Hyperion Planning and Consolidation solution overview v2
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“There were fewer adjustments at the reporting unit level than we had expected and they tended to be relatively minor. They mainly related to acquisitions, intangibles, leases, and joint ventures. Adjustments at headquarters were more significant and more complex and related to pensions, share option expenses, deferred tax, and financial instruments. Given this relatively straightforward framework, the group was able to quickly establish a unified chart of accounts in Hyperion Financial Management covering UK GAAP, U.S. GAAP, and IFRS. It was then a simple matter to post the adjustments against these accounts as required.” “We had total visibility of the process and could instantly see the effect of changes posted anywhere in the group. Also, if we needed to maintain the central model—for example, to collect more data—we could effect the change, and it was immediately available throughout the group. We could not have managed this so easily using our old business consolidation system.”
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邵小卫 商务智能售前总监 海波龙中国区
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Integrated planning and control for convex-bodied nonholonomic systems using local feedback
Integrated Planning and Control for Convex-bodied Nonholonomic systems using Local Feedback Control Policies David C.Conner,Alfred A.Rizzi,and Howie ChosetCMU-RI-TR-06-34August2006Robotics InstituteCarnegie Mellon UniversityPittsburgh,Pennsylvania15213c2006Carnegie Mellon UniversityAbstractWe present a method for defining a hybrid control system capable of simultaneously addressing the global navigation and control problem for a convex-bodied wheeled mobile robot navigating amongst obsta-cles.The method uses parameterized continuous local feedback control policies that ensure safe operationover local regions of the free configuration space;each local policy is designed to respect nonholonomicconstraints,bounds on velocities(inputs),and obstacles in the environment.The hybrid control systemmakes use of a collection of these local control policies in concert with discrete planning tools in order toplan,and replan in the face of changing conditions,while preserving the safety and convergence guaran-tees of the underlying control policies.In this paper,we provide details of the system models and policydefinitions used to validate the approach in simulation and experiment with a convex-bodied wheeled mo-bile robot.This work is one of thefirst that combines formal planning with continuous feedback controlguarantees for systems subject to nonholonomic constraints,input bounds,and non-trivial body shape.c2006Carnegie Mellon iContents1Introduction1 2Related Work32.1Motion Planning and Control with Nonholonomic Constraints (3)2.2Sequential Composition (4)3General Framework73.1System Models (7)3.2Generic Policy Requirements (8)3.2.1Simple Inclusion Tests (8)3.2.2Contained in Free Space (9)3.2.3Conditionally Positive Invariant (10)3.2.4Finite Time Convergence (10)3.3Discrete Planning in Space of Policies (11)3.3.1Extensions to Prepares Definition (11)3.3.2Planning in Policy Space (12)4Local Policy Definitions154.1Inclusion Test (18)4.2Free Configuration Space Test (18)4.3Conditional Invariance Test (19)4.4Vector Field Definition and Convergence Test (20)5Policy Deployment Technique23 6Current Results276.1Robot System and Implementation (27)6.2Navigation Experiments (29)6.3Task Level Planning Simulations (30)7Conclusion33 A Free Space Testing37 References41c2006Carnegie Mellon iii1IntroductionThe problem of simultaneously planning and controlling the motion of a convex-bodied wheeled mobile robot in a cluttered planar environment is challenging because of the relationships among control,nonholo-nomic constraints,and obstacle avoidance.The objective is to move the robot through its environment such that it arrives at a designated goal set without coming into contact with any obstacle,while respecting the nonholonomic constraints and velocity(input)bounds inherent in the system.Conventional approaches addressing this problem typically decouple navigation and control[12,31,33]. First,a plannerfinds a path,and then a feedback control strategy attempts to follow that path.Often the methods assume a point or circular robot body;other non-trivial robot body shapes complicate the problem offinding a safe path,as the path must be planned in the free configuration space of the robot.This leaves the challenging problem of designing a control law that converges to the one-dimensional path,while remaining safe with respect to obstacles.We address the coupled navigation and control problem by generating a vectorfield along which the robot can“flow.”Unfortunately,determining a global vectorfield that satisfies all of these objectives for constrained systems can be quite difficult.Our approach,inspired by the idea of sequential composition[11], uses a collection of local feedback control policies coupled with a switching strategy to generate the vector fiposing these relatively simple policies induces a piecewise continuous vectorfield over the union of the policy domains.A policy is specified by a configuration dependent vectorfield defined over a local region of the robot’s free configuration space,termed a cell.From this vectorfield and knowledge of the current robot state,the control inputs are determined such that the closed-loop dynamicsflows to the specified policy goal set within the cell.Figure1shows four paths induced by invoking the local policies for four different initial conditions in the robot experiments,as will be discussed in Section6.Figure1:Experimental results of four robot runs using the proposed hybrid control framework.An explicit desired path is never calculated,the path is induced by sequentially chaining local feedback control policies together;the policy ordering is determined by a discrete planner.The induced path preserves the local guarantees of the local polices,and is thus free of collision while respecting the system constraints.c2006Carnegie Mellon1A discrete transition relation represented by a graph is induced by the transition between the domain of one policy to the domain of a second policy containing the policy goal set of thefirst.On-line planning,and re-planning under changing conditions,becomes more tractable on the graph,allowing us to bring numerous discrete planning tools to bear on this essentially continuous problem.By sequencing the local policies according to the ordering determined by a discrete planner,the closed loop dynamics induce the discrete transitions desired by the discrete plan.The overall hybrid(switched)control policy responds to system perturbations without the need for re-planning.In the face of changing environmental conditions,the discrete graph allows for fast online re-planning,while continuing to respect the system constraints.By coupling planning and control in this way,the hybrid control system plans in the discrete space of control policies;thus,the approach represents a departure from conventional techniques.A“thin”path or trajectory is never explicitly planned;instead,the trajectory induced by the closed-loop dynamicsflows along the vectorfield defined by the active policy,which is chosen according to an ordering determined by a discrete planner.A plan over the discrete graph associated with the collection of policies corresponds to a“thick”set of configurations within the domains of the associated local policies.This approach offers