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Planning Platform Selection Best Practice Guide

​How to shortlist vendors
It is common for those considering investment into planning platforms to start with the Gartner Magic Quadrant to shortlist potential vendors. It is also quite intuitive to focus on the top right ‘Leaders’ box and guess that it might be safer to shortlist from among those options as choosing a Challenger, Visionary or Niche Player might require additional justification and, therefore, carry higher reputational risk.

What is it actually measuring?
The Magic Quadrant focuses on the vendor, not the product or its capabilities. As of April 2022, there were 22 vendors listed although we are aware of many more vendors who either have their own technology platform or provide a specialised implementation service for one or more technology platforms as the main contracting party.

These 22 vendors are placed in one of the four boxes which are formed by two axes or criteria:
  • Completeness of vision: the degree of alignment with Gartner’s view of future requirements development (i.e. future-proofed)
    • e.g. Leaders & Visionaries are highly aligned with Gartner’s view, Challengers and Niche Players are not 
  • Ability to execute: the vendor’s organisational delivery capability, for example, taking into account client support structure and track record
    • e.g. Challengers & Leaders have a high ability to executive whereas niche players and visionaries may successfully focus on a particular segment but don’t have as broad scale 
​Focus on critical capabilities
Through our best practice sharing discussions, we have heard members that have started by considering ‘Leader’ planning platforms because they represent ‘best in class’ and so match the company’s planning maturity goals.

Aside from the premium pricing, some have realised that at least some parts of their organisation are not ready to adapt to these platforms and so at least some of the potential benefit from the investment would not be realised. This may also risk confidence in future transformation efforts.

As one member put it, going from Excel to a full digital twin solution would be ‘like using a bazooka to kill a fly’! A better approach may be to walk (or crawl) before you try to run by aligning your platform options according to your general level of planning maturity.

Priority capabilities by maturity level
 Maturity level Priority capabilities
 1: Limited process integration within supply chain functions (e.g. planning, warehousing, distribution)
Demand forecasting / planning

 2: Established process integration within supply chain functions Demand and supply planning
 3: Cross-functional process integration beyond supply chain (e.g. including commercial, finance, production & procurement) Cross-functional enterprise planning to support S&OP / IBP (and S&OE)

 4: External collaboration with Tier 1 partners (i.e. suppliers and customers) Multi-enterprise / collaborative planning
 5: End-to-end / multi-tier external collaboration  Advanced analytics, decision support / predictive analytics & automation
Priority capabilities by planning horizon
Planning horizonCapability checklist
Long-term (>18 months)

  • Product & market planning: NPI, EoL / PLM
  • Network design & simulation
  • Strategic resource planning
Medium-term i.e. S&OP/IBP (3-24 months)
  • Demand forecasting & planning
    • Statistical forecasting
    • Probabilistic forecasting
    • Demand-driven planning
  • Machine learning
    • Core algorithms
    • Advanced algorithms
    • ‘Glass box’ / ability to edit / adapt / modify algorithms
  • Artificial intelligence
    • Automatic algorithm selection / recommendation
    • Decision support / option recommendation
  • Customer CPFR / TPM
  • Supplier CPFR
  • Supply planning
    • Capacity planning
    • Inventory planning
  • Concurrent / non-sequential planning
  • Business intelligence & dashboards
Short-term i.e. S&OE (0-3 months)
  • Control tower capabilities
    • Demand sensing
    • Supply sensing
    • Real-time data & dashboards
    • Exception alerting & management
  • Demand execution
    • Inventory optimisation
    • Customer allocation
    • Order management
  • Supply execution
    • Distribution planning
    • Production planning / scheduling
    • Material planning
General / cross-horizon

