Regional Data Archiving and Management for Northeast Illinois

This project studies the feasibility and implementation options for establishing a regional data archiving system to help monitor and manage traffic operations and planning for the northeastern Illinois region. It aims to provide a clear guidance to the regional transportation agencies, from both technical and business perspectives, about building such a comprehensive transportation information system. Several implementation alternatives are identified and analyzed. This research is carried out in three phases. In the first phase, existing documents related to ITS deployments in the broader Chicago area are summarized, and a thorough review is conducted of similar systems across the country. Various stakeholders are interviewed to collect information on all data elements that they store, including the format, system, and granularity. Their perception of a data archive system, such as potential benefits and costs, is also surveyed. In the second phase, a conceptual design of the database is developed. This conceptual design includes system architecture, functional modules, user interfaces, and examples of usage. In the last phase, the possible business models for the archive system to sustain itself are reviewed. We estimate initial capital and recurring operational/maintenance costs for the system based on realistic information on the hardware, software, labor, and resource requirements. We also identify possible revenue opportunities. A few implementation options for the archive system are summarized in this report; namely: 1. System hosted by a partnering agency 2. System contracted to a university 3. System contracted to a national laboratory 4. System outsourced to a service provider The costs, advantages and disadvantages for each of these recommended options are also provided.ICT-R27-22published or submitted for publicationis peer reviewe

A Few Implementation Solutions for Business Intelligence

To succeed in the context of a global and dynamic economic environment, the companies must use all the information they have, as efficiently as possible, in order to gain competitive advantages and to consolidate their position on the market. They have to respond quickly to the changes in the business environment and to adapt themselves to the market’s requirements. To achieve these goals, the companies must use modern informatics technologies for data acquiring, storing, accessing and analyzing. These technologies are to be integrated into innovative solutions, such as Business Intelligence systems, which can help managers to better control the business practices and processes, to improve the company’s performance and to conserve it’s competitive advantages.Business Intelligence, competitive advantage, OLAP, data mining, key performance indicators.

K-means clustering combined with principal component analysis for material profiling in automotive supply chains

At a time where available data is rapidly increasing in both volume and variety, descrip- tive Data Mining (DM) can be an important tool to support meaningful decision-making processes in dynamic Supply Chain (SC) contexts. Up until now, however, scarce attention has been given to the application of DM techniques in the field of inventory management. Here, we take advantage of descriptive DM to detect and grasp important patterns among several features that coexist in a real-world automotive electronics SC. Concretely, Principal Component Analysis (PCA) is employed to analyze and understand the interrelations between ten quantitative and dependent variables in a multi-item/multi-supplier environment. Afterwards, the principal component scores are character- ized via a K-means clustering, allowing us to classify the samples into four clusters and to derive di↵erent profiles for the multiple inventory items. This work provides evidence that descriptive DM contributes to find interesting feature-patterns, resulting in the identification of important risk profiles that may e↵ectively leverage inventory management for superior performance.This work has been supported by FCT - Fundacao para a Ciencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. The authors want to extend grateful thanks to the editors and reviewers, whose comments have greatly improved the quality of the paper

