Challenge Solution Outcome KAZAKHSTAN TEMIR ZHOLY

SAP® Innovation Awards 2020 Entry Pitch Deck

Innovative Business Planning & Traffic Routing for Kazakhstan Railways

KAZAKHSTAN TEMIR ZHOLY Company Information

Headquarters Nur-Sultan, Kazakhstan Industry Railroad Web site KAZAKHSTAN TEMIR ZHOLY

KAZAKHSTAN TEMIR ZHOLY [KTZ] is the national railway company for the worlds’ 9th largest country, Kazakhstan. Kazakhstan is situated in the heart of Eurasia, along the ancient Silk Road. The complex geography and harsh weather conditions create serious challenges in operating cargo and passenger transportation, yet railroad logistics remain a crucial sector for Kazakhstan’s economy. Our job is to maintain, operate, develop railway transportation, and move cargo across the 21,000km (13,000mi) of railway track we control within Kazakhstan and with our country-partners in Asia and Europe. With 130,000 employees, we are Kazakhstan’s largest employer. We operate a rolling stock of 1,700 locomotives. Our wagon fleet of 137,000+ carries over 400 million tons/year. We have a turnover of 300 million ton-km.

Challenge • Technology incapable of handling huge volumes of cargo & freight data made it difficult for KTZ to make timely investment & The Integrated Planning System managerial decisions, fully capture market potential, or have a reliable tool for aligning shareholder expectations & KTZ brings KTZ’s planning to a whole resources. new level with the introduction of • Inefficient manual processes, required months to complete & involved dozens of cross-functional departments. innovative SAP technologies in the field of big data, predictive analytics, Solution and machine learning. • Implementation of an Integrated Planning System on SAP HANA created a single platform capable of processing huge volumes of cargo & freight data. SAP HANA allows KTZ to quickly process large amounts of data and • The Integrated Planning System helped to provide ‘’what-if’’ scenario comparisons, manage KPI’s using the bottom up approach, perform complex calculations in manage revenue forecasting, and an optimization model for wagon traffic routing. real-time – something that seemed Outcome impossible until recently. • Transparent & efficient planning process integrated machine learning with human expertise for rapid forecasted wagon traffic The new System also serves as a costing, tarification, map-based visualization, and traffic routing optimization. powerful tool for making managerial • The Integrated Planning System uses historical and forecast data to perform analytics at deeper level of granularity. decisions, timely responses to ongoing changes and factors affecting KTZ’s activities and the industry overall. Faster annual and mid- Traffic flows have term planning, optimizing Transparency the potential for human resources, and throughout all Dair Kusherov optimization with allowing for prompt end-to-end Chief Financial Officer, KTZ 14% variable cost savings 40x 100% reactions to market planning phases. worth ~$5 million. changes.

SAP Innovative Business Solutions

SAP Innovative Business Solutions is integral in optimizing KTZ’s traffic routing. SAP IBSO experts collaborate with us and our partners – from discovery to delivery – in order to develop tailored, high-value solutions, using an agile, design-driven approach. Using SAP HANA 2.0 FULL USE as a foundation, the SAP IBSO team is developing and delivering the IPS modules necessary for integration into new KTZ business processes.

“We are working with KTZ using an agile project methodology to maximize business values for our customers in short time. Innovative usage of data becomes even more important in times of ever increasing speed and growing complexity of business. We provide a state of the art platform to enable KTZ for the future of railroad cargo logistics planning for the 9th largest country in the world. I’m proud to be a part of this story together with our team of SAP experts.”

Dr. Gernot Schreider Delivery Head CIS, SAP Innovative Business Solutions

Oliver Wyman Oliver Wyman [OW] is a global leader in business consulting & operations, with unmatched expertise in logistical industries. OW drafted a new approach for integrated planning, where they combined demand forecasting with historical traffic patterns in order to optimize KTZ’s wagon traffic forecasting & routing. This new approach is currently undergoing user-testing. The OW experts are currently working on prototyping algorithms for traffic routing optimization, which bridges the gap between wagon traffic forecasting, capacity limitations, input for investment decisions, and financial metric calculations.

“Adoption of modern traffic-based planning instruments will empower KTZ in efficient decision-making. Transparency of expected performance levels, granularity of planned KPI’s, and common methodologies and tools will drive material improvements of operational and financial efficiency.”

Rodney Case Partner & Head of Oliver Wyman Rail Practice

Challenges for an Integrated Planning System:

• Complex and long planning cycle lasting ~260 days due to manual work processes that involved dozens of cross- functional departments within KTZ. • Lack of transparency during information flow between planning departments leads to loss of analytical depth and inability to fully manage root-cause analyses. • A large margin of error in planning which does not allow for proper resource allocation and financial liquidity. IE – KTZ was unable to afford flexibility in investing funds to value-generating projects. This prevented KTZ from further developing opportunities present across the 21,000km (13,000mi) long railways which connect strategic markets in Asia and Europe.

Objectives for an Integrated Planning System: The main goal of KTZ’s Integrated Planning System is to enhance planning processes at all stages, from accurately determining demand and production planning, to setting realistic financial and strategic indicators that affect companywide performance: • Increase reliability, transparency, and robustness of midterm planning and forecasting processes. • Utilize machine learning and cutting-edge technologies like machine learning and in-memory computation to speed-up midterm planning processes. • Make real-time operational and investment decisions based on “what-if” scenario-analyses provided by monthly granulated demand forecasts, routing models, and financial statements generated by the Integrated Planning System.