guaranteed convergence over the union of the local policy domains.For the method to be complete,the entire free configuration space must be covered by policy domains(cells).This is a difficult problem due to the multiple constraints on the robot dynamics.Herein,the focus is on deploying a “rich enough”collection of policies that enables the navigation problem to be addressed over the bulk of the free configuration space.This paper describes the basic requirements that any local policy must satisfy to be deployed in this framework;each local policy must be provably safe with respect to obstacles and guarantee convergence to a specified policy goal set,while obeying the system constraints within its local domain.We develop a set of generic policies that meet these requirements,and instantiate these generic policies in the robot’s free configuration space.The underlying equations are detailed,and examples are provided.Finally,a concrete demonstration of controlling a real mobile robot using a collection of local policies is described.2c2006Carnegie Mellon2Related WorkThe approach advocated in this paper maintains the coupling between planning and control,unlike con-ventional approaches that decouple the problem into a path planning problem and a path-following control problem.This section presents a brief overview of conventional approaches,and concludes with a discussion of the sequential composition approach that motivates this work.2.1Motion Planning and Control with Nonholonomic ConstraintsThe control of systems with nonholonomic differential constraints is more complex than control of purely holonomic1systems.This section contains an overview of techniques used to plan paths and trajectories for nonholonomic systems,and address four basic control problems for nonholonomic systems–stabilization, path-following,trajectory-tracking,and point-to-point steering[18,30,43].The discussions give insight into the difficulties associated with nonholonomic motion planning and control.For a more thorough discussion and reference list,refer to[30,32,33].To recognize the complexity introduced by nonholonomic constraints,consider the“simple”problem of stabilizing a system about a given equilibrium point.Brockett’s theorem provides necessary conditions for the existence of a smooth,time-invariant feedback control law that stabilizes the system about the given point[10].It is well known that many nonholonomic systems,although small-time locally controllable,fail Brockett’s test[30,43].This precludes the use of conventional feedback control based on potential functions. Several classes of stabilizing feedback control policies have been developed:discontinuous time invariant, time varying,and hybrid control policies[30].Given the complexity of this control task,it is no surprise that the coupled navigation and control task is more complex than for holonomic systems.Many approaches addressing the coupled navigation and control problem for nonholonomic systems de-compose the problem into a motion planning problem,followed by a control problem.A common planning approach is to pretend the system is holonomic and hope for the best.In the holonomic case,the path or tra-jectory can be planned using any of a number of methods[12,35].Grid-based search algorithms are popular in path planning,as are roadmap methods such as V oronoi diagrams.Potential function methods,while not necessarily complete,are also widely used in path/trajectory planning.Given a path through the environment,a path-following algorithm is then used to converge to the desired path.There are two basic formulations to path-following.In thefirst,a designated point on the robot traces a given path in the workspace,without concern for orientation[15].This may fail in cluttered environments as the designated point may exactly follow a safe path,yet still allow the system to collide with an obstacle at another point on the robot body.The second formulation attempts to track position and orientation of a path in the free configuration space[17].If the environment is not overly cluttered,so that deviations are not catastrophic,path following may work well.In fact,if a system is small-time locally controllable,any continuous path can be approximated arbitrarily well[34].Unfortunately,the methods used to control the system along arbitrary paths often lead to highly oscillatory motions that require great control effort.If the path does not respect the system constraints, the resulting motions may require an inordinate number of reversals to follow the desired path.One approach to address this problem is to plan a path without regard to nonholonomic constraints,and perturb the path to respect nonholonomic constraints[51].Techniques that consider the nonholonomic constraints during planning typically use only a discrete set of feasible motions.The shortest feasible path(SFP)metric is used to plan paths that approximate a holonomic path using afinite number of motions[42].The motions are selected by choosing the shortest feasible path to a point on the holonomic path intersecting the largest ball defined by the SFP metric[56].Dynamic programming methods determine an optimal path for a discrete set of controls(e.g.hard left,soft left,straight,soft right,hard right)[3,21,36].Probabilistic roadmaps(PRM)and rapidly-exploring random trees(RRT)are other discrete approaches to determining feasible paths for nonholonomically constrained systems[37,54].With the exception of dynamic programming,these discrete methods are not feedback based,and require replanning if the system deviates from the desired path.Even if the planned path respects the nonholonomic constraints,the path must be followed by the robot. The presence of nonholonomic constraints renders path-following a non-linear controls problem.Control laws based on a Lyapunov analysis[17]or feedback linearization[18,50]are common.Most path-following algorithms assume continuous motion,with a non-stationary path defined for all time.This(temporarily) avoids Brockett’s problem with stabilization to a point[15,17].The path-following control policy asymptot-ically brings the error between the desired path and the actual path to zero.Typically,the control policy is constructed for a specific vehicle and class of paths[2,17,15,55].The path-following control laws are unaware of environmental obstacles;therefore,for a nonzero initial error or perturbation during motion,the system may collide with an obstacle.Path-following may be coupled with local obstacle avoidance,but this may invalidate the convergence guarantees.Thus,if the errors are large enough,the paths must be replanned,starting from the current location.In addition to path-planning,trajectories that specify when the system arrives at points along the path may be planned[17,50].Trajectory-tracking problems can be problematic if the system is subject to a constraint that delays the tracking[17].In this case,the accumulated error may make the system unstable or require unreasonably high inputs.Another possible problem is that trajectory-tracking controls may switch directions for certain initial conditions[50].Unless the time matching along the trajectory is crucial,path-following is often a better formulation[17,50].In related work,several methods–including sinusoidal inputs,piecewise constant inputs,optimal control, and differentiallyflat inputs–solve the point-to-point steering problem between two positions using open loop controls[34,43].These methods are sometimes incorporated into the discrete planning systems.Each of these methods is an open loop