SUPPLY CHAIN ANALYTICS
Trusted Data are pioneering analytics in Supply Chain Transformation. Our supply chain solutions leverage AI and Machine Learning to offer clients data-driven decision capabilities, reducing their cost to serve and enhancing customer fulfilment.
Supply Chain Analytics Overview
With global supply chains bringing increased risk, complexity and competition, Trusted Data’s Supply Chain analytics solutions utilise advanced approaches to data science with a stern focus on unlocking working capital, reducing cost to serve and uplifting customer fulfilment with a targeted and measurable performance outcome.
Trusted Data have successfully delivered complex supply chain analytics solutions for clients, including demand forecasting, replenishment optimisation, location-based inventory optimisation, and ML-driven routing, scheduling and logistics network design.
Revenue & Sales Uplift
How to Increase Revenue with Supply Chain Analytics
Supply Chain Data and Analytics are key drivers behind higher revenue and increased profitability. The data and advanced predictive analytics approach for Supply Chain functions, helps uncover underlaying patterns and critical information.
Trusted Data’s supply chain analytics approach combines customer-level data such as frequency of replenishment, gross sales data, net sales data, wastage data, volume sold, product mix and other geograhical information about customers to design optimal supply chain predictive models, in order to uplift revenues, sales volume and profitability at different clusters, regions or specfic customer accounts.
Planning & Integration
What is Supply Chain Planning and Integration
Key Attributes of Supply Chain Planning: The planning aspect of Supply Chain involves raw materials, production, sales demand and other operational matters. Often the planning activities are dependent on inputs from other departments such as manufacturing, procurement, marketing, pricing and sales.
Aligning and Integrating Supply Chain: Often there are conflicting objectives between departments. For example, marketing wants to promote whilst production capacity is stretched and finally all the pressure is on Supply Chain to make that happen.
Role of Analytics in Supply Chain Planning and Alignment between Departments: Data Science using advanced analytics play a vital role in ensuring insights and data modelling can be utilised to establish alignment and integration between different and often conflicting departments.
Achieve Operational Efficiency through Supply Chain Data Modeling
Optimising Operational Efficiency and end-to-end inventory for raw materials and finished products, requires a very focused attempt to simultenously anticipate demand and supply variables. Inventory optimisation analytics is targeted to unlock working capital through determining a lower carrying cost.
Trusted Data achieve this for clients by identifying and modelling for:
1. Right safety stock levels, considering for stock turnover.
2. Variances caused by localised demand.
3. Customer replenishment cycles.
4. Propensity for inventory obsolescence by item and location, over time.
Reduced Cost Optimisation
What is Reduced Cost Optimisation in Supply Chain Analytics
Cost Reduction is a core KPI in Supply Chain Optimisation. Yes, often the dynamic nature of a business scenario is overshadowed by off-the-shelf solutions or best practices. Given that most business situations are unique – Trusted Data’s Supply Chain Analytics team excel at establishing key factors behind cost optimisation from the perspective of customer demand changes, product quantity, inventory balancing, logistics network re-engineering and through to sourcing.
Trusted Data’s cost reduction analytics include multidimensional end-to-end optimisation and robust data simulation along with business evaluation and effectiveness criteria.
Our data science team ensures that we achieve our promise of delivering a cost effective and optimised supply chain function.
Our Supply Chain Transformation Areas
Every supply chain organisation is different in respect of goals, data and context. we have helped leading companies transform their approach to Supply Chain Management by delivering solutions that fit each client’s context and needs.
Ai-driven Demand Forecasting
Most businesses face the supply chain planning question of “how best to Demand Forecast” at product, account or category level. With our specialism in Predictive Analytics in forecasting – Trusted Data advise clients on initial forecast design, acquiring the right data and to fitting the appropriate algorithms. We utilise both quantitative and qualitative methods with customised forecasting algorithms and techniques. We ensure your forecasts are error reduced and more robust than any software solution in the market.
Sales Forecasting in Supply Chain
There is a fundamental trade-off between forecasting sales and demand. The two are mixed up, however the reality of the matter is that sales forecasts are what retailers, wholesalers or even customers expect you to sell to them.
Whereas demand is more about what retailers sold to customers or customer off take or what is termed ‘consumption’. The two concepts are very different and can result in optimisation but with different outcomes for a Supply Chain function.
Trusted Data’s sales forecasting team help businesses to understand and define what might be the relevant strategy, including the impact of including sales or demand variables. Our expertise has helped clients to infer the right demand in order to supply the right quantities to their customer base.
How to Reduce Waste in Supply Chain
Many Supply Chain experts focus on waste reduction programs as through cost reduction strategies. The reality is that reducing waste internally (i-e factories, production lines, depots…) might help but wastage attributed from sold items is more harmful to revenue and profitability.
Reducing Waste should be viewed as a strategic supply chain process. At Trusted Data, we believe the Waste Reduction process begins with data. It includes exploratory analytics on all aspects of supply chain processes including associated lines such as manufacturing, sales, marketing and supported IT systems to collect and examine data with views to fitting robust models and algorithms to control your waste.
