How to audit SCRM? Conducting the Audit (6/9) – List of questions (part a/c)

Below is a list of questions that can be used to audit the SCRM, concerning the topicsTransparency of supply chain structures and processes, Information and dependencies of suppliers and Identification.

Transparency of supply chain structures and processes Are the most important, value-creating corporate processes defined (e.g. development to production to sales)?
  Is there accountability in these operational processes, i.e. are the potential risks and their impacts on different departments known and addressed?

Information and dependencies of suppliers

Is there a list of all direct upstream suppliers?
  Is the most important company data of the upstream suppliers documented (corporate headquarters, production facilities, local contact persons, cell phone numbers, etc.)?
  Are the supplier contacts with decision-making authority known?
  What are all of the value creation processes of the direct upstream suppliers?
  What are the dependencies between upstream suppliers?
  Have they been properly identified?
  Is information about the suppliers obtained on a regular basis?
  Who are the most critical suppliers (critical suppliers can be characterized as the highest proportion of sales, or as the supplier of the material for the most products which cannot be easily replaced, etc.)?
  If the most critical supplier fails, what are the financial consequences?
  How often does the operational business check whether certain deadlines have/will expire?
  How often are the supply contracts checked to see if they need to be transferred to a new company standard?
  Is information about suppliers regularly shared with other departments?
  Does an on-site visit of the most critical suppliers take place every three to five years?
  Is there a structured guidelines in place for communicating with suppliers?

Identification

Are operational supply chain risks systematically identified at regular intervals?
  Are strategic supply chain risks systematically identified at regular intervals?
  Is there a catalog for the systematic identification of supply chain risks?
  Are external as well as internal corporate risks considered during the identification of risks?
  Are the interfaces with supply chain actors considered during risk identification?
  Is it always possible to add newly identified supply chain risks to the catalog?
  Are the results of the supply chain risk identification from each individual workplace recorded in writing?
  Are the results of the supply chain risk identification from the entire department recorded in writing?
  Are risks from supply chain partners that may have a negative impact on the company considered in the identification process?
  Is the identified supply chain risk list up-to-date?
  Is the operational supply chain risk assessment complete?

Extract from Schröder, M. (2019): Structured improvement of supply chain risk management. In: Supply Chain Management – Contributions to Procurement and Logistics, Series-Editor: Essig, M.; Stölzle, W., Kersten, W., Springer Gabler: Wiesbaden

How can supply chain risk management be implemented?

When introducing SCRM, organizational, technological, and personnel aspects should be taken into account. At the same time, structural aspects should be aligned with the individual phases of the SCRM process—risk identification, analysis, management, and control (process). Method catalogs were created as a further component

Relevant Aspects  
Personal
  • Awareness of SCRM should be raised among employees
  • Heterogeneous team composition is advantageous (i.e. representatives from purchasing, supply chain management, IT, quality management, etc.)
  • Team members must have sufficient capacity (available working hours)
Organization
  • Integration of SCRM into existing units (e.g., Purchasing, Global Distribution Fulfillment)
  • Support of the project by management
  • Appointment of a project manager who coordinates the SCRM process, collects necessary data/documents, and consolidates the results
  • Regular supplier evaluation—especially for critical suppliers. Clustering according to cash turnover is recommended
  • Complete documentation (e.g. defective rate, special releases, delays, etc.)
  • Regular exchange of information with suppliers such as forecasts, ERP system information, etc.
IT
  • SCRM process support from an IT system
  • Integration into existing IT systems (e.g. ERP) and access to the same data sources (e.g. sales and purchasing) can be advantageous
  • Conducting audits to identify supplier weaknesses

For the SCRM implementation process, the first step is to raise awareness among employees. Internal company events and attendance at specialist conferences or external training events on this topic are, for example, suitable for this purpose.

In addition, a heterogeneous team composition is ideal. If, for example, employees from purchasing, supply chain management, IT, and quality management work together on the SCRM team, a cross-departmental exchange of information is ensured. Additionally, the hierarchical and functional composition of the SCRM team must be considered.

In general, it must be ensured for the implementation process that the team members are motivated and have available capacity (working hours) so that the employees involved do not see the implementation of an SCRM system as an additional workload.

Furthermore, an SCRM team leader should be appointed to coordinate the SCRM process, collect the necessary data or documents, and consolidate the results so that continuous processing of the SCRM is ensured. The associated shift of decision-making authority to the SCRM team is also critical to performance success. Management support for the SCRM is particularly critical here.

From an organizational perspective, a decision must be made at the start of implementation as to whether the SCRM should be integrated into the existing organization or whether a restructuring should be sought. It should be noted here that, particularly in the case of SMEs , integration into an existing department is seen as advantageous. In addition to an increase in the acceptance of SCRM-related measures by other employees, a better exchange of information from this step can be guaranteed.

Furthermore, regular supplier evaluations, especially for critical suppliers, (e.g. clustering by sales) should be integrated into the implementation process, accompanied by complete documentation on aspects such as error rates, special approvals, delays, etc. A continuous exchange of information with suppliers (e.g., via forecasts or ERP system) helps to identify possible failure risks at an early stage.

