Integration of Decision-Making Components in ERP Systems

Jānis Pekša and Jānis Grabis

Institute of Information Technology, Faculty of Computer Science and Information Technology,

Riga Technical University, Kalku street 1, LV-1658, Riga, Latvia

Keywords: ERP Systems, Decision-Making, Integration.

Abstract: Enterprise resource planning (ERP) systems are large modular enterprise applications intended for

execution of majority of enterprise business processes with focus on transaction processing. However, the

business processes often also require complex decision-making. Data processing logics is deemed as

complex decision-making logics if it involves complex analytical calculations and requires domain specific

knowledge. This paper reviews existing research on decision-making capabilities of ERP systems and

identifies different approaches for integrating decision-making logics in ERP systems. This review leads to

an initial framework for integration. This framework evaluates current solutions used in integration. The

research findings suggest that decoupling of decision-making logics from ERP systems enables usage of

advanced decision-making techniques for execution of decision intensive business processes in real-time

though logical integration between decision-making components and business processes should be

improved.

1 INTRODUCTION

ERP systems are large modular enterprise

applications intended for execution of majority of

enterprise business processes. They are primarily

geared towards transaction processing. However,

many modules contain complex decision-making

logics (Holsapple and Sena, 2005). Data processing

logics is deemed as complex decision-making logics

if it relies on analytical or managerial models for

determining course of action in business process

execution and often requires domain specific

knowledge. Examples of decision-making logics are

inventory replenishment and production planning

decisions. Bahrami and Jordan (2013) indicate that

ERP is to improve the decision-making process at

both strategic and operational levels, by providing

necessary information, tools and capabilities

necessary to enhance the decision-making process.

Traditionally, decision logics is embedded in

ERP systems. Companies frequently need to modify

this decision-making logic to meet specific

requirements (O’Leary, 2008). They have incentives

to continuously improve the decision-logics that is a

major source of competitive advantage. Frequent

modifications are needed as the results. Usually

modification is done in the ERP’s internal

development environment. Results of the

modification process are not always satisfactory

(Aslan et al., 2012).

Incorporating the decision-making logics into

ERP systems has several drawbacks such as

inflexibility and cost of changes (Borovskiy et al.,

2009). Advances in technology allow for using other

technologies for providing decision-making

capabilities in ERP systems (Uppström et al., 2015).

That includes research on integration of decision-

making logics in ERP systems beyond the embedded

approach. These approaches include data

warehousing and OLAP (Liu and Liu, 2010), model-

driven configuration and system thinking (Kurbel

and Nowak, 2013), incorporation of the semantic

information in structured models (Deokar and El-

Gayar, 2013) and a generic association model

between planning module and ERP system (Wei and

Ma, 2014)

While ERP systems are highly standardized

systems, there is no common agreement on role and

implementation of decision-making components in

ERP systems. The overall goal of the proposed

research is to clearly distinguish decision-making

components in ERP system to support development,

maintenance and utilization of these components.

These components should be distinguished both at

the logical level and technical level. At the logical

Pekša, J. and Grabis, J.

Integration of Decision-Making Components in ERP Systems.

DOI: 10.5220/0006779601830189

In Proceedings of the 20th International Conference on Enterprise Information Systems (ICEIS 2018), pages 183-189

ISBN: 978-989-758-298-1

183

level, users should well-aware of implication of

decision-making components on execution of

business processes. At the technical level, decision-

making components should modifiable (Uppström et

al., 2015), portable (Vidoni and Vecchietti, 2016)

and scalable (Aslan et al., 2012).

The objective of this paper is to review existing

research on decision-making capabilities of ERP

systems and to identify different approaches for

integrating decision-making logics in ERP systems.

The specific research questions are: 1) what kind of

methods are used to provided decision-making

capabilities in ERP systems; and 2) what kind of

technologies are currently used to implement these

methods.

The paper is structured as follows. Section 2

proposes to use an application integration viewpoint

to investigate decision-making components and ERP

systems and briefly reviews related research.

Integration approaches are identified, and the

integration framework is proposed in Section 3.

Section 4 concludes.

2 BACKGROUND

Decision-making capabilities of ERP systems are

integrated from application integration viewpoint

(Linthicum, 2003). From this perspective we

distinguish: 1) decision-making capabilities as an

internal component of ERP systems; 2) decision-

making capabilities as external component

integrated by data sharing; and 3) decision-making

capabilities provided by external components

forming an integrated process jointly with ERP data

processing capabilities (Figure 1).