Optimal Replenishment Analytics
A Replenishment system or tool should be the last business priority. The fundamental question around replenishment is what, when and how much to replenish. Trusted Data help businesses establish this dynamically prior to designing an expert replenishment solution that is customised to unique business requirements and needs.
The second aspect of an effective replenishment tool is the degree of integration with other source systems such as sales, production, logistics, handhelds, ERP and other key software to either read or write into. Our replenishment analytics drive key outcomes such as higher sales, inventory turnover, reduce waste, low markdowns and maximise profits.
Minimise Overstocking | Understocking
Both aspects are costly to businesses. Understocking happens when your customer finds your shelves or online platform empty. The opposite is true for Overstocking when you over sell and stock more than the desired demand.
The underlying reasons could be many but major factors often link back to a lack of planning and inaccurate forecasts. The business impact of understocking is customer frustration, opening doors for competitors and a substantial loss of revenue.
Trusted Data’s analytics team have experienced many business scenarios of the above imbalance. Our rigorous methodological and analytical approach enables us to deep dive into data, at the customer level, and optimise that imbalance such that an optimal balance is attained and the dynamic movement of stocks ensures right product at right shelves at right time.
Lost Sales Optimisation
How to Measure and Optimise Lost Sales | Revenue | Missed Opportunities
The out of stock time (in hours, days, weeks) together with sales transactional data is central to quantifying the magnitude of lost opportunities. In addition to out of stock, excessive stock is also a major factor contributing to loss of revenue and sales. For example, comparing between 2 distinct accounts – an imbalance of both factors can lead to heavy loss of revenue and customer engagement.
At Trusted Data we do not just help clients with quantifying the size of lost revenue, lost sales or missed opportunities, but we effectively apply exploratory data analytics techniques to identify the causing and relational factors and then applying advanced analytical techniques to model the optimisation, such that we increase your revenue and sales through missed opportunity algorithms.
Product mix analytics
Product Mix Analytics
Trusted Data believes that businesses spend a lot more time and efforts on costs, prices, promotions and are less attentive to Product Mix Analytics. Often we hear terms like Product Mix Analysis to gain loose insights. Our Analytics team have proven capabilities in Product Mix identification and configuration. In our recent consulting work we have delivered both static and dynamic Product Mix Analytics for leading Retail, CPG and FMCG companies to uncover the source of revenue, margins and sales.
We have helped companies to move away from a segmentation-based approach to Product Mix Analysis where our advanced analytical techniques can automate the process of selecting the right product, right customer, right time and right quantity. The dynamic Product Mix modelling approach enabled our clients to increase sales and revenue by tapping into undervalued activity of product mix configuration.
How to Model Consumer Off-Take
Off-Take is when customers purchase from a retailer, online shop or wholesaler. In broader term, Off-Take Analytics is a hierarchical process that varies across businesses. Often global or regional Consumer Goods corporations have partial or minimal visibility on Off-Take information.
Our analytical expertise suggests that it’s a more accurate measure of both revenue and sales. In addition, Off-Take enables analytically-minded companies to more accurately advanced their supply value chain comparatively to those that end up modelling gross sales data.
Trusted Data, by estimating off take for our clients’ forecasting solution, proved the point, resulting in generating better forecast and alignment of their supply value chain.
Trusted Data’s advanced algorithms on assortment optimisation and assortment simulation are central to how we capture and model the impact of multidimensional assortment attributes on capturing consumer purchasing behaviour and subsequent impact on product sales, category effects and other key parameters such as switching and optimal locations.
We analytically advise and deliver tangible results for consumer goods companies, in specific, retailers and CPGs on assortment strategies to maximise assortment optimisation impact on both easy to shop customer experience and engagement that leads to positive increase in purchases. Our assortment analytical tools can handle simple to complex constraints such as space, cost, opportunity, consumer experience, revenue and profitability.
Analytics to Achieve Inventory Optimisation
The four rights of inventory optimisation deliver significant benefits to enterprises by ensuring right products are delivered to right customers at the right time and quantity.
Trusted Data’s approach to inventory optimisation is through predictive analytics for inventory management. Our expertise in operationalising advanced predictive and forecasting techniques help us to balance stock and raw material demand at different levels both within the business and the market.
Trusted Data’s team have experience in mining millions of inventory transactions to negate the negative impact of inventory surpluses and shortage. We have proven experience in working with food producers FMCG, distributors, retailers and manufacturer across industries. Our ability to tackle stock-outs and surpluses through the advance application of machine learning, has positioned us as a credible analytics partner in achieving inventory optimisation goals.
Supplier Performance and Management Analytics
Trusted Data’s team ensures our global and regional clients demonstrate competitiveness in supplier performance analytics. We help and enable our clients to gain business intelligence and key decision insights to manage supplier strategy.
We have helped clients with both central and local supplier management platforms. Our key achievement in supplier performance management include reducing spend, products and service optimisation, quality of services, contracts and invoicing.
In addition to solving complex Supplier Management questions – we are proud to have developed multidimensional supplier segmentations, risk management and performance management systems to deliver central, regional and local supplier management excellence.
