# Investigating the Challenges and Opportunities for Production Planning and Control in Digital Lean Manufacturing

Daryl John Powell, Eirin Lodgaard, Heidi Dreyer

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Daryl John Powell, Eirin Lodgaard, Heidi Dreyer. Investigating the Challenges and Opportunities for Production Planning and Control in Digital Lean Manufacturing. IFIP International Conference on Advances in Production Management Systems (APMS), Aug 2020, Novi Sad, Serbia. pp.425-431, 10.1007/978-3-030-57997-5_49. hal-03635633

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Distributed under a Creative Commons Attribution 4.0 International License
Investigating the Challenges and Opportunities for
Production Planning and Control in
Digital Lean Manufacturing

Daryl Powell¹,²; Eirin Lodgaard¹ and Heidi Dreyer²

¹ SINTEF Manufacturing, Raufoss, Norway

² Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology, Trondheim, Norway

{daryl.powell; eirin.lodgaard}@sintef.no
Heidi.c.dreyer@ntnu.no

**Abstract.** Digital Lean Manufacturing has emerged as a new approach to Lean Production, combining lean thinking and practice with the new opportunities presented by innovative digital technologies and Industry 4.0 concepts. However, this combined approach also raises certain challenges for the manufacturing industry. In this paper, we explore both the challenges and opportunities presented to manufacturers in light of digitalization *contra* Lean Manufacturing, with a specific focus on Production Planning and Control. Drawing on insights from four diverse explorative industrial cases studies, we identify the challenges and opportunities experienced by manufacturers embarking on a journey towards Digital Lean Manufacturing and highlight important avenues for further research.

**Keywords:** Lean Production, Digitalization, Production Planning and Control.

# 1 Introduction

A recent trend in operations management is digitalization and a shift towards Industry 4.0, which is set to dominate the next frontier of operational change and improvement in the manufacturing industry [1]. As such, this has created a so-called lean-digitalization paradox [2] and has even raised the question as to whether digitalization contradicts lean and indeed if digitalization will replace lean [3]. Certainly, in some cases, digitalization may indeed begin to counteract the application of lean, for example when decision-making becomes more centralized in information systems, as opposed to the decentralized and autonomous decision-making principles of lean thinking. However, current research has illustrated that lean thinking and practice is still very much here to stay as a dominant manufacturing concept contributing to efficiency and performance improvements, and that digitalization can behave as an enabler and catalyst for Lean Production [4]. An example is the application of digital algorithms on production planning decisions based on sensor technology and real time ordering and demand data. This is, in fact, in line with previous research that investigated the role of information
and communication technology (ICT), specifically enterprise resource planning (ERP)
systems in lean transformations [5].

The concept of Digital Lean Manufacturing (DLM) has emerged in response to this
debate [6]. DLM is realized when traditional lean methods gain a new digitally-enabled
edge [7, 8]. However, the integration of digitalization and lean thinking is a two-sided
coin. Adopting a limited view of digitalizing lean practices in isolation rather than con-
sidering also the change processes and application of lean thinking to digital transfor-
mations, risks simply digitalizing unnecessary activities, leading to digital waste [7]. In
this paper, we explore the challenges and opportunities that arise during the integration
of Lean Production and digitalization with a particular focus on Production Planning
and Control (PPC) processes (strategic, tactical and operative).

## 2 Theoretical Background: Beyond the Lean Vs. ICT Paradox
- The Emergence of Digital Lean Manufacturing

Production planning and control is a key mechanism in lean manufacturing, since plan-
ning puts the organization in a position where future demand can be met with a lean
approach to better utilize resources and capacity. Supported by digitalized planning so-
lutions mitigates uncertainty by providing information for better decision-making. Alt-
hough in some instances considered an enabler for lean production, planning is other-
wise strongly challenged by lean principles, since lean makes rigid planning highly
sensitive to disturbances [9, 10], in particular variability in supply and demand. For a
competitive environment this contradiction is emergent and the role of digitalization in
a lean manufacturing setting must be further explored.

Though earlier publications identified Lean- and ICT-based approaches to produc-
tion planning and control as contradictory [11-13], the more recent scientific literature
presents both (therein specifically the integration of) as enablers of competitive ad-
vantage since digitalization promises to positively impact on flexibility and capacity
utilization [5, 14]. This is an important development in thinking with regards to the
contemporary debates around the contradictory or complementary nature of lean and
digitalization – and suggests that we must once again revisit the Lean-ICT Paradox [15]
in order to exploit potential novel concepts from the paradox [16].