In terms of technological implementation, the SCRM process should be supported by an easy-to-use IT system; however, isolated solutions should be avoided here. Access to the same data sources by different departments, such as sales and purchasing, also promotes an exchange of information. Associated reporting is also critical for SCRM success. The frequency of reporting, the volume of reports, and the specified group can promote or hinder the SCRM process.

Excerpt from Kersten, W.; Feser, M.; Schröder, M. (2013): Situationsadäquate Implementierung eines Supply Chain Risk Managements, Bundesvereinigung Logistik e.V. (BVL) – Schlussbericht des geförderten Vorhabens 17234N.

Changes in Risk Management via Big Data

The meaningful and beneficial evaluation of large amounts of unstructured data is the next important step for effective risk management as a whole to take. This challenge, along with several other new, pertinent challenges, will be briefly summarised below (Rogers 2017): 

  • The integration of Big Data into the risk management process will be further expanded in the future. Thus, both the accessibility and validation of the data and the use of corresponding analysis and evaluation tools will play a central role. 
  • Within the scope of risk identification, preliminary considerations should therefore be made to address questions such as “Who feeds the data?”, “How can the timeliness, completeness and compatibility of the data be ensured?”, and “How can data quality be guaranteed? 
  • It may also be necessary to adapt customized procedures in order to use limited resources sparingly: for example, it is advisable to first define the goal of data analysis (e.g. predicting the risk of Ebola infection) instead of trying to draw as many evaluation options as possible from an available data set without a specified goal in mind.
  • For better, more extensive data availability in the future, risk management must be geared more strongly towards interdisciplinary cooperation within companies. At the same time, as shown above, a multitude of departments may benefit from the evaluation of the results. 
  • For data processing, the correct IT tools–Amazon Elastic MapReduce, Microsoft Azure Cortana Analytics Suite–must be used to efficiently identify the required information (e.g., implementing machine learning and artificial intelligence).
  • However, the continuous analysis of unstructured data cannot be mastered by IT tools alone; the support of experts, i.e. data scientists, who perform technical data analysis and provide decision assistance is also necessary. This includes, among other things, a manual cleansing of raw data to increase data quality and the programming of algorithms for the automatic use of real-time data.
  • The increased emphasis on data analysis in risk management will thus lead to a division of responsibilities between data scientists and risk managers.
  • In the future, one of the risk manager’s core tasks will be to consider the results of data analysis as a forecasting aid in management decisions. 
  • The primary tasks will consequently become more data-driven, and, as a result, the demands on the qualifications of risk managers will also change.
  • The automated research and evaluation of real-time information will lead to a reduction in the manual activities of the risk manager. This leaves more time for analytical and strategic tasks, i.e. medium and long-term solutions can be developed based on the results of Big Data Science (Al-Khazrage 2018, p. 58). 

It should be noted that the use of Big Data in risk management is associated with various outcomes. In order to prepare for these outcomes, companies should–depending on their resources–initiate appropriate measures at an early stage. 

Excerpt from Schröder et al. 2019, Neue Anwendungsmöglichkeiten für Risikomanagement durch die Einsatz von Big Data – Zwei Fallbeipspiele, in: Schröder, Meike; Wegner, Kirsten (eds.) Logistik im Wandel der Zeit, Springer: Wiesbaden, pp. 121-136.

 

MBP 15/16 Measures and Best Practices for “Communication”

“The reporters stood outside our doors with microphones and cameras. By this point we had learned, to a certain extent, how to handle this internally–by having everyone “Please keep their mouths shut”. […] What if, for example, one of the very top corporate officers dies in a plane crash? Such an event is very specifically regulated here.” (Interview – Managing Director Food and Retail)

The design of communication is another factor in the success of SCRM. In addition to risk reports and reporting, associated internal and external communication can also influence the success of SCRM.

In the numerous expert interviews and focus groups with company representatives and scientists for the development of the maturation model, the following measures were identified:

  • Define procedures for the frequency and scope of SCRM-related communication. 
  • Formally establish meeting minutes to record relevant details.
  • Ensure that employees are largely aware of the internal communication process.
  • Outline the expectations of internal communication within the department and link this with aspects of the internal reporting process.
  • Ensure that the communication process is both bottom-up and top-down.
  • Use a risk management information system to facilitate communication as well as the documentation of SCRM.
  • In addition to internal communication, also formally regulate the process of external communication (for example, with supply chain partners, authorities, etc.) and ensure that this system is understood by all relevant employees.

Extract from Schröder, M. (2019): Structured improvement of supply chain risk management. In: Supply Chain Management – Contributions to Procurement and Logistics, Reihen-Hrsg.: Essig, M.; Stölzle, W., Kersten, W., Springer Gabler: Wiesbaden

 

Suche in OpenEdition Search

Sie werden weitergeleitet zur OpenEdition Search