: How to identify the employees that can fill the jobs The main objectives of Resource Planning in the Services Industry are to Increase workforce utilization Optimize labor costs

Optimize the matching of job requirements with employee qualifications The fundamental problem of Workforce Planning is to provide the workforce resources with the right skills, for the right job, at the right time, Slide 23 at the right location, Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Resource Planning (2) Workforce planning faces both demand and supply uncertainty Demand main sources of uncertainty: Uncertainty about winning a project opportunity Uncertainty about starting time, (duration, resource requirements of projects) Supply main sources of uncertainty: Attrition Uncertainties around hiring Long hiring and labor transformation lead times Workforce planning under uncertainty cannot be done at the detailed skill-set level A standard labor Taxonomy is required Objective: Optimal (cost & skill) demand fulfillment Balance workforce utilization and availability Quantify and cope with associated risks Slide 24 Copyright 2015 Hewlett Packard Enterprise |

Global Information Technology (GIT) 1) Supply data: Employee classified by skill group/Job Attributes. 2) Demand data: Job requirements by opportunities and periods. 3) Planning Scenario Input data (demand &supply) set to run planning engine. 4) Output Plan Reports List of planning engine suggestions by given scenario. Resource Planner Demand & Supply Consolidation Input +List of selected projects +Job-project requirement + Employee Qualifications & Trainability, moves +job attrition rates emp Job-Projects Mathematical Optimization Input +Availability of Resources +Hiring & training lead-times + Job-Opportunity requirement + employees job qualifications & trainability +Job replacement requirements due to attrition Min

j xj jJ s.t a i, j Output +Supply & Demand expressed in terms of jobs + Flexible Mapping 1) Allocation Plan 2) Workforce Transformation Plan x j bi i I jJ xj S j j J 3) Hiring Plan Slide 25 Engine Copyright 2015 Hewlett Packard Enterprise |

Global Information Technology (GIT) Employee-job characterization RP Matching Taxonomy Employee Labor Demand Job Attributes Qualified for Specified as Defined as Belongs to Capability Role Job Level Industry WF Domain Type Location Location Resource Business Job Code (site) Type Pool Segment Organizational Attributes Technology/Platform uses Example

CapabilityApps Development, IT Admnistration WFtype RWF or CWF Skills Job level ENT, INT, EXP, MAS Tools Role Developer, Manager Industry Domain Manufacturing, Aerospace, Finance, Location Type: Onsite, Offshore Slide 26 Technical Attributes Location Bangalore, Chennai (offshore), USA, Germany, UK (on site) Copyright 2015 Hewlett Packard Enterprise | Job Code: ENG0001 Global Information Technology (GIT) Resource Pool: AMS Healthcare Applications Business segment: Apps Employee scoring algorithm There are no real cost associated to mapping employees with job requirements of projects in the optimal portfolio there is the problem of discriminating good matches from bad matches automatically RP engine computes employee scoring based on the individual matching of each attribute and their importance expressed as weights. Resource1 Job Requirement Max Weight Java

Java 50 50 Manufacturi 20 20 15 2.625 Any Intermediat e Regular Offshore Offshore 4 2.8 Any Bangalore 1 0.7 Manufacturin g

Entry Resource1 is not fully qualified training ng 10 Employee Ranking Resource2 Job Requirement Max Weight Java Java 50 50 50 Manufacturi 20 20 20 15 0 15

Any Intermediat e Contingent 10 10 0 Offshore Onshore 4 4 0 Any US 1 1 0 Manufacturin g Entry training ng Employee

Ranking Slide 27 Similarity Score 85 Copyright 2015 Hewlett Packard Enterprise | 7 83.125 % Hierarchy dependency Similarity Score 85 % Similarity Score No hierarchy Global Information Technology (GIT) Similarity function RP mathematical models Matching future availability of employees with future job requirements is quite complex GDAS has thousands of employees in delivery roles, with thousands of skills; hence the number of combinations of people, skill, win time, and location is astronomically large. Convolution Bench

i Mathematical Optimization P 75% Accumulative Probability of Requirement 100% GDAS Funnel of Opportunities Bernoulli: Prob distribution p of SG requirements Pr{ X ) i i, j by opportunity 1 pi X i , j xi , j X i , j 0 90% 80% Service Level 70% 60% 50% 40% Prob of total SG requirements Computed as a convolution. 30% X j X i , j