control method that does not respect obstacles.Collision detection must be performed after the path is found to determine feasibility in a cluttered environment[27].These point-to-point steering methods are strictly open loop,and not suitable for feedback control.The inevitable errors necessitate repeated applications to induce convergence to the goal point.There have been a few attempts to address the coupled navigation and control problem for nonholonomic systems.A method based on potentialfields uses resistive networks to approximate the nonholonomic con-straints[14].This approach requires a discretization of the configuration space,and is therefore subject to numerical difficulties when calculating derivatives necessary for feedback control.Other approaches define integral sub-manifolds in configuration space that contain the goal[25,29,41].On the sub-manifold,the nonholonomic constraints are integrable,and the control naturally respects the constraints.The approaches drive the system to the sub-manifold,and then along the sub-manifold to the goal.While these methods are suitable for feedback control implementations,determination of a suitable manifold is sometimes difficult. For systems where the stable manifold is not given in closed form,an iterative process is used to approximate the manifold.The approaches also involve designing several functions that require insight into the specific problem and system constraints.2.2Sequential CompositionThe research presented in this paper uses the technique of sequential composition,which enables the con-struction of switched control policies with guaranteed behavior and provable convergence properties[11].The original form of sequential composition uses state regulating feedback control policies,whose do-mains of attraction partition the state space into cells[11].The control policy can be thought of as a funnel, as shown in Figure2,where the vertical represents the value of a Lyapunov function,and the domain is the 4c2006Carnegie MellonFigure2:An idealized Lyapunov function and its associated domain of attraction rep-resented by its shadow on the state space. The goal point is shown as a large dot within thedomain.Figure3:Composition of control policies leads to an enlarged domain of attraction.Note that the active policy switches to the highest priority policy as soon as the state enters its domain.“shadow”cast by the funnel on the state space below[11].The domain is the safe domain of attraction, which is the largest positive invariant region that does not intersect an obstacleThe basic idea behind sequential composition is to compose multiple control policies in a way that enlarges the overall domain of attraction,while preserving the underlying convergence guarantees.The approach specifies the goal of one policy to lie within the domain of another policy.By properly prioritizing the policies,and switching to a higher priority policy once the state enters the domain of the higher priority policy,it is possible to construct a switching control policy with a larger domain of attraction than any single policy[11].The domain of attraction of the switched policy is equal to the union of the domains of the component policies,as shown in Figure3.By composing policies with limited domains,constraints in the state space can be respected while building an almost globally convergent control policy.In this way,the free state space may be covered by incrementally covering an additional region of the free state space.The policy composition is based on a formal notion of prepares[11].For a given control policy,, denote the domain of the policy and the goal.Given two control policies,is said to prepare,denoted,if.Let afinite collection of instantiated control policies, ,defined over the free state space of a given system be given,and assume at least one policy stabilizes the overall goal.The prepares relationship between any two policies in the collection induces a directed graph,,over the collection of instantiated control policies.In general the policy graph is cyclic;however,an acyclic graph,,may be generated over the collection of policies by searching the original graph breadthfirst,beginning at the node corresponding to the policy that stabilizes the overall goal, and adding only those links and nodes that connect back to previously visited nodes.The acyclic graph is a partial order over the collection of control policies.By construction,the partial order graph is a connected graph containing a node corresponding to the policy that stabilizes the goal.Given the collection of policies ,the switching strategy defined by the associated partial order induces an overall switching control policy, denoted.The union of the domains of the instantiated policies included in the partial order gives the domain of the overall policy;that is(1) c2006Carnegie Mellon5The overall control policy induced by sequential composition is fundamentally a hybrid control policy[6, 8,24].The composition of these local policies in a hybrid systems framework enables analysis on the discrete representation of the transitions between policy domains[8,11].We may analyze whether a goal node is reachable using the partial order graph,which functions as afinite state automata[24].Reachability of the goal state and decidability of the navigation problem for a particular collection of policies can be determined by the discrete transitions on,without analyzing the underlying continuous system[24].This analysis may be done prior to,or during,construction of the partial order.The stability of the underlying control policies guarantees the stability of the overall switched policy because the partial order results in monotonic switching[11].This obviates the need for complex hybrid sta-bility analysis of the form given in[5,7,16,38].Disturbances are robustly handled provided their magnitude and rate of occurrence is small compared to the convergence of the individual policies[11].The system in[11]uses multiple policies to demonstrate the inherent robustness of the technique.The deployment of the generic policies–including specification of the setpoints,control policy gains,and pol-icy ordering–is accomplished manually.The deployment uses conservative approximations of the policy domains obtained through experimentation and simulation.Sequential composition-like techniques have been applied to mobile robots.Many examples are for systems without nonholonomic constraints,where the policies are defined over simple cells–polytopes and balls–in configuration space[47,48,57].Other approaches have used optimal control techniques on discrete state space representations to encode local policies[9,22].Sequential composition has also been used to control wheeled mobile robots using visual servoing[28, 44].In these cases,the local control policies were designed based on careful analysis of the system,its constraints,and the problem at hand.These later approaches have the key feature that many of the individual policies are not designed to converge to a single point.In the later example,the“goal”of the highest priority policy is to drive through a doorway[44].It is assumed that another control policy becomes active after the vehicle passes through the doorway.This idea offlow-through policies inspired work where generic policies are defined over polytopes that partition the environment into local cells[13].This work was followed by similar approaches that used different methods of defining the control vectorfields over the polytopes[4,40].These methods were originally developed for idealized