The preliminary literature review is conducted

following these integration perspectives. Table 1

lists keyword used to identify the relevant literature.

Packaged ERP systems contain many functions

for decision-making including functionality for

making inventory replenishment, production

planning and forecasting decisions. Aslan et al.

(2012) evaluates ability of ERP systems to meet

requirements characteristic to make-to-order

companies. That also includes evaluation of

planning and other decision-making capabilities.

Samaranayake and Toncich (2007) review

manufacturing planning, control and execution in

ERP systems. They indicate that there is a variety of

strategies and methods available and appropriate

case specific configuration of these functions is

required. Similarly, multiple forecasting methods are

also incorporated in ERP systems and they provide

different accuracy and are applicable in specific

circumstance (Catt et al., 2008).

Figure 1: Application integration perspective of decision-

making capabilities in ERP systems.

Table 1: Research subject group keywords.

Research subject

Keywords

Internal ERP

decision-making

capabilities

Enterprise resource planning,

decision-making, production

planning, inventory

management, forecasting,

optimization, simulation

Decision-making

capabilities

provided by

other systems

integrated with

ERP

ERP systems, decision support

systems, information systems

integration, business

intelligence, advanced planning

systems

Interfacing

between ERP

systems and

external systems

Service-oriented architecture,

decision services, integration

standards and formats

Due to unique enterprise requirements, ERP

systems often lack the necessary functionality, for

example, Nikolopoulos et al. (2003) develop a new

module for maintenance management and this

module interacts with asset, production and

warehouse management modules. ERP systems

support decision-making within a single

organization but in supply chain management these

decisions have profound impact on supply chain

partners (Kelle and Akbulut, 2005). ERP systems

can serve as a basis for development of such

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collaborative decision-making components, for

example, "autonomic supply chain" (O’Leary, 2008)

and vendor management inventory (Shiau and Tsou,

2015).

To enhance existing decision-making capabilities

ERP systems are frequently integrated with other

applications. It has been identified that most

frequently ERP systems are integrated with

Advanced Planning Systems (APS), data analytical

systems such as data warehouses and business

intelligence and special purposed modelling tools

such as simulation tools.

Chou et al. (2005) point out that business

intelligence systems use data from ERP systems to

support organizational decision-making processes.

This is an example of decision-making capabilities

provides by external components using data sharing.

Recently, Russman et al. (2017) investigated

providing data feedback from business intelligence

systems to ERP systems. Moon and Phatak (2005)

use simulation to check production schedules

generated by an ERP system. This approach is

further extended by involving APS to generate

advanced schedules evaluated using simulation

while the ERP system focuses on transaction

processing (Krenczyk and Jagodzinski, 2015). Van

Nieuwenhuyse et al. (2011) develop an advanced

resource planning system, which particularly focuses

on fine-tuning of manufacturing planning and

control parameters used in ERP systems. Large

scale APS typically included functionality for long,

mid and short-term planning in areas of supply chain

design, master planning, scheduling, transportation

and others (Meyr et al., 2015).

The aforementioned papers focus on enhancing

functional capabilities while a group of other papers

investigate technical aspects of integrating ERP

systems with other applications. Integration

technologies have evolved significantly ad

developments such as service-oriented architecture

(SOA) and cloud computing have significant impact

of development of decision-making capabilities of

ERP systems (Uppström et al., 2015).

Service-orientation allows to decouple decision-

making logics from the core application what

improves flexibility of decision-making solutions.

Zarghami et al. (2012) proposes decision as service

to separate decision-making logics from core

processes because of specialized nature of these

components. An adaptive service regulation

architecture and a decision service template let both

synchronous request-response interaction and

asynchronous notification.

The decoupling of decision-making components

requires solutions for simplifying integration

between them and other applications including ERP

systems. Service-oriented architecture (SOA)

coupled with semantic web technologies (El-Gayar

and Deokar, 2013) facilitate information exchange

functions such as model publication, discovery and

use. The similar problems are addressed using model

exchange standards such as PMML (Guazzelli et al.,

2009). The PMML package exports a variety of

predictive and descriptive models from R to XML

for usage in other applications. Predictive models in

a form of services are proposed by Kridel and Dolk

(2013).

Cloud computing allows building distributed and

scalable decision-making solutions interacting with

ERP systems (Cardoso et al., 2016). The vehicle

routing application reported is able to perform

computationally intensive tasks and to gather data in

real-time from distributed sources such GPS devices

mounted on vehicles. Auer et al. (2013) investigate

orchestration of services using workflow

technologies as a foundation of ERP systems.

