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Measuring 'true' cost-to-serve

    

Data & analytics
JP Doggett

SKU rationalisation driven by volatile demand during the pandemic has brought greater focus on cost-to-serve analysis at an increasingly granular level. In tandem with IBP processes that forecast and plan by value as well as volume to enable better decision-making and reduced costs, cost-to-serve analysis must be able to pinpoint where efficiencies and opportunities can be found. Moreover, shareholders are increasingly demanding a 'triple bottom line' view of costs which include ESG / sustainability metrics.

 AGENDA 

Measuring 'true' cost-to-serve

  • How to do cost-to-serve analysis at a granular level?
  • How to use granular cost-to-serve to have better conversations with finance?
  • How to incorporate sustainability / ESG metrics?

 WHO FOR? 

Industry sectors: all sectors but particularly relevant for Consumer Goods / FMCG and Food & Beverage companies

Located: Global

Org. size (annual T/O): typically £1 bn+

Roles & remits: Heads of:  Supply Chain, Finance, Analytics and Sustainability

 ABOUT INTENT DISCUSSIONS 

  • All discussions are private, held under the Chatham House Rule and moderated by INTENT with approx. 6-8 participants for 45-90 mins of candid, interactive discussion (not a passive webinar)
  • Some discussions include subject matter experts from member-recommended INTENT Partners, others are exchanges of best practice, experiences and ideas among practitioner members only
  • Discussions are shaped by participants according to their interests and questions
  • We may adjust participation to avoid competitive sensitivities and ensure productive discussion

 WHEN? 

Thursday 20th May (11.00 BST / 12.00 CEST) for max. 90 minutes

Hosted by Intent

Guest experts: Dan Levy and Richard Thompson, CadDo

 

Request to join

 

Interested but can't make the date? Email us and we'll update you about future discussions.

 

  • Also...

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      Although there continue to be many challenges in arriving at a robust plan in the first place, this discussion focused on how to close the gap with execution or, in other words, reduce time lag or latency of deviations from plan being predicted and detected to being successfully managed.
      Latency definition: how quickly can you predict something is going to happen? How quickly can it be filtered in the hierarchy? It’s fundamental to how the SC and finance are organised. Latency is a combination of data availability and process

       
      Latency -1 (predictive)
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      The pandemic has pushed businesses towards short term decision making. But it’s the mid term (S&OP) monthly horizon will influence the profitability. Translating from demand forecast to ordering requires a reduction or elimination of silos. Latency is most often caused by layers of hierarchy. Siloed decision making is a very common challenge. Large businesses are often regionally siloed too - hence the recognition of need for a centralised decision making unit. 
      Be aware that the flip side of empowerment can be regionally made decisions that affect other parts of the global business.
      Latency challenges/causes
      Slower decision making is exacerbated when finance does not trust the IBP number as much as its own financial forecast. There is a growing convergence of finance into supply chain; often the CFO is the ‘co-pilot’ to the CEO. 
      Suggested approaches to IBP and reducing latency
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      Summary of a discussion hosted on 20th May with Intent members and guest experts Richard Thompson and Dan Levy of CadDo.
      Market context and typical challenges
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      COST-to-serve is somewhat of a misnomer as it can overly narrow the focus on the cost side whereas framing it as something like 'cost-to-serve contribution', Holistic Customer Investment or taking an EBIT-level view offers better perspective coupled with and end-to-end view. Incorporate data from other parts of the business in whatever format it is recorded (don’t try to introduce or change data format as this will surely be impeded). Start with the invoice data as a base and go to each function in your organisation to see what data can be pulled to augment this?  Set the CTS rules and get buy-in to allocation methodology. You will find that the warehouse is the most complex area. Ensure CTS is not being used to ‘beat up’ one function. Transparency of CTS data helps defuse a sometimes adversarial dynamic where one function or teams' view is pitted against another, acting as a glue rather than a wedge. This transparency itself often prompts more and better questions which are enriched by different viewpoints. Factor in FTE overhead - e.g. how many planners, how much devotion in customer service? Those FTEs are most often allocated to customers, or geo’s, or products, so these costs can be attributed. Establish the wins for each function and you’ll get the buy-in! How does better CTS insight help each function perform its role better and contribute to the common goal e.g. improving EBIT? Consider extending the potential “wins” to include suppliers who may need to be motivated to support upstream enhancements (open book discussions). This could be particularly significant in the ESG expectations of suppliers. CTS can start in supply chain but often end up in commercial where it is used as a framework for productive negotiation and to drive deals and offers. Sharing this information with customers can help influence how they accept being served, or nudge buying practices in a positive way. Make CTS a living breathing exercise - take data feeds once a month. A one-off exercise tends to land and be ignored because there is no change or measurement for improvement. CTS analysis can then be used as a data feed for other changes, projects or servicing decisions.  Incorporating ESG metrics into CTS analysis
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      Request to join
       
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