holonomic systems,but may be applied to point nonholonomic systems using feedback linearization[4].However,these approaches do not apply to systems with non-trivial body shapes,and cannot guarantee that the linearized system does not“cut a corner”between polytopes and collide with an obstacle.A key feature of these approaches is that the policies are generic,and are therefore amenable to automated deployment[4,13,40].These approaches also formed the base for later work in applying discrete planning techniques to specify logical constraints on the ordering of the local policies[19,20].Using the policy graph, ,a model checking system generates an open loop sequence of policies whose closed-loop behaviors satisfy the tasks specified in temporal logic.In addition to model checking,there has been substantial work in the problem of planning and replanning on discrete graphs.The D*algorithm,originally developed for grid based path planning,facilitates fast replanning based on changes in the graph cost structure[53].A similar,but algorithmically different version, called D*-lite has been applied to graph structures;including those,such as Markov Decision Processes (MDP),that support non-deterministic outcomes[39].6c2006Carnegie Mellon3General FrameworkThis section presents the framework used to address the navigation problem described in this paper.First,a brief overview of the robot modeling framework is given.Next,the generic requirements for the the local policies are presented.This section concludes with an overview of planning based on the discrete transition graph induced by the policies.3.1System ModelsThe robot system consists of a single body that navigates through a planar environment that is cluttered with obstacles.The planar environment,or workspace,is a bounded subset.Letdenote the position and orientation,relative to the world frame,of a reference frame attached to the robot body.As the robot moves through its workspace,evolves on the manifold.To address the navigation problem,the robot body must move along a path that reaches the overall goal, while avoiding obstacles along the way.Let denote the two-dimensional set of workspace points occupied by the body at position and orientation.The obstacles in the workspace are represented as the union over afinite set of convex regions.Thus,for all body positions and orientations,,along a collision free path,The robotic systems considered in this paper are driven by wheels in contact with the planar environment; the wheel-to-ground contact generates nonholonomic velocity constraints.The rotation of these wheels may be represented by internal shape variables[1].Thus,the robot configuration is fully specified as ,where denotes the shape variables.The shape variable velocities are controlled via control inputs.For kinematic systems,;for second-order dynamical systems.This paper is restricted to simple robot models where the nonholonomic constraints determine a linear mapping,, between velocities in the shape space and the velocity,,of the bodyfixed frame.The robot is induced to move along a path by application of the control inputs;the closed-loop dynamics determine the velocity via the mapping.The velocity determines the robot path.The control problem is to specify control inputs such that the system moves along a collision free path and reaches the overall goal.To be a valid control,the inputs must be chosen from the bounded input space.As bounded inputs and the mapping constrain,the navigation problem is tightly coupled to the control problem.To address the navigation and control problem in a coupled manner,we define local control policies over local regions of that are termed cells.Let denote the feedback control policy in a collection of policies and let denote the local cell.Define the cell in a subset of that locally represents the configuration space;the cells are restricted to compact,full dimensional subsets of without punctures or voids.It is assumed that the boundary of the cell,,has a well defined unit normal,, that exists almost everywhere.The policy goal set,denoted,is a designated region in the local cell; that is.In this framework,the coupled navigation and control problem of moving the robot body through the space of free positions and orientations of the bodyfixed frame is converted to a problem of specifying safe feedback control policies over the local cells,and then composing these local policies to address the larger navigation problem.Over each local cell,define a feedback control policy,where denotes the tangent bundle over the robot’s configuration space.In other words,the local policy maps the current robot state,whose configuration falls within the local cell,to an input in the bounded set of inputs associated with the policy.The policy must be designed such theflow of induced by entersc2006Carnegie Mellon7Figure4:A cell defines a local region in the space of robot body positions and orientations.In this example, the cell is funnel shaped and the designated goal set is the small opening at the point of the funnel..Thus,instead of a specific path,the closed-loop dynamics of the local policy induce a vectorfield flow over the cell that enters.3.2Generic Policy RequirementsFor a local policy to be useful in the sequential composition framework,it must have several properties.First, to be practical,the local policies must have efficient tests to see if a specific local policy can be safely used; that is the system must be able to determine if the current robot state is within the domain of a given policy. Second,to induce safe motion,the cell must be contained in the space of free body positions and orientations so that collision with any obstacle is not possible while the body frame is within this cell.Third,under the influence of the policy,the induced trajectories must reach the policy goal set defined within the local cell without departing the associated cell from any initial position and orientation within the cell.Finally,the system must reach the designated goal set infinite time for any initial condition within the cell.The requirements discussed below are generic with respect to the given robot model and any specific cell definition.The focus in the remainder of this section is on the generic policy requirements that enable the proposed hybrid control framework to work with a variety of system models.3.2.1Simple Inclusion TestsA given policy is safe to activate if the robot state is within the policy domain,.The domain,which depends upon the policy definition,generally specifies both configurations and velocities.As the policies are defined over,thefirst test of domain inclusion is that.For kinematic systems, because the state is simply the configuration.Therefore,only the cell inclusion test is needed to check to see if a policy is safe to activate for the simple models considered in this paper.8c2006Carnegie Mellon。
Oracle Cloud EPM Pillar Two 解决方案说明书