Specification of decision-making components using

domain specific languages allows development of

reusable components pluggable in different

enterprise applications (Brodsky and Luo, 2015;

Brodsky et al., 2015). Wei and Ma (2014) integrates

product configuration, production planning and

production execution on the basis of the ERP

system. The integration is enabled by using a unified

feature framework, which ensures information

integration among the components.

3 INTEGRATION SOLUTIONS

The review of related work suggests that four

integration approaches could be identified. These

categories are: 1) embedded; 2) external batch; 3)

external real-time; and 4) extended. The embedded

approach represents decision-making capabilities

implemented inside the ERP system. The external

batch approach implies that data from ERP systems

are sent to external decision-making applications

with or without a direct feedback loop to the ERP

systems. This corresponds to data integration. The

external real-time implies that decision-making is

performed by external components though decisions

are made as a part of integrated real-time business

process exchanging data with ERP systems. In most

cases, these three approaches treat decision-making

as general software components. In the case of the

extended approach, specific characteristics of

decision-making algorithms and models are also

Integration of Decision-Making Components in ERP Systems

185

Figure 2: A preliminary framework of technologies used specifically for providing decision-making capabilities in ERP.

systems.

taken into account and decision-making capabilities

are provided by such model-based components.

Table 2 allocates the paper reviewed in Section 2 to

the integration categories.

Table 2: Integration approaches used in literature.

Category

Source

embedded

[Aslan et al., 2012], [Borovskiy et

al., 2009], [Deokar and El-Gayar,

2013], [El-Gayar and Deokar,

2013], [Guazzelli et al., 2009],

[Kridel and Dolk, 2013], [Kurbel

and Nowak, 2013]

external batch

[Aslan et al., 2012], [Kridel and

Dolk, 2013], [Liu and Liu, 2010],

[Vidoni and Vecchietti, 2016]

external

real-time

[Cardoso et al., 2016], [Kurbel

and Nowak, 2013], [Uppström et

al., 2015]

extended

[Aslan et al., 2012], [Brodsky et

al., 2015], [Deokar and El-Gayar,

2013], [Kelle and Akbulut, 2005],

[Kurbel and Nowak, 2013]

These integration approaches can be implemented

using variety of technologies (for instance, Singh et

al. (2017) define various integration technologies as

a part of the reference architecture for integration

platforms). Figure 2 proposes a preliminary

framework of technologies used specifically for

providing decision-making capabilities in ERP

systems.

Embedded decision-making functionality is

implemented using internal development tools and

executed on application server. Built-in reporting

features (Online-analytical processing or OLAP)

also support decision-making and in-memory data

base technologies are increasingly used to expand

internal analytical capabilities of ERP systems

(Karduck and Chitlur, 2015). Data warehousing and

business intelligence with or without direct data

feedback to ERP processes are typical examples of

external batch integration approach. Similarly, APS

systems are primarily intended for batch integration

based on data exchange between the ERP system

and the APS. Integrated decision-making intensive

processes are typically developed using service-

orientation. Services are either invoked directly from

the ERP system or using an orchestration engine.

The extended approach is supported by a variety of

technologies, which are often specific to particular

decision-making methods, e.g., predictive analytics

or simulation. In this case, decision-making is

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preformed by an external component and specific

integration protocols are used to ensure data

interexchange and integrated process execution with

the ERP system.

The evaluation of integration approaches is

shown in Table 3. The scalability criterion describes

an ability of the decision-making component to deal

with computationally intensive problems. The

modifiability criterion is considered assuming that

decision-making logics requires frequent

customization and it is beneficial to separate it from

the rest of the application. The data latency criterion

indicates whether the decision-making component

operates with the most recent data from the ERP

systems. The embedded approach has the same level

of scalability as an ERP system itself and does not

have specific means for handling computationally

demanding algorithms. Modifiability is obscured

within code for transactions processing and

modification might lead to excessive testing of the

core part of the ERP systems. However, the

embedded approach uses the most recent data. The

external batch approach has medium level scalability

and modifiability because these are large scale

applications and specific decision-making

algorithms are not always easy to isolate. The

service-oriented systems and micro-service based

systems in particular are specifically tailored for

achieving scalability and modifiability. The

extended approach focuses on interfacing between

external decision-making components and ERP

systems and integration protocols ought to enable for

plugging-in appropriate decision-making

components when necessary, thus, facilitating

modifiability.

Table 3: Evaluation of integration approaches.