Total Cost of Purchasing at Duni AB: Development of a Cost Model

BACKGROUND Through global competition with possibilities for companies to set up production and to secure supply from all over the world the role of purchasing has increased within businesses. In order to achieve business results, a well-working purchasing department plays an important part. To contribute, the purchasing function should not only focus on getting the cheapest price possible, but to take part in shaping strategic directions for their corporation. PROBLEM Duni AB and the business area Meal Service has recognized opportunities in developing their sourcing work by bringing a wider cost focus into their work. By this, they think that they could identify cost saving areas and validate that they make the right decisions based on more aspects than they are doing today. The main objective was therefore to develop a cost model including multiple cost elements besides the purchasing price. PURPOSE The purpose of this study is to create a cost model that Duni Meal Service can use in sourcing and economic life cycle decisions, showing a holistic view of the total cost of purchasing. METHOD Since the objective was to develop and deliver a purchasing cost model to Duni Meal Service a constructive research approach was applied. The focus was on bridging theory and practice and an interview study was held at the principal company, to gain practical knowledge and insight. This together with the theoretical framework, created from our literature studies, worked as a foundation in the analysis and the development of the cost model, as well as for further recommendations given to Duni. THEORY Purchasing Management was investigated, including theory about supplier selection and cross-functional integration. Literature about trade companies was also sought for, since this thesis is limited to traded goods at Duni. In addition, a section of Purchasing Measurements was added since it was mentioned that this might be one of the background issues at Duni. Furthermore, a set of purchasing cost models have been researched and presented. These models are Total Cost of Ownership (TCO), Activity-based Costing (ABC), Landed Cost and Life Cycle Costing (LCC). When the cost models were studied the objective was to find information regarding the following areas: general information, cost elements and cost drivers, applications and success factors. These areas were then summed up and discussed in order to find some patterns in the literature. EMPIRICAL DATA All empirical data collection was made at the principal company, Duni, by interviewing a lot of employees from various functions and at different levels in the business. The focus areas in the interviews were the same as during the literature review: general information, cost elements and cost drivers, applications and success factors. The interviews were mainly held with people from the business area Meal Service or from the Supply Chain department, including the warehouse and logistic functions. ANALYSIS & CONCLUSION Some conclusions were made when comparing the theory with the empirical data in order to find the best possible solution for Duni. It was decided which cost elements and cost drivers to involve in the cost model development and it was also analyzed which the typical application areas of the cost model should be. It was clear that the theory and empirical data were aligned at many areas but the scope of this thesis did not suit all of the studied cost models. THE COST MODEL To fit the needs at Duni Meal Service a Duni specific cost model was created. However, this cost model has almost all the same characteristics as a Landed Cost model and can be seen as a limited version of it. The cost model covers the stages from the point where Duni takes over the ownership of a product from the supplier, via the inbound logistics into the warehouse, and then all parts of the warehousing. Outbound logistics is not involved. The cost model should be used in various sourcing decisions as well as product life cycle decisions such as phase in or phase out decisions. The cost model was created in Excel and along the cost model a user guide and a model manual was developed. Also further guidelines and recommendations were provided in order to successfully implement and maintain the cost model at Duni. Some of the recommendations were that they need to work more cross-functional at Duni in general and that they should align the KPIs to the corporate strategy and take actions