Constituent Entities •Which companies are affected? GloBE Income•Determination ofthe assessmentbasisCovered TaxExpense•Determination of thetax payments madeETR & Top-upDetermination of theETR, and if necessary,the top-up taxPillar Two in Oracle Cloud EPMThe Pillar Two solution in Oracle Cloud EPM helps tax and finance stakeholders at multinational companies to automate the end-to-end Organisation for Economic Co-operation and Development (OECD) Pillar Two requirements. Built with best practices, the solution ensures reporting compliance with regulations and empowers users with robust tax forecasting, modeling, and analysis capabilities to better understand impacts across all your legal entities.Automates all data collection, calculation, process automation, and reportingPillar Two in Oracle Cloud EPM addresses the full top-up tax model. The solution includes data collection for both, data that must be manually collected, as well as data that can be collected from source systems. Thetop-up tax model includes the Global Anti-Base Erosion (GloBE) Income calculation, including Income Inclusion Rule (IIR) and Undertaxed Payment Rule (UTPR), the Cover ed Tax Expense calculation, the ETR Reconciliation,and the Top-up Tax calculation. It also includes pre-built dashboards, reports, and analytics.Image 1: An example of the Pillar Two dashboardImage 2: The Pillar Two calculation flow Key business benefitsBe ready for Pillar Two requirements andimplement the Oraclesolution quickly byleveraging the best practice tax reporting framework Speed up the financialclose and keep taxreporting connected to thebroader financial closeprocessLeverage your existing investment in OracleCloud EPMAutomate all your taxaccounting processes bytaking advantage of themodular features for taxprovision, country-by-country reporting, transferpricing, and moreKey featuresFull top-up tax modelincluding GloBE Incomecalculation, Covered Taxexpense calculation, ETRreconciliation, & Top-upTax calculationPrebuilt dashboards and reports provide you withthorough analysisTask Manager allows you to coordinate Pillar Twoactivities across all usersData Managementcapability allows you toautomate data collectionfrom any source systemPillar Two features areconnected to FinancialConsolidation & Close,Transfer Pricing, andCountry by CountryReporting (CbCR), and therest of the Cloud EPMThe Pillar Two capabilities are included as part of yourCloud EPM deploymentBest practices are built-in to Oracle Cloud EPM and designed to work with your cloud and on-premises systems as well. For example, it works withboth Financial Consolidation and Close in Oracle Cloud EPM as well as on-premises Hyperion Financial Management (HFM). This allows you to leverage your existing investments, but quickly address the Pillar Two requirements in a robust, auditable process.Automate data collection from any source systemPillar Two data requirements go beyond the general ledger. The data required will be sourced from various system such as the financial consolidation system, tax provision, ERP and sub-ledgers, HR systems, sales systems, etc. Using the standard Data Management capabilities in Oracle Cloud EPM, tax departments can automatically collect the data from these source systems and transform it to the needs of the Pillar Two data model. Importantly, this ensures a strong audit trail, and enables tax resources to spend more time on data analysis and waste less time collecting data. Any data that cannot be easily automated, can be manually entered into the best practice Pillar Two Input screens within Oracle Cloud EPM.Ensure process collaboration across the enterpriseThe Pillar Two process will require coordination of activities from colleagues across tax, finance, and other operational parts of the enterprise. To this end, Oracle Cloud EPM includes an easy-to-deploy Task Manager to ensure seamless coordination and collaboration across the entire process. Tasks can be assigned and monitored from a central dashboard. End users are provided a simple step-by-step process flow to guide them through their Pillar Two responsibilities. This allows you to minimize the impact of the new requirements across the enterprise to ensure that the Pillar Two process runs as smoothly as possibleTax forecasting & modeling for Pillar Two impactsPillar Two represents a major change to tax process and tax planning strategies. One of the core benefits of the Pillar Two solution in Oracle Cloud EPM is the ability to forecast and model the future impacts of the new requirements. In addition to the world-class calculation and reporting capabilities tax users can copy Pillar Two data to forecast scenarios for end-to-end modeling. This allows tax power users to change assumptions that could have material impact on the outcome. This ensures that your tax function can best prepare the enterprise for the new realities of the global minimum tax. Are you Pillar Two ready? If not, Oracle Cloud EPM can help fast!The Pillar Two module in Oracle Cloud EPM has best practices built in. This allows you to get up and running very quickly. While the module is part-and-parcel of the Oracle Cloud EPM, it is built in a manner that allows the tax department to deploy it without impacting other existing financial processes. This gives tax stakeholders the independence they need, but still allows for the synergy of data and process with other cloud or on-Premises financial processes – such as HFM or Financial Close and Consolidation (FCC). Be prepared for Pillar Two. Empower your tax department today by simply launching the Pillar Two capabilities in Oracle Cloud EPMConnect with usCall +1.800.ORACLE1 or visit . Outside North America, find your local office at: /contact. /oracle /oracleCopyright © 2023, Oracle and/or its affiliates. All rights reserved. This document is provided for information purposes only, and the contents hereof are subject to change without notice. This document is not warranted to be error-free, nor subject to any other warranties or conditions, whether expressed orally or implied in law, including implied warranties and conditions of merchantability or fitness for a particular purpose. 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Hyperon全套培训资料_计划与预算_PLN4.1CMA_L3_Hyperion_Planning_Dimension_Overview
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Determining Performance Efficiency
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Dense Dimensions
Dense Dimensions
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At the end of this lesson, you should be able to: Identify required dimensions Identify user-defined dimensions Describe dense and sparse dimensions Describe data block creation Describe aggregation, data storage, and calculation options Set up alias tables
hyperion-financial management
ORACLE HYPERION FINANCIAL CLOSE MANAGEMENTORACLE’S FINANCIAL CLOSE MANAGEMENT SOLUTION IS THE FIRST OF ITS KIND – A FINANCIAL CLOSE MANAGEMENT SOLUTION THAT SPANS THE EXTENDED FINANCIAL CLOSE CYCLEFEATURES•Web-Based Task Scheduling •Pre-built dashboards •Active Calendars•Task automationBENEFITS•Process consistency •Improved control•Clear communication•Easy to identify bottlenecks The Oracle Hyperion Financial Close Management application is built for centralized, web-based management of period-end close activities across the extended financial close cycle. The first application of its kind, Oracle Hyperion Financial Close Management will help manage all financial close cycle tasks including ledger and sub-ledger close, data loading and mapping, financial consolidation, reconciliation, tax/treasury and internal and external reporting processes – any task associated with the extended financial close.Get Control of the Extended Financial CloseMost companies manage the extended financial close process using offline spreadsheets, emails and phone calls. This is cumbersome and time-consuming and can often slow the financial close and make it more error-prone. Another challenge is the wide diversity of the tasks themselves - the financial close can mean different things to different people. To a divisional controller it may mean closing out the sub-ledgers and general ledger at month end or quarter end and submitting the