[17] posed the question as to whether lean and ICT were complementary or contra-
dictory in nature. Exploring this challenging issue, [18, 19] explored the support func-
tionality of Manufacturing Execution Systems (MES) and Enterprise Resource Plan-
ning (ERP) Systems for Lean Production, respectively. Exploring the concurrent appli-
cation of lean and ERP through action research, [5] proposed an ERP-based Lean im-
plementation process – suggesting that the ERP implementation acted as a catalyst for
the case-company's lean transformation. [20] also explored the support functionality
offered by ERP systems for pull production, using multiple case-study research.

Given the complementary nature of contemporary ICT solutions and Lean Produc-
tion, [6, 7] proceed with presenting both conceptual and practical insights into the com-
plementary nature of Lean and Digitalization – rather than dwelling on the debate as to
whether the two paradigms can co-exist or not. As such, [6] discusses Industry 4.0
technologies as enablers of leaner production, while [7] coins the term *Digital Lean Manufacturing*, and subsequently extends the focus beyond production planning and control to also include total quality management (TQM) functions, such as *Jidoka 4.0* [21] and *Quality Management (QM) 4.0* [22].

As a final theoretical discussion, [1] presents and discusses the managerial challenges associated with lean and digitalization, classifying the *Digital Lean Landscape* in terms of a set of paradoxes within organizational design, supply chain planning, decision systems and supplier relationships. As such, these important research themes represent the structure for this investigation.

## 3 Research Design

This paper presents preliminary results from the initial stage of a four-year research project. To fully understand and gain a deep insight into the production planning and control processes of the digital lean manufacturing concepts applied by manufacturing companies, the research design is based on a theory-building case study approach [23]. The unit of analysis is the production planning and control process at strategic and tactical levels, which has been explored by the research question: *What are the challenges and opportunities for Production Planning and Control in Digital Lean Manufacturing?* Aggregated planning is particularly interesting in a DLM context, since the long-term planning horizon absorbs uncertainty and sets more robust direction for lower level planning.

Given the what-type research question [24], we chose to adopt a multiple case study research design and to draw useful insights from the results of semi-structured interviews with representatives from four industrial case companies (for an overview, see Table 1.). In addition, information from two workshops with the four case companies has contributed to contextual insight about the planning and control process. Data from the interviews was compiled in a report and triangulated with other sources, such as company documentation and follow-up discussions. The data has been analyzed according to the constructs *planning challenges* and *digital opportunities* (for planning).

<table><caption>**Table 1.** An overview of the case companies and interviewees.</caption><thead><tr><td>Case</td><td>Industry</td><td>Interviewee</td></tr></thead><tbody><tr><td>1</td><td>Automotive</td><td>Project manager – lean responsible</td></tr><tr><td>2</td><td>Oil and Gas</td><td>Chief Operations Officer (COO) – lean responsible</td></tr><tr><td>3</td><td>Construction</td><td>Human Resources (HR) manager – lean responsible</td></tr><tr><td>4</td><td>Aluminium</td><td>Project manager – lean responsible</td></tr></tbody></table>

### 3.1 Case 1: Automotive

Lean has been the main management model in Case 1 for several years. PPC at Case 1 is largely driven by input from customers and forecasted expectations of sales and market development as well as strategic priorities over a five-year horizon, which then
provides the basis for making plans for production, distribution and procurement. In forecasting and planning, various digital planning tools are used, such as ERP and MES. These systems support the planning processes of the various functions at different levels in the organization (strategic, tactical, operational).

Takt-time and capacity are important tactical planning constraints. Planning meetings are conducted in order to consider available resources, equipment, and materials. One challenge in particular is that suppliers have different response times for different requirements which directly affect the inventory and safety stock level. Demands for reduction in inventory and varying response time from the suppliers lead to greater uncertainty in the planning environment and vulnerability in relation to the level of delivery precision. As a countermeasure, the Industrial Internet of Things (IIOT) and supply chain connectivity present an interesting opportunity for Case 1 concerning more advanced analytics about demand and supply, and involvement of suppliers and customers in planning.

## 3.2 Case 2: Oil and Gas

Case 2 processes over 400,000 work orders through its base stations each year, for example for material supplies and maintenance equipment to multiple installations geographically spread. A substantially part of the flow through the base stations are specialized engineer to order material and equipment, delivered on JIT premises. Therefore, the planning and management of supply, operations and demand at base stations presents a grand challenge for Case 2 (the base stations are the central hubs of the value chain that link on-shore and off-shore installations). As such, the PPC task is complex, and the bases are required to coordinate both inbound and outbound material- and information flows from- and to its facilities off-shore, its external suppliers, and its logistics providers. In addition, the base stations serve as (intermediate) consolidation and storage points for equipment and materials. Therefore, effective flow, interaction and coordination in and between base stations presents a key challenge, whereby digitalization can provide a solution in the form of more integrated digital planning.