Approach

Scalability

Modifiability

Data

latency

Embedded

Low

None

External batch

Medium

High

External

real-time

High

Medium/

High

Low

Extended

Medium/Hig

High

Low

4 CONCLUSIONS

Decision-making capabilities of ERP systems are

analysed through the prism of application integration

resulting in four approaches for integration of

decision-making components in ERP systems.

Current technologies supporting implementation of

these approaches are identified and the approaches

are evaluated according to the scalability,

modifiability and data latency criteria.

The scalability is required because decision-

making components often rely on complex

computations. The modifiability is required because

decision-making logics often needs to be changed

during ERP implementation because it provides

competitive advantage. Additionally, decision-

making logics changes more often than the rest of

the application and might require different

development competencies. Data latency is

important for operational decisions but less so for

strategic and tactical decisions. The external real-

time approach emerges as suitable for providing

decision-making capabilities on ERP systems,

especially, for operational decisions. It is argued that

decoupling of ERP decision-making logics is

beneficial to support scalability and modifiability.

That also facilities using the best-of-breed approach

to selecting decision-making components without

relying solely on components provided by an ERP

vendor. However, existing technologies supporting

external real-time integration focus on technical

rather than logical integration where logical

integration is perceived as understanding of relations

among decision-intensive business processes and

decision-making components. The logical

integration is addressed in the external approach.

However, the external approach is often tailored for

specific decision-making methods and logical

integration is not considered specifically in the

context of ERP systems.

Thus, the paper identifies the further research

direction on generalized interfacing between

external decision-making components and decision-

intensive business processes supported by ERP

systems both at the technical and logical systems.

The integration method should support for easy

plugging-in of decision-making in ERP systems and

exploration of relationships between decisions made

and processes performed.

REFERENCES

Aslan, B., Stevenson, M., Hendry, L.C., 2012. Enterprise

Resource Planning systems: An assessment of

applicability to Make-To-Order companies.

Computers in Industry, Vol. 63, No. 7, 692–705.

Auer, D., Draheim, D., Geist, V., Kopetzky, T., Küng, J.,

Natschläger, C., 2013. Towards a Framework and

Integration of Decision-Making Components in ERP Systems

187

Platform for Mobile, Distributed Workflow Enactment

Services on a Possible Future of ERP Infrastructure.

Innovation and Future of Enterprise Information

Systems, 201–215.

Bahrami, B., Jordan, E., 2013. Utilizing Enterprise

Resource Planning in Decision-Making Processes.

Innovation and Future of Enterprise Information

Systems, 153–168.

Borovskiy, V., Zeier, A., Koch, W., Plattner, H., 2009.

Enabling enterprise composite applications on top of

ERP systems. In IEEE Asia-Pacific Services

Computing Conference, APSCC 2009, 492.

Brodsky, A., Krishnamoorthy, M., Menasce, D.A., Shao,

G., Rachuri, S., 2015. Toward smart manufacturing

using decision analytics. In Proceedings - 2014 IEEE

International Conference on Big Data, IEEE Big Data

2014, 967.

Brodsky, A., Luo, J., 2015. Decision Guidance Analytics

Language (DGAL) - Toward Reusable Knowledge

Base Centric Modeling. In 17th International

Conference on Enterprise Information Systems -

Volume 1, ICEIS, 67–78.

Cardoso, P.J.S., Schütz, G., Semião, J., Monteiro, J.,

Rodrigues, J., Mazayev, A., Ey, E., Viegas, M., 2016.

Integration of a real-time stochastic routing

optimization software with an enterprise resource

planner. Geographical Information Systems Theory,

Applications and Management, 124–141.

Catt, P.M., Barbour, R.H., Robb, D.J., 2008. Assessing

forecast model performance in an ERP environment.

Industrial Management and Data Systems, Vol. 108,

No. 5, 677–697.

Chou, D.C., Tripuramallu H.B., Chou, A.Y., 2005. BI and

ERP integration. Information Management &

Computer Security, Vol. 13, No. 5, 340–349.

Deokar, A.V., El-Gayar, O.F., 2013. On semantic

annotation of decision models. Information Systems

and e-Business Management, Vol. 11, No. 1, 93–117.

El-Gayar, O., Deokar, A., 2013. A semantic service-

oriented architecture for distributed model

management systems. Decision Support Systems, Vol.

55, No. 1, 374–384.

Guazzelli, A., Zeller, M., Lin, W., Williams, G., 2009.

PMML: An open standard for sharing models. R

Journal, Vol. 1, No. 1, 60–65.