20% 10% i Pi win 75% 14400 12600 9000 10800 7200 5400 3600 1800 0 0% SG Demand at SL Staff projects with deterministic demand using MIP Staff Bench at SL for all SG Bench includes attrition replacements Optimization model must encode business rules Min ( T (t 1)) * winprbi * RLi * gap j ,i ,t CT * xt w, j ,i ,t CH * h j ,i ,t high probability opportunities are first staffed with available employees. j ,i ,t

w , j ,i ,t j ,i ,t Low priority opportunities are staffed with hiring/gap Practice building requirements are satisfied with people hired Constraints Slide 28 Gaps are filled by training employees Remaining gaps are filled with hiring Satisfy priority opportunity requirements Satisfy employee capacity & capability constraints t CIa * (inv j ,i ,t a j ,i ,t ) CIx ( Rw, j ,i ,t w ,t 1 x w , j ,i ,t j ,i ) CU * u w, j ,i

w , j ,i (1 honly i ) * x w, j ,i ,t y j ,i ,t REQ j ,i ,t w t x (1 honly i ) * (Technology Rw, Qw(GIT) , j QTw, j * Copyright 2015 Hewlett Packard Enterprise w|, j ,i ,tGlobal Information 1 t lt ( w, j ) xt 1 w, j ,i , * Rw, ) 1 IP for PPO/RMO technology 3 patents granted 15 patent applications in progress HP proprietary algorithm Slide 29 Patent US 8639562 B2: Cost entity matching Inventors: Marcos Cesar Vargas-Magana, Cipriano A. Santos, Carlos

Valencia, Lyle H. Ramshaw, Robert E. Tarjan, Ivan LopezSanchez, Maria Teresa Gonzalez Diaz Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Mathematical Optimization model Min ( T (t 1)) * winprb * RL * gap i i j ,i , t CT * j ,i , t CIa * (inv j ,i ,t a j ,i ,t ) CIx ( Rw, w ,t w , j , i ,t w , j ,i ,t t j ,i ,t xt x 1 CH * h j ,i ,t j ,i ,t ) CU * u w, j ,i

w , j ,i , t j ,i w , j ,i Subject to: 1) (1 honly i ) * x w, j ,i ,t y j ,i ,t REQ j ,i ,t u 5.1) x w , j ,i ,t 1 xw, j ,i ,t (1 honlyi ) * ( Rw, Qw, j QTw, j * 1 j ,i 3) t lt ( w, j ) t 6) 7) a j ,i ,t gap j ,i ,t y j ,i ,t 1

j ,i w 2) w , j ,i QT w, j t xt * Rw, ) w, j ,i , 1 1 t * xt w, j ,i ,t Rw, 1 1 a j ,i ,t inv j ,i ,t 4) inv j ,i ,t inv j ,i ,t 1 h j ,i ,t lh( j ) hpipeline j ,i ,t 8) 5) h

j ,i ,t atmosthire sg j ,i ,t: sg j x w , j ,i ,t T * u w , j ,i t Slide 30 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) h j ,i , t j ,i ,t hglobal RP Assignment Problem Formulation Problem: Lets assume we have four job requirements, two employees, and we can hire only one resource. Nodes in the graph represent either resources or jobs. + Resources can be employees, people to hire, unfilled positions (gap). Arcs in the graph map resources with jobs whenever the resource can fill the job

+ Qualified employee for job + Train and qualified employee for job + New hire for a job + Gap Penalties at arcs represents the cost of filling a job with the linked resource. + Penalty reflects skill matching, resource availability, allocation costs (job level), and Other business objectives Gap for job1 g1 Employee 1 e1 Gap for job2 g2 Employee 2 e2 New Hire h1 Gap for job3 g3 Gap for job4 g4 Penalties

Resources Slide 31 Copyright 2015 Hewlett Packard Enterprise Qualified jb1 job1 jb2 job2 job3 jb4 job4 | Global Information Technology (GIT) (Resource Planning -Bipartite Graph) Hire then Qualified Unfilled Demand jb3 Jobs Train then Qualified