accordingly, based on the information provided by the cost model.BAKGRUND På grund av att företag idag har möjlighet att konkurrera globalt genom att flytta produktionen utomlands och att säkra leveranser ifrån alla världens hörn har också inköpsfunktionens roll förändrats. För att nå företagets uppsatta mål är det viktigt att ha en välfungerande inköpsfunktion som jobbar effektivt. Inköpsfunktionen bör inte enbart fokusera på att uppnå det billigaste möjliga inköpspriset, utan också bidra i de strategiska beslut som påverkar hela företaget. PROBLEM Meal Service, som är ett affärsområde inom Duni AB, har identifierat en möjlighet att utveckla deras inköpsarbete, genom att börja arbeta med ett bredare kostnadsfokus. Genom detta, hoppas de kunna identifiera fler kostnadsbesparingsmöjligheter samt ta bättre inköpsbeslut som grundar sig i fler aspekter än vad de använder sig av idag. Därför har huvudsyftet med detta projekt varit att utveckla en kostnadsmodell som även inkluderar kostnadselement utöver inköpspriset. SYFTE Syftet med denna studie är att skapa en kostnadsmodell som Duni Meal Service kan använda I inköpsbeslut samt beslut rörande en produkts ekonomiska livscykel, genom att visa en holistisk bild av den totala kostnaden av ett inköp. METOD Eftersom syftet med denna studie var att utveckla och leverera en kostnadsmodell för inköp hos Duni Meal Service, användes en konstruktiv forskningsmetod. Fokus låg på att länka samman teori och praktik och en intervjustudie gjordes på Duni för att få praktisk förståelse och insikt. Tillsammans med det teoretiska ramverket som skapades genom litteraturstudier, låg detta till grund för analysen och utvecklandet av kostnadsmodellen. Även de framtida rekommendationer som har getts till Duni baserades på den empiriska och teoretiska kunskapen. TEORI Inköpsfunktionens olika delar har undersökts, innefattande teori om leverantörsval och tvärfunktionell integration. Även litteratur gällande handelsföretag eftersöktes eftersom att denna studie är begränsad till inköp av färdigt gods. Det lades också till en sektion om mätsystem för inköp eftersom att detta hade nämnts som ett av de bakomliggande problemen på Duni. Vidare undersöktes och presenterades några kostnadsmodeller för inköpsaktiviteter. Dessa modeller är: Total Cost of Ownership (TCO), Activitybased Costing (ABC), Landed Cost och Life Cycle Costing (LCC). När dessa studerades var målet att hitta information inom de följande områdena: generell information, kostnadselement och kostnadsdrivare, tillämpningar och framgångsfaktorer. Dessa områden summerades sedan upp och diskuterades för att se om det fanns något mönster i litteraturen. EMPIRISK DATA All insamling av empirisk data gjordes hos uppdragsgivaren, Duni, genom att hålla intervjuer med anställda från olika funktioner och nivåer inom företaget. Fokusområdena under intervjuerna var desamma som under litteraturstudien: generell information, kostnadselement och kostnadsdrivare, tillämpningar och framgångsfaktorer. Intervjuerna hölls framförallt med personer inom affärsområdet Meal Service samt inom Supply Chain-avdelningen, inklusive lager- och logistikfunktionen. ANALYS & SLUTSATSER Under analysen av det teoretiska ramverket och den empiriska datan, med syfte att hitta den bästa tänkbara lösningen för Duni, kunde några slutsatser dras. Det bestämdes vilka kostnadselement och kostnadsdrivare som skulle involveras i utvecklandet av kostnadsmodellen och det undersöktes också vilka tillämpningsområden modellen framförallt skulle fungera för. Det var tydligt att teorin och den empiriska datan överensstämde på många områden men ramarna för den här studien lämpade sig inte för alla de studerade kostnadsmodellerna. KOSTNADSMODELLEN För att passa behoven på Duni Meal Service utvecklades en Duni-specifik kostnadsmodell. Dock har denna modell stora likheter med en Landed Cost-modell och kan betraktas som en begränsad version av en sådan. Den utvecklade modellen innehåller stegen ifrån det att Duni tar över ägandeskapet för en produkt, vidare genom den ingående logistiken in i lagret, och slutligen alla delar av lagerhållningen. Utgående logistik till kund ifrån lagret är inte inräknat. Kostnadsmodellen ska användas i olika inköpsbeslut samt i produktlivscykelbeslut såsom infasning och utfasning. Kostnadsmodellen skapades i Excel och tillhörande användarguide och modellmanual utvecklades också. Vidare riktlinjer och rekommendationer gavs också till Duni för att modellen ska kunna implementeras och bibehållas på ett framgångsrikt