Warehouse Space Optimisation Analytics
Warehouses or Distributions centers are a space constraint optimisation problem. If space is not being optimised in an efficient manner, then it is a costly business. With our expertise in space and cost-based optimisations we ensure that we define the right problem, set constraint parameters and apply advanced heuristic programming to draw out the best efficiency.
Trusted Data’s team has worked with clients on achieving goals such as: increasing the quantity of stock storage, reducing the cost associated with storage space and advanced models for merchandising based on product association rules for enhanced customer access and uplift in sales.
Over the years Trusted Data has developed several warehouse and store space optimisation algorithms where we were asked to not just achieve maximum storage objectives but also embed discriminate analytics to allow access ease, safety, damage propensity, changing storage capability and product demand movement.
Logistics and Fleet Optimisation Analytics
Logistics applications, particularly focused around routing, have been around for some time but with broader and more complex distribution networks, there is a growing need for a more intelligent approach to this optimisation dilemma.
The final leg in your supply chain should not undo all your efforts upstream; finding the right network design and approach in reducing your cost-to-serve, is much more complex than many routing and scheduling solutions market.
Trusted Data have extensive experience in logistics and fleet optimisation, utilising their machine learning environment to provide clients with more robust solving complexity when facing challenges around right routing & scheduling, fleet size & structure and optimal approaches to fulfilment. The result is a bespoke decision support system, solely focused on optimal asset utilisation, with the end fulfilment goal in mind.
Digital Supply Chain
Digital Supply Chain Transformation
The heart of Digital Supply Chain is not just the numbers but ensuring fast response time to both internal and external customers, flexibility in adopting right strategy quickly, extensive use of granular data and application of models to acquire decision making capabilities and accuracy of machine learning or deep learning models to ensure right decision are taken at the right time. Trusted Data have worked with leading supply chain executives and organisations to digitise supply chain by applying “best fit” approaches using internal and external data to make key decisions.
Using advanced analytics Trusted Data deploys advanced analytical layers on digital supply chain planning, performance management, order management, supplier management, physical assets, business partnerships and organisational supply chain strategy.
Supply Chain Revenue Maximisation
Often supply is driven by demand whilst rarely the converse is true. It is also a fact that often supply chain as a function is evaluated on cost based efficiency measures whilst other departments take credit for increase in revenues, margins and so on… Our experience tells us that supply chain is a core function that can undoubtedly deliver a lot more business value by deploying advanced analytics and optimisation beyond cost efficiencies.
In most of our recent projects we achieved business KPIs for supply chain leaders in the areas of demand affected processes from an increased revenue perspective than simple cost based profitability measures.
Supply Chain Analytics Delivery Model
Define the SUPPLY CHAIN CHALLENGE & target performance outcome
Each clients’ supply chain challenge has its’ own unique dimensions; data, processes, business context and target improvement outcome.
Likewise, Trusted Data’s approach to solution design begins with identifying and defining the right problem for the client and how to clearly define success parameters, which underpin the solution modelling and deployment approach.
ACQUIRE THE right data & ASSIGN THE RIGHT solution methodology
Given the variety and scale of data processed through Enterprise systems nowadays, it is no surprise that Enterprise solutions fail so often to deliver exactly what the Client wants.
Once we have defined the right problem, we turn our focus quickly to selection of the right data and modelling methodology, which will deliver your improvement outcome.
Model & Deploy the right proprietary solution to achieve your TARGET outcome
By utilising AI & Machine Learning, we offer Clients added analytical horsepower to comb through the myriad of data which they warehouse, to extract the right insights and outcomes across forecasting, S&OP, inventory optimisation and fulfilment.
Rather than ‘selling’ solutions, we focus on the ‘promise of success’, guaranteeing clients superior performance.
Knowledge Transfer, Solution adaptation & impact tracking with the client
We remain to close to clients to support effective knowledge transfer, solution impact tracking and iterative refinements to solutions beyond Pilots or version 1.0
Our client needs may evolve and Trusted Data remain repsonsive to adapting solution functionality in line with such requirements.
How We Set Ourselves Apart
Supply Chain Analytics
Trusted Data focus their supply chain analytics practice on creating cost efficiencies and process automation, to deliver responsive supply chain functions that can quickly meet customer needs, without compromising their cost base. We utilise advanced analytical techniques, including Machine Learning to improve forecasting, integrated planning, inventory management, scheduling and routing, offering clients rapid ROI without the need for extensive technology investment
- Flexible pricing (gain share or result driven)
- Right| Data, Methodology & Modelling
- Open source tools
- Achieving target for you
- Speedy delivery
- Guaranteed ROI
Some of our Supply Chain Solutions
Our specialist team of Data Scientists and Supply Chain experts have delivered a suite of sophisticated solutions, supporting supply chain transformation agendas and delivering beyond client expectations.
Predicting Store / SKU Demand
Regional Reduction in Dairy Waste
Improved Forecast Accuracy for a global brand
Cost to Serve Reduction
FMCG Routing & Scheduling
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