RMO Results and comparisons (2012) Preliminary results Seconds g1 e1 jb1 g2 e2 jb2 h1 g3 g4 Solver Code: 1 Auction Algorithm 2 Flow Assignment Algorithm 3 Hungarian Method 5 - Gurobi Slide 32 O (| E | jb3 jb4 | J | log(| J | C ) Lyle Ramshaw and Robert E. Tarjan. "A weight-scaling algorithm for min-cost imperfect matchings in bipartite graphs",53rd Annual IEEE Symposium on Foundations of Computer Science (FOCS'12), pp. 581--590, 2012 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT)

Suitability Score: Multi-objective optimization To compute the employee-job suitability score we consider the weighted average of various resource matching objectives Skill matching score Capacity Availability Score Allocation (cost) score Weights reflecting the relative importance of the matching objectives can be defined by the user Or we have developed a proprietary methodology that determines the objectives weights by a pairwise comparison reflecting the preference intensity of one objective respect to the other one Suitability Score = (weight)*skill matching score + (weight)*Capacity score + (weight)*Allocation score Slide 33 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) RP Planning Process input Uncertainty Demand & labor supply Demand & labor supply Forecast action RP

Demand & labor supply Forecast Demand & labor supply RP Today - 3 Today +3 Planning Horizon Today output Planning Execution Planning Soft Allocation & Fulfillment Plan Metrics Assignment & Project Schedule Soft Allocation & Fulfillment Plan Metrics Execution Assignment & Project Schedule

Workforce planning cycle represents a connection between execution and planning for labor demand and supply under uncertainty. The planning cycle is fed by the current status of the resources and the expected labor demand for future periods, then the planning tool forecasts resource capacity to satisfy the future demand minimizing gap and maximizing utilization. The managers execute project scheduling based on soft allocation and fulfillment plans planned to anticipate future demand and labor supply. Slide 34 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Questions ?? Back up slides Questions: Strategy and Planning Objectives What do you interpret as planning in your business? A Services Enterprise needs a planning process to address complexity and uncertainty you cannot wait and see, there are lead times to hire/procure and transform. Complexity: There are many dimensions to consider, hence an astronomical number variables courses of action, and there are limited resources. Thousands of employees with thousands of skills and capabilities that needs to be allocated to the right job, at the right time, at the right location, at the right cost In addition, when choosing the best course of action, the Services Enterprise typically have several criteria to consider; where these criteria is aligned with the Enterprise business strategy During the optimization of the selection and scheduling of an IT project portfolio several business objectives are considered: Direct/Indirect Benefit, Customer Satisfaction, Strategic Alignment, Technical Alignment, Employee Satisfaction, etc Slide 37 Finally, several key Copyright 2015 Hewlett Packard Enterprise | Global

Informationbe Technology decision makers might in(GIT)conflict, so having a data driven mechanism helps resolving the conflict in a more objective way Questions: Strategy and Planning Objectives (2) How does your business model drive the principles and characteristics of your planning approach? Due to the complexity of Service Enterprises the planning approach should be driven by the principle of Think globally and act locally Instrumentation: Measure what is measurable, and make measurable what is not. Galileo Galilei Collect and transform data into actionable information Planning processes need to scale: It is imperative to have high levels of automation for the planning approach Benefits of Automation Enables decision making based on data Enables process transparency Increases speed and accuracy of data processing Reduces labor costs Does this vary across your different businesses or assets? Slide 38 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Questions: Planning Processes What planning methodologies do you use? How does this vary by time horizon and decision type? A hierarchical planning process is recommended Business strategy is translated into quantifiable criteria that in turn drives strategic

decisions while considering various BUs constraints and limited resources. A planning horizon of 3 or 5 years with quarterly time periods is recommended Strategic decisions create a framework for tactical planning The planning horizon of 12 or 18 months with monthly time periods is recommended In turn tactical decisions create a framework for operational planning and execution For operational planning, the planning horizon of 3 or 6months with weekly time periods is recommended. For execution, planning horizon of a week with daily (or shift based) time periods is recommended Slide 39 A hierarchical planning process -with feedback loops monitoring execution, enables a homogeneous and Copyright integrated planning system that 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) efficiently/effectively addresses the complexity of the Service Enterprise and the uncertainty about Questions: Planning Processes (2) How do you manage uncertainty and options in your planning? Need a good forecasting process that determines an accurate forecast error, your planning process addresses uncertainty based on forecast error Your planning process should help identifying mechanism to reduce forecast error Is the forecast error large because of lack or inaccurate data? What is the right level of aggregation that reduces forecast error and at the same time you can make decision and implement them? Or the forecast error reflects the random nature of the system? What if scenario analysis can be use to address uncertainty during planning Simulation and Stochastic Programming can be used requires mathematical sophisticated user ..

