Sales & operations planning in complex business-to-business planning environments

Abstract. Sales & operations planning (S&OP) is a tactical planning process to balance company’s demand and supply. Increasing demand volatility has made S&OP very topical. Business-to-business (B2B) manufacturing with high product variation sets high requirements for S&OP processes and tools. Digitalization has created lots of hype around integrated business planning, which might have raised unjustified benefit expectations for S&OP deployment. In order to deploy S&OP process, it is important to recognize its core purpose and its plausible benefits, to avoid deployment failures caused by the lack of knowledge. This thesis aims to provide S&OP knowledge for complex business to business manufacturing. The qualitative research conducts literature review, and investigates tactical planning processes of three case companies, and current S&OP tool offering of five vendors through semi-structured interviews. From the aim of this thesis, three research questions were conducted: RQ1: What are the desired outcomes of S&OP? RQ2: What aspects of business are expected to be improved by S&OP process and tool deployment according to case companies? RQ3: How do the identified S&OP process models and tools compare with the case companies’ expectations? Following answers to research questions were found: RQ1:S&OP can be defined as a systematic tactical planning process to enhance collaborative target setting, vertical and horizontal integration, visibility creation, and performance management. By combining the different outcomes in different situations, the ultimate desired outcome seems to be the ability to consider all necessary factors in tactical planning. Answer to this research question is derived from the literature review, and it reflects to other research questions. RQ2: Visibility creation, demand forecasting, supply planning, financial planning, scenario planning, internal collaboration, external collaboration, product portfolio management and after sales services were high level requirements derived from the case companies’ specific expectations in the empirical study. RQ3: Identified S&OP process and tools support the major parts of case company expectations, although when having a closer look of some of the case companies’ specific external collaboration, and supply planning aspects, case companies have some unplausible expectations for S&OP tools. Managerial implications: In the early phases of S&OP deployment, companies should mainly focus on designing the process, rather than tool consideration. Only after the suitable process is established, companies should utilize advanced planning tools. The tactical planning tool vendors might emphasize high customizability or high optimization capabilities. These aspects might be trade-offs which companies should be aware. Platform flexibility allows non-standard process designs, and industry specific S&OP practices enables optimization to maximize results by S&OP specific tools. Scientific implications: This study investigates companies operating in B2B business that are utilizing make-to-order production strategy’s variants. Study provides insights of companies planning environments requirements and their desired outcomes of S&OP deployments. Study pointed out the conflicts between S&OP methods and quick response make-to-order strategies in high product variety environments, which indicates that besides evaluating S&OP’s design for planning environments at deployment, evaluation of S&OP methods’ suitability to company specific strategies should be highly considered.Sales & operations planning vaativissa yritykseltä-yritykselle-markkinan valmistusympäristöissä. Tiivistelmä. Sales & operations planning (S&OP) on taktisen suunnittelun prosessi yrityksen kysynnän ja tarjonnan tasapainottamiseksi. Kasvanut kysynnän vaihtelu on tehnyt S&OP:sta erittäin ajankohtaisen. Vaatimukset S&OP prosesseille ja työkaluille ovat korkeat, kun yritys valmistaa useita erilaisia tuotteita yritysmyyntiin. Digitalisaatio on kasvattanut kiinnostusta integroitua liiketoimintasuunnittelua kohtaan, minkä vuoksi S&OP:ta kohtaan on voinut syntyä katteettomia hyötyodotuksia. S&OP-prosessin käyttöönotossa on tärkeää tunnistaa sen päätarkoitus ja mahdolliset hyödyt, jottei implementointi epäonnistuisi tiedonpuutteen vuoksi. Tämän työn tarkoitus on tuoda tietoa S&OP:sta vaativissa yritykseltä-yritykselle-markkinan valmistusympäristöissä. Tässä kvalitatiivisessa tutkimuksessa koostetaan kirjallisuuskatsaus, tutkitaan kolmen case-yrityksen taktista suunnittelutoimintaa, sekä tutkitaan nykyistä S&OP-työkalutarjoamaa viiden järjestelmätoimittajan avulla. Case-yritykset ja järjestelmätoimittajat haastatellaan puolistrukturoiduilla haastatteluilla. Tutkimuksen tueksi on koostettu kolme tutkimuskysymystä: TK1: Mitä ovat S&OP-prosessin odotetut hyödyt? TK2: Mitä osa-alueita case-yritykset odottavat S&OP-prosessin ja työkalujen parantavan? TK3: Kuinka tunnistetut S&OP-mallit ja työkalut tukevat case-yritysten parannusodotuksia? Tutkimuskysymyksiin löydettiin seuraavat vastaukset: TK1: S&OP voidaan määritellä systemaattiseksi taktisen suunnittelun prosessiksi, joka vahvistaa yhteistä tavoitteiden asettamista, vertikaalista ja horisontaalista integraatiota, näkyvyyden luomista ja suorituskyvynjohtamista. Yhdistämällä erilaisia mahdollisia hyötyjä erilaisissa tilanteissa, suurin tavoiteltava hyöty olisi kyky ottaa huomioon kaikki tärkeimmät lopputulokseen vaikuttavat osatekijät taktisessa suunnittelussa. TK2: Näkyvyyden luominen, kysynnän ennustaminen, tuotannon- ja hankinnansuunnittelu, finanssisuunnittelu, skenaariosuunnittelu, sisäinen yhteistyö, ulkoinen yhteistyö, tuoteportfolion hallinta ja jälkimarkkinointi — palvelut ovat tunnistettuja ylätason osa-alueita, joita yritykset odottavat S&OP-prosessin ja työkalujen parantavan. TK3: S&OP prosessit ja työkalut tukevat pääosin yritysten odotuksia, mutta yrityksillä on eräitä spesifisiä ulkoisen yhteistyön ja toimitusketjun suunnittelutoiminnan odotuksia, joita ne eivät tue. Käytännön implikaatiot: S&OP-prosessien käyttöönottovaiheessa yritysten kannattaa ennemmin keskittyä prosessin suunnittelun, kuin työkalujen hankkimiseen. Vasta kun yrityksellä on vakiintunut S&OP-prosessi, yrityksen kannattaa pohtia kehittyneempien suunnittelujärjestelmien hankkimista. Suunnittelutyökalujen järjestelmäntoimittajat saattavat korostaa tuotteidensa räätälöityvyyttä tai optimointikyvykkyyttä. Välttämättä näiden molempien ominaisuuksien tuomia hyötyjä ei voida saavuttaa samassa järjestelmässä. Järjestelmän joustavuus sallii joustavamman rakenteen taktiseen suunnitteluprosessiin, kun taas optimointikyvykkäät järjestelmät nojautuvat toimialan suositeltuihin S&OP-prosessimalleihin. Tieteelliset implikaatiot: Tutkimus esittelee kompleksisissa ympäristöissä toimivien yritysten tarpeita S&OP-prosessille. Tutkimuksessa todettiin ristiriita nopean asiakasvasteen strategian, ja S&OP-metodien välillä, kun yrityksen tuotetarjoama on erittäin suuri, ja kaikki valmistettavat tuotteet ovat asiakasspesifisiä. Tämä viittaisi siihen, että toimivaan S&OP-prosessin rakenteeseen ei vaikuta voimakkaasti vain suunnitteluympäristö, vaan myös yrityksen strategia

