Effectively implement requirements of the new German law on corporate due diligence in supply chains

Integration of MBI CONIAS data into the VertiGIS solution

Supply chain visibility with MBI CONIAS Risk Intelligence Data

On June 11, 2021, the German parliament passed the “Act on Corporate Due Diligence in Supply Chains”. The new Supply Chain Act obliges companies above a certain size to better meet their responsibilities in the supply chain with regard to respecting internationally recognized human rights. It will be binding for companies with more than 3,000 employees from January 1, 2023, and for companies with more than 1,000 employees from 2024.

New law demands transparency and risk management along the entire supply chain

Many companies perceive the new Supply Chain Act as a major challenge: It requires transparency and risk management along the entire supply chain and, at the same time, special knowledge about the status of human rights violations and environmental offenses on site. Failure to comply with the new requirements on minimum social and environmental standards within the supply chain could result in loss of image, loss of sales, fines and exclusion from federal procurement procedures.

The upcoming law confronts companies with new tasks and obligations for which there is often too little in-house expertise. Risks have to be identified, analyzed and appropriate measures taken. The lack of transparency within fragmented supply chains in particular makes risk management difficult for companies. Obtaining data involves a great deal of effort and assessing the situation is associated with great uncertainty.

Solution for the analysis and visualization of risks supports risk minimization

This is where the joint approach of MBI and the VertiGIS companies comes in. MBI CONIAS data is integrated into the risk management and business continuity solution of VertiGIS. This provides an effective and globally applicable solution that enables the analysis and visualization of risks along the entire supply chain. Risks can be identified, evaluated and suitable countermeasures can be taken. In this context, indicators and further information on the human rights situation as well as the environmental situation can be shown for locations worldwide, risks can be anticipated and mitigated through appropriate measures.

CONIAS has its origins in the early detection of conflicts: This means that it not only shows where there currently are violations of the Supply Chain Act, but also where human rights violations and climate damage measures are improving or worsening. This creates transparency in the supply chain and sustainability is already achieved in the procurement process. The CONIAS data is continuously updated. In the event of changes in the characteristic values, users are informed in detail and measures are recommended. Risks can be reduced or avoided altogether through foresighted risk assessment and adequately coordinated catalogs of measures.

The detailed article, published in the VertiGIS [email protected] magazine 2021, is available in German here. For further information, please contact our Sales Team.

share

The assessment of political risks – Orientation and security through MBI CONIAS Risk Intelligence

It’s a paradox: Political risks, including wars and political violence, are consistently ranked among the biggest risk factors for business managers[1]. Supply chains can be disrupted, inventories can be destroyed, sales markets can disappear. Nevertheless, the area of early detection and warning of political risks receives little attention from internationally operating companies. It is often assumed that crises and wars are too complex to be effectively predicted – but the scientifically based CONIAS approach was developed for precisely that purpose. One of the basic methods used to understand and more quickly classify the multi-layered risk situations is pattern recognition[2].

Pattern recognition is derived from general human approaches

For the complex field of political risks, pattern recognition is so well suited because it closely resembles general human behavior. An example of this is the following scenario: Two people, 20 and 50 years old, start their new job in a small company with ten employees on the same day. While the younger of the two tends to be quiet and reticent about the new situation, acting rather defensively and preferring to listen rather than speaking himself, the older one benefits from many years of professional experience and several job changes. Having experienced this situation many times before, the older person can therefore better and more quickly assess people he encounters in the new situation. He compares their behavior, their body language, the sound of their voice, but also their position with people he met on earlier “first days at work”. In doing so, the older person recognizes patterns that give him orientation in the new situation and derives conclusions for his behavior.

The MBI CONIAS database records non-violent early phases and other conflicts

People make use of pattern recognition – no matter whether through their own experience or through experience acquired through telling or reading – and thus orient themselves in new situations.  The CONIAS approach and the CONIAS database are also committed to this idea. Unlike conventional conflict databases, which only record wars or violent phases of conflict, the CONIAS database also records the non-violent early phases of these later wars[3]. In addition – and this is what makes the CONIAS approach so special – other conflicts that begin similarly to later wars but ultimately take a peaceful course are also recorded. Only in this way is it possible to make statements about the vulnerability of certain conflict constellations. This can be explained as follows: It is true that a large proportion of the few interstate wars since 1945 have been fought over territory. Examples include Iraq’s invasion of Kuwait (1991) or the conflict between Armenia and Azerbaijan over the Nagorny Karabakh region (2020). Nevertheless, conversely, it would be wrong to say that territorial or border disputes lead to war particularly frequently. Currently, there are about 120 recorded border disputes between states, almost all of which are settled without violence only at the diplomatic level. Other sources speak of an even higher number of unresolved border disputes[4].

Only a comprehensive collection of data allows to properly assess the risk potential of border disputes

In total, the CONIAS conflict database contains information on the course of more than 1,900 intra- and interstate, violent and non-violent conflicts since 1945. A large number of indicators are recorded for each conflict and actor involved, reflecting all dynamic changes in conflict resolution, but also in the socio-economic environment[5]. Thus, the CONIAS database provides millions of data points supplying statistical information on global conflict behavior. One of the most important findings of empirical conflict research can also be confirmed by CONIAS: Democracies do not wage wars against other democracies[6]. We have already integrated this “law” of democratic peace into our thinking to such an extent that, for example, even the most severe low blows in bilateral relations between Germany and the U.S. did not cause any fear of war even among the greatest pessimists.