## 3.3 Case 3: Construction

Case 3 is an engineer-to-order (ETO) / project-based producer, providing systems to the oil and gas industry. As such, the customer's product specifications intervene "deeply" into the company's upstream processes, i.e. in or before engineering and includes the sub-suppliers. This creates a completely different planning environment to the one which is typically found in the traditional commodity manufacturing industry, where demand uncertainty is usually mitigated through the production and storage of standard products. The ETO environment is therefore surrounded by significantly greater uncertainty related to, among other things, lead times, delivery reliability, access to specialized engineering expertise / capacity / resources, etc. This uncertainty also propagates further down the value chain to suppliers. Coordination, integration, planning / management of the processes in these types of organizations and the utilization / role that digitization can have, for example in connection with information
capture, the sharing of information between decision steps and levels, product config-
urators / bill-of-materials / catalogs, organization, integration with suppliers and cus-
tomers, etc., are critical elements that can greatly affect profitability and competitive-
ness.

**3.4 Case 4: Aluminium**

Case 4, a producer of aluminum, has developed and implemented an advanced digital model to plan and allocate resources in relation to demand / order requirements. The model is mainly used for the European region and has an accuracy of about 80%, i.e. the inaccuracy of 20% is relatively significant, which in turn has implications for the quality of planning and a need to build capacity (storage, production, transport, etc.) to maintain a high level of delivery precision. The company could benefit further from an analysis of the digital model and its subsequent planning process, as well as the integration of a Big Data analytics module in order to uncover barriers and potential "digital waste" and mitigate uncertainty in Production Planning and Control.

4 Discussion

The aim of this paper was to investigate the research question: *What are the challenges and opportunities for Production Planning and Control in Digital Lean Manufacturing?* Results from the multiple case-analysis is summarized in Table 2 and will be discussed below.

<table><caption>**Table 2.** Cross-case analysis.</caption>
   <thead>
    <tr>
     <td>
      Case
     </td>
     <td>
      Production planning challenges
     </td>
     <td>
      DLM opportunities
     </td>
    </tr>
   </thead>
   <tbody>
    <tr>
     <td>
      1
     </td>
     <td>
      Planning uncertainty caused by varying supplier lead times at the same time as reducing stock levels
     </td>
     <td>
      Supply chain connectivity by Industrial Internet of Things (IIOT)
     </td>
    </tr>
    <tr>
     <td>
      2
     </td>
     <td>
      Complex supply and demand planning for JIT operations
     </td>
     <td>
      Integrated digital planning
     </td>
    </tr>
    <tr>
     <td>
      3
     </td>
     <td>
      Planning of ETO orders with high uncertainty caused by poor customer specification
     </td>
     <td>
      Integrated digital production and supply chain planning
     </td>
    </tr>
    <tr>
     <td>
      4
     </td>
     <td>
      Complex production network planning causing low planning accuracy
     </td>
     <td>
      Exploiting advanced analytics/Big Data technology in network planning
     </td>
    </tr>
   </tbody>
  </table>

The research resulted in the identification of challenges and opportunities for PPC
in DLM, specifically intra- and inter-organizational integration (with respect to material
and information flows). The planning environment in the cases is characterized by un-
certainty and complexity, consisting multiple units and their interdependency, and var-
iability in demand and supply which challenges lean management of operations. Criti-
cal elements of DLM identified in the cases are the access to and sharing of information
for integrated planning and decision support across functions and between customers
and suppliers. Next, the results identify the role DLM might have on improving pro-
cesses and driving change management by the strong emphasis on integrated planning
and connectivity in the cases. Further, the cases identify the complexity and systemic
component of the planning and control process as critical elements in DLM, but also
the potential benefits and novelty coming from investigating the paradox of DLM. We
consider this to represent both the fundamental challenge and opportunity for PPC in
DLM – traditional lean supply chain practices can certainly be enhanced by novel dig-
ital solutions such as IIoT and Big Data analytics.

5 Conclusion

By considering the challenges and opportunities for PPC in DLM, it appears that lean
paves the way for successful digital transformation and digitalization enriches lean
practices. From the results of this investigation, it appears that the combination of lean
with digital solutions certainly promises to enable lean thinking to be extended beyond
company borders and out into the supply chain. As such, we suggest that further re-
search should investigate *Digital Lean Supply Chains* in more detail.

Acknowledgements

The authors acknowledge the support of the Norwegian research project *Lean Digital*
and the Norwegian research program *SFI Manufacturing*.

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