Create buffer capacity covering a quantile of the forecast probability distribution How much buffer capacity you need that allows to satisfy SLA and at the same time does not hurt resource utilization? What is the cadence of your planning process, and what triggers change? Hierarchical planning drives the cadence of the planning process Slide 40 Rolling planning horizon for scheduled re-planning Significant deviations from the assumptions/input data of the strategic/tactical/operational plans triggers change Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Questions: Planning Processes (3) How does your planning approach respond to disruptive events? Can you dynamically re-plan? Plans are useless, planning is essential. Planning processes and tools should enable re-planning to address complex dynamics and uncertainty associated with your environment How do you achieve integration and alignment (timeframes, value chain, functions, suppliers)? Hierarchical planning with feedback loops from execution How do you incorporate risk management in your planning approach? By considering forecast error How is planning performance and execution performance measured? Comparing cost and benefits derived from your plans with the actual Slide 41 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Questions: Planning Technologies What planning technologies do you currently use and why (data; analysis; simulation; automation)?

Big Data/Data Sciences Data Mining, Machine Learning, Predictive Analytics, Statistics, distributed computing HPSW/Idol, HPSW/Vertica, R Resources Scheduling and Allocation technology Mixed Integer Linear Programming (MILP) MILP solvers: Gurobi, IBM/Cplex Commercial SW tools for Project Portfolio Planning and Resource Management HPSW/PPM Center, Microsoft/Enterprise Project Management, Planisware, Oracle/Primavera Enterprise Project Portfolio Management How do you use technology for communications and alignment? Skype technology is critical for project coordination What new planning technologies are you planning to adopt and why? What do we need to watch out for? Cloud bases planning services Slide 42 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Questions: Planning Organization How is your planning function structured? How do you incorporate diversified business and geographies? How is planning integrated with broader business? How do you build and sustain the required capability? We are re-organizing and this information is confidential What culture are you trying to create, and what levers are you pulling to achieve this? Incentives? Kay Yut is an expert in market mechanism design and incentives South32 Recomendation Which fundamental principles should South32 have for their planning process to maximise value?

Have a clear vision of your business Translate vision into a business strategy with clear quantifiable objectives Optimize the trade-offs of conflicting business objectives while considering budget and resources constraints, and business rules/constraints Consider hierarchical planning (Strategic/Tactical/Operational) with feedback loops Always look for opportunities to reduce forecast which in turn reduces uncertainty Which aspects of planning methodologies, technologies and organisation should South32 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Slide 43 focus on? Labor Nomenclature Standardization LSO Labor Strategy Optimization Model Attrition Forecast Country/SL/ Job Level/ Role/Skill Business Strategy Constraints Attrition Rates FTE actual Inventory -Cost -Budget Constraints -Transformation Rules -Metrics Demand

Signal Forecast Optimization Engine FTE Forecast Split Rates Productivity Metric Learning Curve Forecast -Labor Mix + location + transformation strategies -FTE Plan -Budget Plan -Metrics Execution Process Slide 44 Copyright 2015 Hewlett Packard Enterprise | FTE Forecast Global Information Technology (GIT) PPO The Model Components: How We Represent the Various Aspects of Labor Strategy Optimization Geography (location) Demand Region Resource Country On-Shore, Off-Shore, Off-Shore Travel relationships (between a Demand