Holsapple, C.W., Sena, M.P., 2005. ERP plans and

decision-support benefits. Decision Support Systems,

Vol. 38, No. 4, 575–590.

Karduck, A.P., Chitlur, S.S., 2016. Data driven decision

making for sustainable smart environments.

In Proceedings - 2015 11th International Conference

on Innovations in Information Technology, IIT 2015,

146.

Kelle, P., Akbulut, A., 2005. The role of ERP tools in

supply chain information sharing, cooperation, and

cost optimization. International Journal of Production

Economics, 93–94, 41–52.

Krenczyk, D., Jagodzinski, M., 2015. ERP, APS and

simulation systems integration to support production

planning and scheduling. In 10th International

Conference on Soft Computing Models in Industrial

and Environmental Applications, 451–461.

Kridel, D., Dolk, D., 2013. Automated self-service

modeling: Predictive analytics as a service.

Information Systems and e-Business Management,

Vol. 11, No. 1, 119–140.

Kurbel, K., Nowak, D., 2013. Customization of on-

demand ERP software using SAP Business by Design

as an example. Lecture Notes in Information Systems

and Organisation, Vol. 4, 289–297.

Linthicum, D.S., 2003. Next Generation Application

Integration: From Simple Information to Web

Services, Addison-Wesley Professional. Indianapolis,

Edition.

Liu, Q., Liu, G., 2010. Research on the framework of

decision support system based on ERP systems. In 2nd

International Workshop on Education Technology and

Computer Science, ETCS 2010, 704.

Meyr, H., Wagner, M., Rohde, J., 2015. Structure of

Advanced Planning Systems. In Stadtler, H., Kilger,

C., Meyr, H. (eds) Supply Chain Management and

Advanced Planning, Springer Texts in Business and

Economics, 99–106.

Moon, Y.B., Phatak, D., 2005. Enhancing ERP system's

functionality with discrete event simulation. Industrial

Management and Data Systems, Vol. 105, No. 9,

1206–1224.

Nikolopoulos, K., Metaxiotis, K., Lekatis, N.,

Assimakopoulos, V., 2003. Integrating industrial

maintenance strategy into ERP. Industrial

Management and Data Systems, Vol. 103, No. 3-4,

184–191.

O’Leary, D.E., 2008. Supporting decisions in real-time

enterprises: autonomic supply chain systems. Inf Syst

E-Bus Management, 239–255.

Russman, R., Seymour, L., Belle, V.J.P., 2017. Integrating

BI Information into ERP Processes - Describing

Enablers. In 9th International Conference on

Enterprise Information Systems, 241–248

Samaranayake, P., Toncich, D., 2007. Integration of

production planning, project management and logistics

systems for supply chain management. International

Journal of Production Research, Vol. 45, No. 22,

5417–5447.

Shiau, J., Tsou, Y., 2015. A decision support module for

ERP system under VMI collaboration. In IEOM 2015 -

5th International Conference on Industrial

Engineering and Operations Management, 1–7.

Singh, P.M., Sinderen, M.V., Wieringa, R., 2015.

Reference Architecture for Integration Platforms. In

IEEE 21st International Enterprise Distributed Object

Computing Conference, EDOC, 113–122.

Uppström, E., Lönn, C., Hoffsten, M., Thorstrom, J.,

2015. New implications for customization of ERP

systems. In Proceedings of the Annual Hawaii

International Conference on System Sciences, 4220.

Van Nieuwenhuyse, I., De Boeck, L., Lambrecht, M.,

Vandaele, N.J., 2011. Advanced resource planning as

a decision support module for ERP. Computers in

Industry, Vol. 62, No. 1, 1–8.

ICEIS 2018 - 20th International Conference on Enterprise Information Systems

188

Vidoni, M., Vecchietti, A., 2016. Towards a reference

architecture for advanced planning systems, ICEIS

2016 - Proceedings of the 18th International

Conference on Enterprise Information Systems, 433.

Wei, J., Ma, Y.-S., 2014. Design of a feature-based order

acceptance and scheduling module in an ERP system.

Computers in Industry, Vol. 65, No. 1, 64–78.

Zarghami, A., Sapkota, B., Eslami, M.Z., Sinderen, V.,

M., 2012. Decision as a service: Separating decision-

making from application process logic. In Proceedings

of the 2012 IEEE 16th International Enterprise

Distributed Object Computing Conference, EDOC

2012, 103.

Integration of Decision-Making Components in ERP Systems

189