sätt. Några av rekommendationerna var att de generellt behöver arbeta med tvärfunktionellt på Duni samt att de ska se till att de länkar samman sina KPIer med företagsstrategin och tar beslut därefter, baserat på information som fås ur kostnadsmodellen.Professional purchasing should look beyond the purchase price and include more aspects in order to take strategic purchasing decisions. Aligning purchasing to the corporate strategies will play an important role for achieving business results. This is what the sourcing team within Duni Meal Service had in mind for this project. Instead of only focus on getting the lowest purchase price possible they wanted to broaden their purchasing cost perspective. Therefore the purpose with this thesis was to develop a cost model that Duni Meal Service can use in sourcing and economic life cycle decisions, showing a holistic view of the total cost of purchasing. To fulfill this purpose, a purchasing cost model was created. The cost model will provide the sourcing team within Duni Meal Service with information about the total cost of a purchase. The model will calculate the total cost based on a number of input parameters filled in by the users. By altering these input parameters the user will see how the total cost vary. Thus, the cost model can for example be used to compare two potential suppliers. Given their different offers, the cost model will show how the total cost will differ between them. By comparing the total cost with the sales estimation, the cost model will also give a direct indication on whether the deal is profitable or not. Moreover, the sourcing team within Duni Meal Service will now have a tool in hand to support purchasing decisions. The cost model will also make sure they make these decisions based on a holistic view of the cost situation, being aware of potential trade-offs. The information provided by the model can also be used to take economic life cycle decisions on already existing products in the assortment. The cost model will show if a product is profitable or not and thus, support a decision about phasing out a product from the assortment. Other actions for a non-profitable product could be to increase the sales price or reduce the cost in potential areas. Regardless of what actions Duni Meal Service will take on the outcome, the cost model brings transparency. Together with the holistic view of the true cost situation the cost model will hopefully help to increase the cross-functionality at Duni as well. The users of the cost model will gain better understanding for how their decisions affect other parts of the supply chain, and thereby other departments at Duni. That awareness will probably improve the collaboration and that will in turn increase the employees’ knowledge for the holistic picture. With gained knowledge and better communication the cross-functional work will be improved. The conclusion is that the cost model will help to increase the cross-functional work, but that will in turn have a positive impact on the outcome of the cost model. This virtuous circle will benefit the employees to make the most suitable decisions for the whole organization. In order to develop a purchasing cost model suitable for the needs at Duni, empirical data was gathered through an interview study. The interviews were held with several employees within different departments at Duni. By spreading over a wide range of information sources, the aim was to get a holistic perspective on the situation and issues of today. Theoretical knowledge was also gained by searching through existing literature within the fields of purchasing management, contextual aspects and measuring of purchasing performance. Literature regarding cost management, and in particular purchasing cost models, was also examined. Four, already existing, purchasing cost models were studied and included in the theoretical framework. These were Total Cost of Ownership, Activity-based Costing, Landed Cost and Life-cycle Costing. The theoretical framework lied as a foundation for the continued study but also for the analysis of the empirical findings. When analyzing the findings at Duni with the theory, we found out that the cost model developed specifically for Duni also could be seen as a limited landed cost model. In order to validate the cost model four separate workshops were held with users and other stakeholders, where it was tested and evaluated. Furthermore a sensitivity analysis was conducted, making sure that the cost model was built correctly