Especially in areas not illuminated by other conflict databases, the CONIAS database reveals more points of reference

The database has shown, for example, that culturally driven conflicts have become significantly more important since the end of the Cold War in 1990 and especially after 9/11/2001[7]. At the same time, however, the CONIAS database shows that over time, it is not the number of different religions in a country that makes it vulnerable to intrastate violence, but the number of different languages spoken in the country[8].

The CONIAS conflict database is continuously maintained, and current conflict events continue to be recorded. Every quarter, knowledge about the evolution of conflicts around the world grows by tens of thousands of data points. Currently, the CONIAS team is working to better understand the links between political conflicts, human rights violations, and damage or destruction to natural livelihoods. The new supply chain law, as well as an ever-growing sense of responsibility for human rights and the environment, requires companies and ultimately every individual to act carefully in this regard. We would be pleased not only to provide you with points of reference, but also to support you with our comprehensive know-how and long-standing expertise. If you are interested, please contact our Sales Team.

About the author:
Dr. Nicolas Schwank
Chief Data Scientist Political Risk
Michael Bauer International GmbH

References:
[1] Allianz (Ed.): Allianz Risk Barometer, Various Years. Last 2021
[2] Trappl, Robert (Ed.) (2006): Programming for peace. Computer-aided methods for international conflict resolution and prevention. Dordrecht: Springer; Schrodt, Philip A. (2000): Pattern Recognition of International Crises Using Hidden Markov Models. In: Diana Richards (Ed.): Political complexity. Nonlinear models of politics. Ann Arbor: Univ. of Michigan Press, pp. 296.
[3] Schwank, Nicolas (2012): Konflikte, Krisen, Kriege. Die Entwicklungsdynamiken politischer Konflikte seit 1945. Baden-Baden: Nomos (Weltregionen im Wandel, 9); Schwank, Nicolas, et al. “Der Heidelberger Ansatz Der Konfliktdatenerfassung.” Zeitschrift Für Friedens- Und Konfliktforschung, vol. 2, no. 1, 2013, pp. 32–63.
[4] https://www.cia.gov/the-world-factbook
[5] Schwank, Nicolas (2012): Konflikte, Krisen, Kriege. (vide supra)
[6] Small, Melvin; Singer, J. David (1976): The war-proneness of democratic regimes, 1816-1965. In: The Jerusalem journal of international relations.  1 (4), pp. 50–69.
[7] Croissant, Aurel (2009) et al.: Kulturelle Konflikte seit 1945. Die kulturellen Dimensionen des globalen Konfliktgeschehens. 1st edition. Baden-Baden: Nomos (Weltregionen im Wandel, 6). Stiftung, Bertelsmann (2010): Culture and Conflict in Global Perspective. The Cultural Dimensions of Global Conflicts 1945 to 2007. Guetersloh: Verlag Bertelsmann Stiftung.
[8] Ibid.

share

Location Intelligence in Retail

When making strategic business decisions, retailers can rely on location intelligence to gain valuable insights on the market, competitors and most importantly consumers’ interests and preferences. By putting that data to work, retailers can better understand consumer behavior and purchasing patterns and therefore improve business results and customer experience. For critical business decisions like expansion or supply chain planning, location intelligence supports well-founded decision making.

Before taking market entry decisions, location data can support the analysis of market opportunities and competition. When entering a new market, various aspects have to be taken into consideration. For the analysis of the location, data on visitors, their movement patterns, whereabouts before and after the visit and duration of stay provide valuable insights into the customer journey. When analyzing the competitive strength, visits and frequency as well as customer loyalty to competitors’ stores are important factors besides competitors’ market share. To get a better understanding of consumers, socio-economic data as well as consumer styles play an important role. With this knowledge, retailers can offer attractive products and services and even poach their competitors’ less loyal customers.

When communicating with consumers, personalization and individualization are key and can significantly enhance customer experience. By utilizing MBI’s data on movement and buying patterns, retailers can better understand interests and preferences of consumers and therefore deliver relevant communication in a targeted manner. Moreover, these insights into consumer behavior can be used to improve the performance of marketing campaigns with for example relevant deals and offers for the target audience. Especially in light of the current pandemic, there’s an increase in demand for click & collect services, where consumers buy online to then pick their order up in-store. Here as well, location intelligence can enhance the shopping experience, for example through the suggestion of the closest store for pick-up. Overall, location intelligence makes it possible for retailers to understand the customer journey in more depth for a target group relevant implementation of marketing strategies to improve customer service and experience.

Another aspect that can be optimized with location data is personnel planning and staffing decisions. When analyzing the store visitors by weekdays and hours in relation to the sales and service staff, discrepancies can be revealed and staffing schedules optimized to match customer traffic. Because of COVID, shopping in-store has noticeably changed with consumers wanting to get in and out of shops as quickly as possible, concerned about their health and safety. In general, these changes in shopping behavior are expected to last even after the COVID pandemic is over. This development is increasing the relevance of store design concepts. With the movement patterns available through location intelligence, retailers can improve the layouts of their stores for a shopping experience that is fitted to the changing consumer behavior.

In conclusion, location intelligence can support strategic decision making with insights based on a data-driven approach in times of crisis, but also thereafter. Contact our Sales Team today to learn how you can leverage this data to improve business results as well as customer experience.

share

To Content To Menu