results to corporate. To a headquarters accountant the financial close is about collecting the details from the divisions, making final adjustments and performing the corporate financial consolidation and reporting. And, to the CFO and other finance executives it’s about finalizing the results, announcing earnings and creating 10Q/10K’s and other regulatory filings for the SEC and other stakeholders. The extended financial close and reporting process is all of the tasks and processes from closing out the sub-ledgers to creating and delivering financial filings to the SEC and other regulatory bodies – which involves many systems, departments and individuals. This process is very complex to manage and too important to control using “hope and email.”Ultimately, without a centralized approach to task management, it becomes more difficult to deliver results quickly to both internal and external stakeholders – while ensuring compliance, auditability and accuracy. And, without an automated system for coordinating and tracking the entire process, identifying bottlenecks and areas for potential improvement, it’s very difficult to shave time from the extended close and reporting process.Example of the Extended Financial Close CycleKey FeaturesFunctionality includes:•An easy to use task scheduling and management feature to ensure the correct prioritization of closing tasks.•Pre-built, web-based dashboards for monitoring the progress of the financial close. Common calendar views, task list views, and Gantt views are leveraged for each user’s tasks based on security.•Active calendars and task lists that allow you to launch applications to complete tasks from the calendar itself.•An automation feature – allows you to schedule tasks for lights-out processing.• A roll-forward feature that allows you to quickly set up new financial close calendars based on the prior financial close.Tasks can be anything that needs to be done during the close process – whether in the transaction system, general ledger, consolidation system or reporting system. Employees are assigned to each task and the tasks are given a due date relative to each period end date so it’s also easy to identify bottlenecks in the process.Oracle Hyperion Financial Close Management Dashboard Summary With Oracle Hyperion Financial Close Management, companies can begin managing the financial close process proactively, rather than being surprised by failures in the process that can cause extensive delays. In addition, once bottlenecks and inefficient processes are made visible, they can be dealt with through process improvements and clear communication of objectives. Oracle Hyperion Financial Close Management can be the first step to a world-class financial close. Contact Us For more information about Oracle Hyperion Financial Close Management, please visit or call +1.800.ORACLE1 to speak to an Oracle representative. Copyright © March 2010, Oracle and/or its affiliates. All rights reserved. This document is provided for information purposes only and the contents hereof are subject to change without notice. This document is not warranted to be error-free, nor subject to any other warranties or conditions, whether expressed orally or implied in law, including implied warranties and conditions of merchantability or fitness for a particular purpose. We specifically disclaim any liability with respect to this document and no contractual obligations are formed either directly or indirectly by this document. This document may not be reproduced or transmitted in any form or by any means, electronic or mechanical, for any purpose, without our prior written permission. Oracle is a registered trademark of Oracle Corporation and/or its affiliates. Other names may be trademarks of their respective owners.ORACLE’SPERFORMANCE MANAGEMENTAPPLICATIONSOracle’s performance management applications comprise a modular suite of integrated applications that support a broad range of strategic and financialperformance management processes to enablemanagement excellence. Part of Oracle’s enterprise performance management system, theseapplications can be quickly deployed out of the box, extended with Oracle’s business intelligenceproduct family, or tailored to meet your organization's specific needs.RELATED PRODUCTS: Oracle’s performance management applications include the following products:Strategy Management SolutionsFinancial Close and Reporting Solutions• Oracle Hyperion Financial Management• Oracle HyperionDisclosure Management • Oracle Hyperion Financial Data Quality Management • Oracle Hyperion Analytics Link for Oracle Hyperion Financial Management • Oracle Hyperion Financial Reporting• Hyperion Enterprise Enterprise Business Planning Solutions Profitability and Cost Management Solutions Enterprise Dimension Management Solutions。
集团合并报表信息化现状、问题及对策分析
集团合并报表信息化现状、问题及对策分析作者：武钰钦来源：《财会学习》2020年第01期摘要：进入21世纪以后，我国经济快速增长。
在此过程中诞生了很多大型企业，这些大型企业定期披露合并报表是企业的一件大事，所以合并报表信息化迫在眉睫。
文章首先分析了目前大型企业合并报表编制的现状;其次分析了合并报表自动化将给企业带来的好处，再次分析了合并报表自动化在企业中应用存在的障碍;最后根据企业所处的宏微观情况，提出了一些对策，以期为大型企业的合并报表信息化提供参考。
关键词：合并报表系统;ERP一、引言为了能够更好掌握企业的财务及经营状况，企业管理者希望能够及时看到企业的财务报表。
对于央企、国企来说，需要按照国资委的要求每个月报送企业财务快报。
对于大型企业来说，财务人员每个月出一份合并财务报表工作量非常的大，而且其效率不能很好地满足集团管理的需求[1]。
对财务信息日益增长的需求与财务人员手工提供信息效率低的矛盾是普遍存在的。
目前市场上已经有一些ERP公司提供合并报表系统，但是这些系统在企业中的应用仍然存在一定的障碍，本文通过分析合并报表系统在集团中应用的现状以及存在的障碍，然后提出相应的对策，以期对集团合并报表信息化提供参考。
二、合并报表系统现状目前，在市场上具有代表性的合并报表系统有：SAP公司旗下的BPC（Business Planning and Consolidation）系统，该系统是企业的合并报表自动化以及预算管理自动化软件[2]。
BPC 软件的特点在于能够与SAP ERP进行很好的数据传输，使用该软件的代表性企业有：太平洋保险、中航国际等;海波龙HFM（Hyperion Financial Management，该软件专注于合并报表的解决方案，它不仅可以与甲骨文ERP进行很好的集成，还能与其他主流的ERP实现良好的数据集成，例如SAP ERP、金蝶、用友等。
已成功建成并投入使用该系统的代表性企业有华润万家、四川长虹等;还有一些ERP公司也开发了自身的合并报表系统，如用友公司的合并报表系统。
财务总监英文简历
财务总监英文简历以下文章作者为您整理的财务总监英文简历（共含9篇），供大家阅读。
篇1：财务总监英文简历财务总监英文简历模板求职者惯用的求职方法是：看到职位信息后，通过email、寄信的方法发送简历，然后在家坐等消息，可往往一周过后仍然音讯全无。
很多条件不错者不禁纳闷：为何企业网络上还在不断招聘，我发的`简历却石沉大海?在求职竞争激烈的时代，聪慧人应当主动出击，顺藤摸瓜发掘信息。
有一位求职者懂得到心仪的企业正在招聘，但应聘者趋之若骛，自己的简历很难脱颖而出，于是除了利用惯例道路发送简历外，还登陆企业主页获取了企业HR 的邮箱，通过114查询获取企业总机号码，进而得知HR部门分机、招聘负责人姓名以及电话号码等。
然后通过致电HR或者快递简历的方法，引起HR的注意，让简历顺利交到HR的手中。
以下是yjbys作者和大家分享的财务总监英文简历模板，更多内容请访问()。
Name: yjbys gender : male Birth : # telephone : Degree : Bachelor Professional: International Finance Experience : 10years national : Han School: University of # address : # E-mail : Self Assessment :Almost 16 years cross-cultural working experience related to accounting, finance and auditing area.Strong ERP system design background and knowledge of large database, sufficient experience in using different manufacture and service MIS.Sufficient experience with US GAAP , SEC 10-Q,10-K and SOX.