Optimisation of vendor-managed inventory systems

Imperial Users onl

Integrated Planning of Industrial Gas Supply Chains

In this work, we propose a Mixed Integer Linear Programming (MILP) model for optimal planning of industrial gas supply chain, which integrates supply contracts, production scheduling, truck and rail-car scheduling, as well as inventory management under the Vendor Managed Inventory (VMI) paradigm. The objective used here is minimisation of the total operating cost consisting of purchasing of raw material, production, and transportation costs by trucks/rail-cars so as to satisfy customer demands over a given time horizon. The key decisions for production sites include production schedule and purchase schedule of raw material, while the distribution decisions involve customer to plant/depot allocation, quantity transported through rail network, truck delivery amounts, and times. In addition, a relaxation approach is proposed to solve the problem efficiently. An industrial case study is evaluated to illustrate the applicability of the integrated optimisation framework

Inventory routing for dynamic waste collection

We consider the problem of collecting waste from sensor equipped underground containers. These sensors enable the use of a dynamic collection policy. The problem, which is known as a reverse inventory routing problem, involves decisions regarding routing and container selection. In more dense networks, the latter becomes more important. To cope with uncertainty in deposit volumes and with fluctuations due to daily and seasonal e ects, we need an anticipatory policy that balances the workload over time. We propose a relatively simple heuristic consisting of several tunable parameters depending on the day of the week. We tune the parameters of this policy using optimal learning techniques combined with simulation. We illustrate our approach using a real life problem instance of a waste collection company, located in The Netherlands, and perform experiments on several other instances. For our case study, we show that costs savings up to 40% are possible by optimizing the parameters