The Integrated Planning System aims to enhance KTZ’s medium-term planning processes and has been implemented across KTZ’s cargo transportation (85% of revenues), wagon business operations, and railway network infrastructure.

The following key principles were implemented within the design of the Integrated Planning System: • Close integration between KTZ’s financial and economic models with railway traffic operational metrics, in order to have end-to-end KPI connectivity. • Implementation of machine learning algorithms and predictive analytics techniques for creating automated forecasts. • Heuristic approaches based on massive data processing for wagon traffic routing optimization. • Utilizing high-performance IT platforms with in-memory computing in order to execute “what-if” scenario analyses in real-time.

Live within KTZ: • Demand forecasting modules to predict cargo freight transportation volumes and turnover at 5 years horizon monthly. The forecast build is online. It uses historical waybill data combined with a macro-economic indicator database (300+ indicators) which explore TOP N indicators that influence the forecasts. • Loaded and empty wagon traffic forecasts resulting from cargo volume forecast disaggregation into wagon flows. This allows the forecasting of traffic volumes on a deeper level of origin-destination stations, countries, types of wagons, and other parameters. • Revenue forecast module based on forecasted traffic data. • Traffic routing optimization based on heuristic algorithms, which allows to minimize variable costs of cargo transportation and find possible bottlenecks within the railway network. • Big data slice’n’dice deep analysis using SAP Business Objects / Business Intelligence solution.

Our 2020 plan is to launch new budgeting systems, SAP Business Planning and Consolidation (BPC), which allow the aggregation of forecasted revenue, variable and regular costs, as well as the build of budget planning solutions that utilize the integration of KTZ KPI management and investment strategies.

Business or Social IT Human Empowerment

• Taking into account economic • Heuristic algorithms for optimizing • Employee empowerment through aspects during wagon traffic routing wagon traffic routes. technological qualifications optimization (fuel and maintenance development. • Machine learning algorithms cost, human resources etc.). integrated and then enhanced with • Transition from mostly manual labor • KTZ and Kazakhstan railroad human expertise. in data manipulation to a high tech logistics strategy can now be approach leads to time for powerful • Data science technologies able to realized through effective mid-term capture and analyze all of industry insight that develops planning. Kazkhastan’s rail logistics big data. machine learning. • Ability to rapidly model the business • Reduced time of planning from • Predictive algorithms for accurate situations assisting in timely demand forecasting that minimize months to days. This releases time decision-making use of human intervention and and empowers employees for more intelligent work related to planning • 100% transparency throughout the provide easy access to extensive end-to-end planning phases. historical data. on every level. • Effective tool for financial • A new profit generating approach to expectations management for route modeling is achieved through wagon fleet, network capacity, and optimization algorithms embedded tariff re-evaluation. into the platform. • Evaluation of potential demand for cargo transportation in the next 5 years horizon.

SAP HANA 2.0 XSA

Users SAP BPC FLP, SAPUI5 SAP HANA OFL HANA XSA User interface (Optimization App Containers Function Library) (NodeJS) Administrators

SAP Smart Data Integration SAP HANA 2.0 DB User SAP HANA APL containers Account (Automated Predictive Library) KTZ Systems, Authentication CEIC, Rail Tariff SAP BO

Shareholder Demand Loaded wagon Traffic routing Budget Expectations forecasting traffic forecasting optimization planning

Revenue estimation

Empty wagon Resource traffic balancing investment planning

Deployment status Live

Date 31.08.2019 Number of users 50

SAP technologies used: SAP product Deployment status Contribution to project

SAP HANA 2.0 Extended Application SAP HANA is the development platform and database for our system. Services (XSA) + Application Live Demand forecasting module created based on SAP HANA APL. 1 Programming Library (APL) and Empty wagon traffic forecasting was implemented using OFL. Optimization Function Library (OFL)

2 SAP HANA Smart Data Integration Live Integration with external data sources, ETL.

SAP Business Objects Business Live Analytics on top of hystorical, actual, and forecasting data. 3 Intelligence (BI) Suite

SAP Business Planning and PoC Financial economical model and KPI management. 4 Consolidation (BPC) If you have used one of the services or support offerings from SAP Digital Business Services during the implementation or deployment phase, please select with X one or more of the following offerings:

X SAP MaxAttention™ SAP ActiveAttention™ SAP Advanced Deployment SAP Value Assurance SAP Model Company Others: SAP Innovation Services X SAP Innovative Business Solutions

The following advanced technologies were part of the project.

Technology or use case Yes or No Contribution to project

1 3D printing No

2 Blockchain No

3 Internet of Things (IoT) No

Forecasting of cargo volumes implemented via machine learning 4 Machine learning or AI Yes algorthms. Selects the best method of forecasting, minimizing errors.

5 Conversational AI No

6 Robotic process automation No

7 Data anonymization No

8 Augmented analytics No

The Integrated Planning System results are currently exceeding all KTZ expectations, and setting new standards for planning. We have decided to continue expanding and developing the project futher into shorter/deeper horizons: from mid-term (monthly-yearly) to operational (decade- monthly) planning.

The Integrated Planning System scope currently covers KTZ’s cargo operations within a monthly- yearly horizon. The proposed expansion will include the whole infrastructure sector, with operational maintenance planning and wagon fleet operations, to properly manage and utilize company assets.

Future Integrated Planning System development may include passenger transportation sections, which would form a full planning circle for KTZ.

Supporting Video