#working independently under pressure or as a cooperative team membe.Can refine the financial working procedure and internal control standard effectively. Target Job：Desired Job Category: Accounting Supervisor Ledger Reconciliation | Financial Director Controller | Financial Manager | Accounting Manager Desired Job Industry: Electronics-electronics | Telemunications(Equipment-Added Service) | Professional Service (Consultancy) | Pharmaceuticals | Machine Manufacturing Industry Desired Salary: Negotiable Desired City: # I can start from: within 1 month Work Experience ：-#Science Inc.Corporate Finance ControllerResponsibilities and Achievements:Control the overall finance and fiscal management for eight affiliated panies, including the panies of medical vaccine R&D, blood serum manufacture, culture medium manufacture, medical instrument retail trade, and investment, located in different provinces or countries.Oversee and approve the processing of revenue, expenditure, data entry, ledger update, department budgets, account maintenance, cash flow forecast and etc. Develop and implement finance, accounting, cost, asset, cash and auditing procedures. Establish and maintain appropriate internal control safeguards.Prepare and ensure the financial statements, consolidated financial reports (include 10K & 10Q to SEC), and business analysis ply with local, government, SEC policy and the BOD oversea budgetary reporting requirements.Evaluate, coordinate, approve, implement and improve the financial programs and financial and management information systems (ERP) for the whole pany.municate with other managers and the BOD, to provide consultative support, through financial and management information analysis, government policy research, to corporate business planning and investing initiatives. Such as the acquisition performance or joint venture set up. Include investment project forecast, feasibility appraisal, return rate analysis, finance due diligence, project asset evaluation, and law issuestudy, equity structure design.Responsible for finance & operation integration of additional subsidiary pany, include former employee training, finance management upgrade, embedding corporate finance & internal control policy and etc.-某#Asia Pacific, ltdFinance ControllerResponsibilities and Achievements:As the project manager, newly set up QAD system(ERP). Use the QAD to plete and continuously improve the working process and procedures with Production, Logistic, Purchase and Sales department, make sure all the operations are under system control, reconcile with each other, ply with internal control policy, and make sure all of the QAD activities is in line with related laws and rules of the SAFE, Tax Bureau, Custom and Bank(Export VAT Refund); Responsible for all the accounting practice of pany, including financial planning, budgeting, creating month end financial reports, and preparing year-end reports for tax and business purposes and to oversea corporate, ensure timely reporting with high quality as well; Establish budgetary control systems and monitor pliance to budgets. Prepare analysis of data for management and executive board members. Lead and manage an efficient accounting and finance dept. Conduct standard cost set up and analysis, administer payroll affair, Maintain close working relationships with tax bureaus and all relevant governmental authorities as well as with independent auditors; Responsible for cash flow management, cash flow forecast, handling the financing in the authorized fields(Bank Loan, Foreign Loan and Capital Increase) to acplish new factory, and etc.-某#pany of#(China) Investment Co., LtdFinance SupervisorResponsibilities and Achievements:With Platinum, Crystal Report system, Hyperion and E-business system, handle two full sets of accounting books，including a investment co. and a trading pany Produce consolidation monthly financial and Managing reports of PRC GAAP & #GAAP to local and overseas management，Responsible for cash flow management, cash flow forecast，reconciliation AR with affiliate pany, Self assessment, Edit and improve internal control policy to ply with SOX，Liaise with inter-offices and external parties, including auditors, tax bureau, suppliers, clients，Conduct administration of payroll affair，Perform monthly variance and analytical review on financial reports between actual and forecast data, Refine finance and related business process, and etc. Education ：- of#MasterMajor Category:International FinanceMajor Description and Courses:Having theories and experiences on Corporation Credit Rating and issued related thesis. 篇2：英文简历－－财务总监PERSONALAddress: 602#, 5 Hong Run Apartment, 2179 Pu Dong (S.) Road, ShanghaiTel:#(8621) #Mob: (86) #E-mail:09-07#Bachelor of EconomicsShanghai University of Finance & Economy09-07#The High School Affiliated to Fu Dan UniversityWORKING EXPERIENCEOver the last ten years, have worked in various multinationalcorporate or investment house in the position of finance director or chief financial controller overcharging the financial operation of the pany starting from financial planning, budgeting, monitoring and risk control system etc.. Very familiar with relevant legislative and financial framework of either local Chinese panies or foreign panies operating in China. Strong relationship with local government entities and intermediary firms especially in the field of accounting, auditing, asset appraisal firms and mercial banks.04-Present NewMargin VenturesChief Financial ControllerNewMargin Ventures is one the leading venture capital firms in China with a range of domestic and international investors including such names as Motorola and was hired as one of the key members involved in the setting up of NewMargin Ventures especially in the area of financial and internal operation system detailed as follows:Res ponsible for leading the group’s finance function and establishing &improving the internal control system;Responsible for internal finance & accounting;Developed the staff performance evaluation system and incentive scheme;Monitored the fund’s fina ncials and prepared the shareholders reports;Coordinated with the fund / custodian bank to execute our investments effectively;Coordinated with the audit firm to implement the annual audit of the fund and financial due diligence on potential deals;Assisted the investment manager monitor the portfolio panies;Assisted in the merger negotiation and listing of portfolio panies;Assisted in the raising of an RMB fund, which was the first JV fund in China under the latest PRC laws.01-04#Toshiba (China) Co., Ltd. Shanghai BranchFinance DirectorLed a team in managing the group’s financial & accounting function;Developed strategic tax plans for the pany;Prepared the annual budget and reviewed / supervised its implementation;Performed financial an alysis of the group’s cost control function.05-01#Waigaoqiao Free Trade Zone Developing (Holding) Co., Ltd.Financial ManagerPrepared the budget and controlled the execution;Prepared strategic tax plan under laws;Organized the accounting work.05-05#Zhangjiang Hi-Tech Zone Developing .Assistant Financial ManagerResponsible for taxation claims;Conducted budget setting and monitoring.07-05#Shanghai Tea Import & Export .Chief Accountant / Internal AuditorResponsible for bookkeeping and maintenance of general ledger.PERSONALFluent written and spoken English and Mandarin.Actively participate in sports, reading and traveling.。
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• 资产负债表与利润及利润分配表之间验证：利润及利润分配表-未分配利润=资 产负债表-未分配利润
• 报表科目与明细科目之间验证：例如：应交税费明细表=资产负债表-应交税费
• 当数据没有通过勾稽关系的验证的时候，系统会有相应的提示，并告知用户没有通过验 证的条目和内容； • 可设置哪些内容没有通过验证无法提交，哪些只是进行提醒；强制校验和合规校验
统一财务数据平台
支持多准则、多架构、多币 种 自由设置抵消规则、勾稽关 系、审批流程 预设内部对账平台、手工调 整分录 完全面对财务用户
权限管理
多维分析报表
按图形化的报表工具 与excel双向集成 修改报表格式
货币转换
能按照指定汇率进行币种折算，满 足不同币种金额报表合并或汇总的 需要
Office集成
滚动 预测 战略 规划
预算编制（围绕年度目标及业务计划进行资源配置）
根据分解后的目标计划在现有条件下所需的资源（市场、员工、资金等） 编制预算，预算过程可能涉及到多个版本
沟 通
分析 报告
目标
目标 分解
预算控制
定期的对预算和实际数据进行对比，对公司实际运营发生的业务活动及费 用进行预算控制发现问题。
协 调
06--数据调整：设置权益法、重分类、准则差异 、审计等调整类型，单独存储调整数据
权益法调整：使用VB脚本编写规则，自动完成权益法确认的计算 数据调整 重分类调整：使用科目架构或者VB脚本编写规则的方式实现重分类调整 未达调整及准则调整：使用手工日记账方式实现调表不调账的调整 审计调整：手工日记账方式实现。账务系统调整滞后于合并系统，要规范处理方法
• 保留合并过程各阶段的数据变化过程； • 系统自动抵销与手工抵销相结合，规范的抵销规则通过系统设置自动实现，非规 范的通过抵销分录模板的建立手工输入； • 可以灵活展现符合中国、香港和其他地区需要的合并工作底稿
基础数据 调整数据 折算数据
抵销数据
抵销后数据
09--组织架构调整：支持复杂持股模式的处理，灵 活调整组织架构
股权抵销
Oracle
各类调整 合并报告
?
天
用友/金 蝶/SAP
准则转换
其他业务 系统
组织架构调整
手工收集数据 核算系统分散多样
复杂的合并过程， 大量手工处理 多口径报表
合并系统处理
先进系统的应用可以帮助集团企业快速改善合并报 表环节、缩短关帐周期
合并工作底稿 多种形式的分析展现
数据验证
1.资产负债平衡验 证 2.表与表之间的验 证 3.数据变化趋势验 证
17
预算编制－多维度编制与分析模型
航线的层级架构 - 地区 - 航线 (往返) - 航段 - 航班.