Vendor managed inventory and routing optimisation for free newspaper delivery

Diese Diplomarbeit beschäftigt sich mit der Lösung eines real existierenden Inventory Routing Problems. Für eine Österreichische Gratistageszeitung wird ein Programm zur Minimierung der Distributionskosten erstellt, das abhängig von der Seitenzahl Fahrzeugtouren erstellt. Die Fahrzeuge beliefern ausgehend von einem Depot Zeitungsboxen, die in Straßen- und U-Bahn-Stationen aufgestellt sind mit Zeitungen. Nach einer zeitlichen Anpassung des Bedarfs an das verfügbare Angebot werden mit einfachen Heuristiken Fahrzeugrouten gebildet. Die Ergebnisse werden anhand von drei verschiedenen dicken Zeitungen dargestellt und mit einem Auslieferungsplan, der auch die Basis der Adress- und Bedarfsdaten bildet, verglichen und in Microsoft Excel ausgegeben

On the inventory routing problem with stationary stochastic demand rate

One of the most significant paradigm shifts of present business management is that individual businesses no longer participate as solely independent entities, but rather as supply chains (Lambert and Cooper, 2000). Therefore, the management of multiple relationships across the supply chain such as flow of materials, information, and finances is being referred to as supply chain management (SCM). SCM involves coordinating and integrating these multiple relationships within and among companies, so that it can improve the global performance of the supply chain. In this dissertation, we discuss the issue of integrating the two processes in the supply chain related, respectively, to inventory management and routing policies. The challenging problem of coordinating the inventory management and transportation planning decisions in the same time, is known as the inventory routing problem (IRP). The IRP is one of the challenging optimization problems in logis-tics and supply chain management. It aims at optimally integrating inventory control and vehicle routing operations in a supply network. In general, IRP arises as an underlying optimization problem in situations involving simultaneous optimization of inventory and distribution decisions. Its main goal is to determine an optimal distribution policy, consisting of a set of vehicle routes, delivery quantities and delivery times that minimizes the total inventory holding and transportation costs. This is a typical logistical optimization problem that arises in supply chains implementing a vendor managed inventory (VMI) policy. VMI is an agreement between a supplier and his regular retailers according to which retailers agree to the alternative that the supplier decides the timing and size of the deliveries. This agreement grants the supplier the full authority to manage inventories at his retailers'. This allows the supplier to act proactively and take responsibility for the inventory management of his regular retailers, instead of reacting to the orders placed by these retailers. In practice, implementing policies such as VMI has proven to considerably improve the overall performance of the supply network, see for example Lee and Seungjin (2008), Andersson et al. (2010) and Coelho et al. (2014). This dissertation focuses mainly on the single-warehouse, multiple-retailer (SWMR) system, in which a supplier serves a set of retailers from a single warehouse. In the first situation, we assume that all retailers face a deterministic, constant demand rate and in the second condition, we assume that all retailers consume the product at a stochastic stationary rate. The primary objective is to decide when and how many units to be delivered from the supplier to the warehouse and from the warehouse to retailers so as to minimize total transportation and inventory holding costs over the finite horizon without any shortages

Long‐term effects of short planning horizons for inventory routing problems

This paper presents a detailed study concerning the importance of the planning horizon when solving inventory routing problems (IRPs). We evaluate the quality of decisions obtained by solving a finite-horizon IRP. We also discuss the relevance of explicitly considering profit maximization models rather than the traditional cost minimization variant. As a means to this end, we describe four classes of the IRP corresponding to different types of markets. Two of them lead to nonlinear models, which are linearized. Furthermore, we provide a deterministic simulator to evaluate the long-term effects arising from using planning horizons of varying lengths when solving the IRP. A computational study is performed on cases generated from benchmark data instances. The results confirm that the long-term performance of the IRP decisions is, in part, contingent on the length of the selected planning horizon. They also show that considering profit maximization instead of cost minimization leads to different decisions, generating considerably more revenue and profits, albeit not nearly as much as suggested by individual solutions to static IRPs with short planning horizons. Keywords: profit maximization, path flow, linearization, end effect, simulationpublishedVersio