Time series forecast and anomaly detection at scale applied to business metrics in an ERP environment

In the business world, dashboards are a widely used analytical mechanism that helps in the decision-making process by displaying insights, key performance indicators, and business metrics. The information provided by this type of mechanism is strongly aggregated, to obtain a high level of summarization and consequently make reading easier. However, the necessary summarization causes “blind spots” to appear by hiding important information such as a sharp drop in revenue from a specific customer, seller, or product/ service. These “blind spots” make it difficult to detect potential business problems and opportunities, which depend on lengthy and thorough additional exploration. Also, the digital transformation process has resulted in a substantial increase in the number of metrics for all systems supporting the business that need to be tracked. Thus, it will be possible to anticipate actions based on the prediction of future behavior, as well as to detect any isolated or successive deviation from the expected behavior. With this dissertation, we intend to promote the acquisition of knowledge from business data through the application of Machine Learning techniques. Based on the Data-Driven Decision-Making process, we intend to propose integration into an ERP application of a mechanism to predict time-series behavior, as well as detecting and measuring possible anomalies. For dealing with a wide diversity of time series, we propose a meta-learning forecasting method that uses a classifier to identify the best forecasting method for each time series. We also propose a new intelligent metric that allows us to sort time series by the accumulated anomaly. The knowledge generated will complement the information provided by the analytical mechanisms typically present in an ERP application (including dashboards). In this way, we intend to contribute to the maximization of profits and reduction of the possibility of error or fraud, as well as waste and consequently mitigate uncertainty and reduce operational risk. Our solution should promote the need to use Machine Learning in Small and Medium Enterprises, and consequently, future implementation of AI-Driven Decision Making. AI-Driven Decision-Making purposes an assertive and automated reaction to problems or opportunities encountered, but whose study is outside the scope of this dissertation.No meio empresarial, “dashboards” são mecanismos analíticos amplamente utilizados que ajudam no processo de tomada de decisão ao exibirem insights, indicadores de desempenho (KPIs) e métricas de negócio. A informação disponibilizada por este tipo de mecanismo é fortemente agregada, de forma a obter-se um elevado nível de sumarização e consequentemente facilitar a sua consulta. No entanto, a necessária sumarização provoca o surgimento de “blind spots”, ao ocultar informação importante como, por exemplo, uma quebra acentuada de receita de um cliente, ou de um vendedor, ou de um produto/serviço específico. Estes “blind spots” dificultam a deteção de eventuais problemas e oportunidades de negócio, que ficam dependentes de uma exploração adicional demorada e minuciosa. Adicionalmente, o processo de transformação digital tem como consequência um aumento substancial do número de métricas referentes a todos os sistemas que suportam o negócio, que importa acompanhar. Desta forma, será possível antecipar ações baseadas na previsão de um comportamento futuro, bem como detetar um eventual desvio isolado ou sucessivo face ao seu comportamento espectável. Como objetivo desta dissertação pretendemos promover a obtenção de conhecimento a partir de dados de negócio, através da aplicação de técnicas de Aprendizagem Automática (“Machine Learning”). Tendo por base o processo de tomada de decisão a partir de dados (“Data-Driven Decision-Making”) pretende-se propor a integração numa aplicação ERP de um mecanismo que permita prever o comportamento futuro de séries temporais que contêm dados de negócio, bem como detetar e medir possíveis anomalias de forma a poderem ser gerados alertas. Para lidar com uma ampla diversidade de séries temporais, propomos um método de previsão de meta-aprendizagem que utiliza um classificador para identificar o melhor método de previsão para cada série temporal, e uma nova métrica inteligente que permite ordenar séries temporais pela anomalia acumulada. O conhecimento gerado irá complementar a informação disponibilizada pelos mecanismos analíticos tipicamente existente numa aplicação ERP (incluindo “dashboards”). Desta forma pretendemos contribuir para uma maximização dos proveitos e redução da possibilidade de erro ou fraude, bem como do desperdício e consequentemente mitigar a incerteza e diminuir o risco operacional. Pretende-se igualmente que a solução promova a utilização de Aprendizagem Automática em Pequenas e Médias Empresas, e consequentemente uma futura implementação de tomada de decisões a partir de Inteligência Artificial (“AI-Driven Decision Making”), onde uma reação assertiva e automatizada é despoletada, face a problemas ou oportunidades encontradas, mas cujo estudo fica fora do âmbito do presente trabalho

Research on the Status Quo and Countermeasures of HR Company's Inventory Management

HR is a manufacturer of electromechanical products in China. Its manufacturing features are muti-variety for orders, mixed batch production mode with small batches and large batches. In recent years, with the development of enterprises, the increase of product varieties and the increase of production tasks, the production process has also encountered new problems of excessive management cost and relatively low production control. The profit rate of enterprises has also declined. The trend of capital cost occupancy has become aware of the importance of inventory management, and it is eager to improve operational management through inventory management. HR company's long-term inventory management is empirical and extensive management, lacking the guidance of scientific theory. Based on the study of inventory management theory and method, this paper uses the theory of constraints (TOC) to analyze the problems and causes in inventory management and find out the improvement. countermeasure. According to the actua situation of the enterprise, using MRP principle and Excel information processing method to build order management, raw material, work-in-process, finished product and production planning data correlative processing platform in order to improve the accuracy of production control. Implement ABC classification for different categories of inventory and select appropriate control strategies. This paper will propose corresponding countermeasures from the establishment of the enterprise database, the construction of a data processing platform, production planning, and scientific inventory management. The actual problems and root causes of inventory summarized in the research process are representative in SMEs. The proposed inventory management strategy is practical, operable and referrible from the perspective of the enterprise and from the technica point of view. It is hoped that this paper can improve the inventory management level of HR companies and can play a reference role for small and medium-sized manufacturing enterprise with the same characteristics. During the completion of the thesis, there is sufficient communication carried out with the company. The important strategy has been adopted by the enterprise