时间
年 季度 月
日
经济舱 舱位 CA123 航班号. LXA-PEK Segment LXA-CTU-PEK 航线 商务旅行 市场 上海 A320 深圳办公室
预算科目 组织架构 投资项目 预算维度 场景 版本 时间 地区/业态
通过业务规则的设定，灵活、方便、快捷的满足 滚动预测中相应的特殊计算。 一套模型，完成资本支出预算、人力资源预算、 运营计划、资金预算等
自上而下的目标下达，自下而上的预算汇总
支持滚动预测，如1+11、2＋10、3＋9等 支持预算调整 同一种预测条件下可以储存多个版本的预测数据
• 数据上载 • • • 在财务合并报表系统与ERP系统之间建立数据接口，实现数据自动上载 利用系统工具Excel插件SmartView将数据上载至系统 利用系统Web表单，直接输入数据至系统 利用手工日记账，录入调整分录数据
Oracle合并报表系统
Oracle
用友
浪潮、远光 等系统 Excel
04--数据验证：提供了自定义数据验证的功能，并将 数据验证与合并流程相结合，强化数据质量管理
• 按照股权关系逐级搭建法定合并架构，按照业态搭建分部架构，出具法定合并报表 组织架构 • 按照区域划分搭建管理合并架构，出具管理合并报表 • 多套架构合并报表结果一致
法定口径
月度股权合并 公司及其他 香港公司合并 管理服务公司总部 China Agri-industries Holdings Limited China Agri-industries Limited Polychest Group
交易层面 关联交易核对 系统中管理各单位每笔关联交易，可以按照设定的规则自动核对或手工核对； 出现差异可以选择触发email通知对方；
各合并层级都可以看到所属单位的内部往来对账情况； 各单位导入或录入每一笔关联交易的交易号、日期、 设定对帐规则，可以按照基于交易号、或者按照 科目进行自动核对，还可以进行手工核对 记账单位、往来方、对应科目、金额、说明等
05--关联交易核对：提供了关联交易对帐平台， 实现往来双方自行核对，同时支持基于科目层面 和交易层面两种方式
科目层面 关联交易核对
按照业务类型设置关联交易对帐报告，往来双方看到对方相关数据，进行核对； 出现差异可以选择触发email通知对方； 各合并层级都可以看到所属单位的内部往来对账情况；
关联交易核对：提供了关联交易对帐平台，实现 往来双方自行核对，同时支持基于科目层面和交 易层面两种方式
行核对；
2.由往来双方自 行核对； 3.科目层面和明 细交易层面的往 来核对
数据上载：通过数据集成抽取多ERP系统的数据，辅助结合手工补充的方式进行数据上载 组织架构：多套组织架构、按期间管理 科目体系：满足多套准则的主表和附表
多维度体系是先进 合并系统的基础
01--组织架构：支持法人、管理、分部等多套组织架 构，满足数据披露的同时，也满足企业管理需要
东海粮油合并 减：东海大米
油脂
东海粮油油脂 北海粮油合并 黄海粮油合并
T1
减：东海面粉
中粮祥瑞合并
油脂本部其他业务 中粮国际油脂业务 服务公司油脂业务
面粉
油脂本部
油脂本部其他业务 中粮国际油脂业务 服务公司油脂业务
香雪东大合并 东海面粉
面粉本部其他业务 中粮国际面粉业务
面粉本部
面粉本部其他业务 中粮国际面粉业务 服务公司面粉业务
Hyperion 企业绩效管理
全球最卓越的企业绩效管理软件提供商
财富500强前20家企业中19家，使用Hyperion实现财务分析 财富500强前20家企业中12家，使用Hyperion完成预算管理 财富500强前20家企业中14家，使用Hyperion实现财务合并
9个获CFO杂志“最佳财务状况奖”的企业中，8个是Hyperion的用户
预算 控制 预算 编制
分析报告（目标完成情况跟踪分析）
客观地准确地及时地反映公司发生的运营活动及消耗的资源。将记录的结 果汇报给相应的管理层。将实际发生的数据与预算进行差异分析，关注 “例外”事项的管理
滚动预算、预测
根据目标完成情况对下一时段进行预测，以及时更新反映公司最新的可能 的经营结果
多维分析引擎支撑的全面预算体系
S2 100% M2 80% T2
60%
T1
T2
M1
M2
2009年8月
2009年9月
10--分析展现：多种分析展现方式，满足不同用户 的使用需要
• 管理层希望能直观地从大指标下钻到明细内容； 分析展现 • 合并管理人员希望能看到完整的合并过程和结果，并给管理层提供美观、内容丰 富的对内对外管理报表； • 操作人员希望合并系统的数据能与EXCEL、WORD、PPT等进行良好的数据交 互，并能随时根据领导的要求，快速自定义出查询报表； • 能转换成XBRL格式
提供统一的财务数据合并平台
勾稽校验
预置校验公式包括表内、表间、公 司间数据勾稽关系审核
数据集成
提供多种数据集成服务工具，可以 实现不同异构ERP系统/财务系统 数据连接
追溯数据源
与财务信息系统保持数据一致性， 能够从合并数据追溯到单笔交易和 凭证
内部往来对账平台
能够生成公司内部交易的余额不匹 配例外报告，并可根据错误报告,手 工注销内部余额的差异
• 依据数据收集模板建立系统不同口径的报表科目及附注所需明细科目 科目体系 • 结合ERP系统，完善系统明细科目，以满足更明细数据抵销的需要 • 通过明细科目与报表科目的映射出具不同口径的报表
财务报表合并系统 明细科目 财务报表合并系统 报表科目
财务报表合并系统科 目搭建原则
财务报表
1001现金 管理报表和会 计报表科目 来源 财务合并报表 系统报表科目 来源 ……
所有报表能够输出至常用的办公软 件（如MS-Office）以便进一步处 理
准则转换
支持多准则自动转换 中国准则、香港准则 手工调整分录 完整审计轨迹
安全管理 详细日志
财务报表输出
基于会计科目维度自动生成各类财 务报表满足各种需求： 对外披露、内部管理、国资委、财 政部
• 组织架构调整 • •
H 60%
在一个时间点可以有不同的组织架构，提供按期间保存动态组织架构的功能 定期管理和跟踪组织结构的变更，比较过去的，现在的和规划中的组织和股 权结构 按期间分配不同的控股比例、合并比例、合并方法
H 60%
100%
100%
S1
S2 80% 70% 100% 60% T1
S1 80% 100 % W1 T2 M1 70%
管理口径
月度管理合并 公司及其他 香港公司合并 管理服务公司总部 中粮国际职能费用
H
100 % T 60%
东海粮油合并 减：东海大米 减：东海面粉
100% S2 80% T2 业务组织架构 10%
中粮国际职能费用 油脂 东海粮油油脂 黄海粮油合并 中粮祥瑞合并 油脂本部 面粉 香雪东大合并 东海面粉 面粉本部