Region and a Resource Country) Labor pyramid Job Code structure: Cost Category, Cost Sub-Category, Job Family, Job Level Global Transformation: Promotion, Transition, Transition-Promotion Pyramid bands: % lower and % upper limits Demand Revenue at (Segment, Region, Quarter) level Revenue % that must be delivered using on-shore resources Revenue % range (LB and UB) that is to be delivered by 3P Time dimension Quarters Number of working hours in a quarter varies with country and quarter Country headcount capacity Slide 45 Attrition, Hiring, Transform (Transit, Promote, Transit-Promote), Move sites), WFR(GIT) Copyright 2015(redeployment Hewlett Packard Enterprise between | Global Information Technology 45 Features and Functionality of PPO Prototype Portfolio Shaping Capability: At least (or at most) percentage of projects, FTE, or Dollars allocated to -Investment Area e.g. R&D, Sales Compensation, Cloud Services BU, etc. -IT organization e.g. ES-IT, GF-IT, etc. -Executive Sponsor e.g. Keogh, Lesjak, Nefkens, etc.

-Decision Maker has the ability to select or de-select projects directly -Active projects may be selected automatically Option to reschedule active projects -On hold projects may be de-selected automatically -Planning Projects are selected (or not) based on Optimization Mechanism considered -Decision Maker has the ability to define start time of project (fixed or flexible) Slide 46 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Multiple-Objective Modeling Capability: -Total Project Ranking Maximization -Total Project Score Maximization -Total Project Benefit (direct or indirect) Maximization -Total Project ROI Maximization -Maximization total project score respect to specific Business Objective e.g. Customer Satisfaction, Strategic Alignment, Technical Alignment, Capabilities Roadmap, Employee Satisfaction, Legal / Regulatory / Audit Slide 47 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) # Yp variables # Xpt variables # Zpt variables # Zipto variables

Total # of variables Total # of constraints Gurobi solving time Gurobi solving time no presolve Coin-OR Regular PPO formulation Optimized PPO formulation 108 108 3062 3062 3062 0 3062 0 9307 3183 6461 337 8.53 s 7.97 s 156.1 s 19.9 s 40291.24 s 82.3 s Regular PPO formulation presolve behavior Presolve removed 6354 rows and 7427 columns Presolve time: 0.05s Presolved: 107 rows, 1880 columns, 6825 nonzeros Variable types: 6 continuous, 1874 integer (1874 binary) Slide 48 Copyright 2015 Hewlett Packard Enterprise Optimized PPO formulation presolve behavior Presolve removed 230 rows and 1303 columns Presolve time: 0.04s Presolved: 107 rows, 1880 columns, 6825 nonzeros

Variable types: 6 continuous, 1874 integer (1874 binary) | Global Information Technology (GIT) PPO Stories: other ways PPO technology can help #0 Project portfolio optimization #1 Projects Scheduling #2 There are many ways to get a project done #3 React to change #4 Next generation What-if analysis #5 Top-Down portfolio optimization Slide 49 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) #1 - Projects Scheduling Projects are already selected, PPO advises when to execute them - Optimize different goals Business value delivery preference (as fast as possible / balanced over execution period) Minimize projects completion time - Respects scheduling constraints: Slide 50 Projects dependencies

Group projects by program Respect critical projects deadlines Build your case to meet objectives Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) I can only deliver all projects this year with an extra 800 k$ budget / 10 more #1 - Projects Scheduling (contd) Related scheduling problems: - Single Project scheduling (tasks from a single project) - Program Scheduling (Projects or Summary tasks from a program) Slide 51 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) #2 There are many ways to get a project done One project can be done in different ways: - different teams - Different technical choices (buy or build) - different costs - different delays - even different business value List all the ways to get your projects done, PPO will pick the best ones. Slide 52 Copyright 2015 Hewlett Packard Enterprise

| Global Information Technology (GIT) #3 React to Change What to do when a change is required in a Project Portfolio being executed? Change can take many forms Critical project running late Sudden budget reduction Workforce reduction New project opportunity One must react to change fast (not next year) Slide 53 Cancel projects Put projects on hold Copyright 2015 Hewlett Packard Enterprise Select new project in the portfolio | Global Information Technology (GIT) #4 Next generation What-if analysis From What happens if to What to do if Traditional What-if analysis:

Make a change to current portfolio and see impact on business value and budget & resources consumption Next-gen What-if: Slide 54 Make a change and PPO comes up with an action plan to minimize impact to the project portfolio Compare PPO proposed plan impact with do-nothing option Adjust PPO proposed action plan as needed Helps you prepare mitigation plans for risks scenarios before portfolio execution starts Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) #5 Top-Down Portfolio Optimization Top-Management driven optimization Top Management sets budget & strategy Where money should go Portfolio Mix: at least 40% of investment in innovation projects, no more than 30% in maintenance, Each investment area executes selection Slide 55 Direct visibility to Top management of strategy VS actual selection Portfolio Mix decisions can be enforced during optimization Strategy violations can be annotated with explanations and tracked

Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) PPO User CASES PPO Global: Centralized Planning (input data, key output results, how to implement them?, when? By whom?) PPO by IT organization: Decentralized Planning (input data, key output results, how to implement them? when? By whom?) Project Optimization: consider one project where tasks of project can be implemented in different ways .. Multi-modal project scheduling. This model will optimize the project by selecting the optimal mode for each task given business objectives minimize completion time and maximize project benefit. PPO Hierarchical Planning: Strategic model feeding information to tactical model feeding information to operational model (input data, key output results, how to implement them? when? By whom?) here the strategic model might be a capital budgeting problem considering uncertainty, where budgets by IT organization and time periods are defined; the tactical model is the PPO model as is today. The operational models are determined as follows. Each Project is optimized by solving the multi-modal problem we will know when each selected task should start (using ML we should determine FTE/capabilities requirements for each task) and then the RP model should assign resources to fill task requirements while optimizing several allocation objectives and satisfying resource constraints Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Slide 56 RP Optimizer Service 4. Operational Output 1. Open Positions & Job Requirements for deals & projects Optimal Allocation Plan Hiring Plan RP Optimizer DB 2. Resource Profile

and Assignments 5. KPI Analytics Demand Fulfillment Trend Utilization Trend Qualification Levels 3. Engine Configurations: Matching Preferences, Hiring bounds Optimization as FTE weekly allocation Resource planning output as Work placement guidance Flexible matching score for resource qualification Hiring bounds by geography and workforce type Slide 57 Minimum availability threshold for Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Allocation Resource recommendation plan Resource hiring plan Demand fulfillment and resource utilization KPIs summary Work placement guidance by resource pool structure RP Service extends automatically the resource scope of matching using the primary and secondary pools of resources .

Region BU POSITION Resource Pool (primary pool) India Center Primary Pools Equally preferred Secondary resource pools Testing: Windows Group Testing: Web Group Secondary pools equally preferred Team 3 Team 1 Team 3 Team 1 Team 2 Team 2 Target Delivery Resources available for allocations Slide 58 Copyright 2015 Hewlett Packard Enterprise |

Structure Resource Pools for the Organization Global Information Technology (GIT) I am particularly interested in IT Analytics Vision Big Data and Decision Making + Machine data Convergences of IT Technologies + Business Data From High Performance Sensors, mobile devices, and laptops to next generation computing: + Social Networks data Computing Services The Machine: high density memory and fiber optic computing environments Anywhere + Anytime From next generation computing to Cloud Computing From Cloud Computing to Analytics (Vertica & Autonomy) + Human Data (Structured Data & Unstructured Data) From Analytics to Decision Supports Systems (PPM) Internet of Things (IOT) Big Data Number Crunching Automation Actionable information (Recommendation)

Why DSS ? IT Business & Engineering decisions are complex There might be an astronomical number of alternatives/courses of action Mathematical Optimization There is uncertainty about outcomes from decisions Statistics, Stochastic Modeling, Simulation Several objectives & Decision Makers might be in conflict Slide 59 CopyrightExperimental 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Game Theory, Behavioral Economics, Economics Questions How is your planning function structured? How do you incorporate diversified business and geographies? How is planning integrated with broader business? How do you build and sustain the required capability? What culture are you trying to create, and what levers are you pulling to achieve this? Incentives? Which fundamental principles should South32 have for their planning process to maximise value? Which aspects of planning methodologies, technologies and organisation should South32 focus on? Slide 60 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT) Slide 61 Copyright 2015 Hewlett Packard Enterprise

| Global Information Technology (GIT) Slide 62 Copyright 2015 Hewlett Packard Enterprise | Global Information Technology (GIT)

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