Gathering data and information in supply chains
The current pandemic has exposed a situation that, even with more data produced than ever before, companies in general do not have a good understanding of their supply chains. This includes risk exposure and alternative responses to supply challenges that may arise.
A company’s supply chains can consist of multiple businesses and assets, together with the flows of items, money, data and information between them. The more interconnected are the production and distribution network, the higher is complexity. The more complex an organisation’s supply chains, the more Uncertainty surrounds plans, outcomes and performance measures.
Uncertainty in an organisation’s Supply Network is generated through three elements:
- Complexity: built into processes, both internal (often management directed) and external
- External complexity is influenced by:
- Breadth: number of direct Tier 1 suppliers in the supply base
- Depth: number of Tiers of suppliers in each supply chain
- Geography: global spread of customers and suppliers
- External complexity is influenced by:
- Variability: in the patterns of demand and supply through supply chains, at locations and on individual machines
- Constraints: restrictions and interruptions in the flows of items, money, transactions and information moving through an organisation’s supply chains
These factors interact and amplify each other, which increases the frequency of disruptions, with unknown outcomes. To reduce Uncertainty requires the supply chain group in an organisation to evaluate and rank uncertainties, so they become structured risks. This is the Supply Network Risk Management approach.
Only when this approach becomes an integral part of management within a supply chain group can Supply Network Risk Management be implemented within a Digital Supply Network Map.
Digital Supply Network Map
The Digital Supply Network Map is a picture of your organisation’s supply network structure. This map joins the nodes and links of the network and shows the flows of items, money, data and information.
The early 1990s was the time when building models and enabling simulation of supply networks using IT applications commenced. However, the time required in modifying models and uploading data, then running simulations in batch mode, meant that to review a supply network was an exercise done maybe once or twice per year.
Jump forward thirty years and the limited computing capability that slowed the adoption of supply network mapping has disappeared. But, so have a number of software companies that developed the early mapping applications.
Now, the situation has arrived where businesses focused for the lowest cost, with dependency on sole suppliers and single countries, find this strategy carries risks. But changing the strategy could add to Uncertainty. This has provided an opportunity for commentators to talk about the need for businesses to map their supply chains.
But this is not using the old way – we should now adopt the Digital Twin approach! As we know, any new term needs to have the word ‘digital’ in front so that it appears ‘new’, but is digital twin new? Not really.
A well-established capability has been to construct a computer model of a physical operation (say a warehouse) and then input variable data to simulate various operational conditions. This has required three capabilities:
- Modelling: to build a descriptive and mathematical representation of an item or event
- Simulation: run a model to enable predictions and forecasts about how the system will work when subjected to different scenarios
- Predictive analysis: an element of Analytics that uses data (often called ‘big data’) within and between connected devices to enable decisions. This establishes the structure and rules for planning
The principles for modelling physical structures can be expanded to address multiple supply chains for an organisation (i.e. a supply network). So, a machine is replaced by a supplier or customer node and a conveyor by a transport link.
But, for the map to be a critical element in making reasoned decisions requires it to become a Digital Supply Network Map; that is a Digital Twin of the actual supply network. To be ‘digital’ requires that data and information are continuously available through links to physical data collection devices (sensors, RFID etc.) and other systems e.g. sales data at customers and supplier and 3PL ‘track and trace applications.
Using a Digital Supply Network Map
Planning supply chains is done over different horizons:
- Operations planning: factory planning and distribution planning – what will be made and delivered over the next week = ERP (most likely)
- Tactical planning: what will be made and delivered in the following months (longest lead time of materials) = S&OP
- Strategic planning: a longer time horizon that may extend for some years = Modelling and Simulation (digital twin)
The Digital Supply Network Map is applicable for tactical and strategic planning. However, ‘concurrent planning’ is a term to describe that although the operational and tactical plans are based on different models, the plans should be interoperable.
Now, given the explanation of why your organisation should implement Digital Supply Chain mapping, you may ask from whom the applicable application can be purchased. But not so fast – the biggest challenge when implementing Digital Supply Network Mapping is to identify the people in your organisation (or to hire) with an affinity for modelling and analytics.
To help find the people, an internal learning program can be structured that focuses on two main elements in mapping a supply network;
- A diagram structured to show the links between the organisation and tier 1 suppliers and the supplier’s suppliers, plus tier 1 customers and the customer’s customers. Document supplier and customer attributes
- A risk analysis of the Uncertainty applicable at the nodes and links of suppliers and customers, with a probability distribution to indicate uncertainty (the likelihood of occurrence and consequences if it occurs) at nodes in the network. This allows a simulation of various supply scenarios
To assist the learning, free software plug-ins to Microsoft Excel can be used:
LucidChart can be used to diagram a supply network using templates – value stream maps and process maps are provided.
RiskModel allows users to insert probability distribution functions that describe uncertainty about values within an Excel model. It then uses Monte Carlo simulation to automatically generate thousands of possible scenarios. Thanks to David Cobby who has recommended the free version for learning (the website has a good one-hour tutorial). See David’s comment.
Disruptions, such as that currently experienced, require investments in capabilities that give additional supply chain resilience. Time is required for modelling and simulation software to be understood, selected and implemented; then operated before the benefits can be measured – it is NOT an IT project. A positive return on investment (ROI) will therefore not be in the short term, but the investment in people and applications is necessary.