‘Best in class’ or end-to-end planning platforms align planning decisions at different levels of granularity, across different time horizons and across the end-to-end (i.e. multi-echelon) supply chain.
  • Scenario modelling / simulation / digital twin
  • Reporting / dashboards
  • Exception management
  • Process management
  • Financial impact analysis
  • Multi-functional integration (i.e. beyond supply chain)
  • End-to-end / multi-echelon (i.e. external partners: customers, suppliers, distributors, manufacturers)
  • Granularity
    • product group, regions
  • SKU, customer orders
  • order changes
  • order events
​Other key selection criteria
  • Industry sector expertise & experience
  • Cost & pricing model
  • Ease of integration with ERP / other data sources
  • User interface (UI) / adoption
  • Time & effort to implement
  • Flexibility / customisability
  • Scalability 
  • Extensibility / modularity
  • Future-proofed / ongoing vendor research investment into the core technology & capabilities
  • Balance of vendor investment between pre-sales and implementation support
  • Cost of ongoing SaaS development
  • General market (i.e. vendor independent) capability to support implementation, customisations or improvements
  • Cyber security

​Four general platform types - pros and cons
Although there can be, of course, exceptions for any given planning platform, the pros and cons of each type generally tend to be:
Platform typeProsCons
Dedicated

Top of the range capability

Future-proofed

Good support

Expensive

Long implementation

Need ERP integration
Flexible
Flexible / customisable
Fast implementation
Expandable
 Require extensive configuration
Blank canvas
Need ERP integration
Integrated ERP
Little or no data preparation
More than adequate for less complex supply chains
 Not cutting edge technology

Expensive

UI often not intuitive

Off-the-shelf (OTS)
Fast implementation
Competitive pricing
Good user adoption / training
 Limited capability
Needs ERP integration
With thanks to Tim Kroezen who came up with this schema, planning platforms can be categorised into four different types:
  • Dedicated: fully focused and designed for supply chain optimisation. Dedicated platforms typically have state-of-the art capability and substantial ongoing investment into research and development. Often, they are structured around industry verticals and so can leverage the collective experience and best practices from similar businesses. Although this can offer some 'plug and play' templates that can help improve current processes, this may be offset by greater complexity leading to longer implementations;
  • Flexible: platforms that are able to support planning but are more flexible in terms of their design and configuration. Limited applications like proofs of concepts can be implemented relatively quickly and then be progressively expanded to deliver a very high level of capability, comparable to dedicated platforms. The comparatively 'blank canvas' approach offers high customisability although there often isn't as much in terms of out-of-the-box templates so tend to work well for organisations with well defined and mature processes;
  • Integrated ERP: most ERP systems have planning modules which may not match dedicated platforms for capability or be as flexible but usually (but not always) should be easier to implement as they require less data cleansing and integration work;
  • Off-the-shelf: allow for little or no customisation and typically offer less capability than dedicated platforms but, if data is available, tend to be faster to implement at lower cost.

Which platform type?
Of course, there’s no simple, failsafe answer but judging from the choices made by members over the last few years, it is possible to discern a pattern based on the following factors:
<<OTSERPFlexibleDedicated  >>
<<LowPlanning maturity / capability needs
Change momentum
Current data quality / complexity
 High>>
Factors
  • Planning maturity / capability needs: as highlighted above, platforms with greater capability and expense ought to have a commensurate degree of maturity to get the most from the investment. At lower levels of maturity, there is less risk associated with taking smaller steps with simpler but easier to adopt technology. Higher levels of planning maturity are also associated with more advanced capabilities such as multi-enterprise collaboration;
  • Change momentum: this is really a grouping of several factors:
    • willingness to change
      • impetus: without a ‘burning platform’ i.e. a clear consensus on why the status quo is unsustainable, members have found it very difficult to generate the buy-in or momentum to support significant investment into planning capabilities;
      • transformation vision & roadmap clarity: a common inhibitor has been a lack of confidence about the ultimate destination and the best route to get there, especially when budgets are tight and mis-steps are possibly career-defining; 
    • ability to change
      • uniformity: the more uniform a business, the more likely it is that investments in planning capability will have larger-scale returns;
      • change capability: a combination of the necessary skills, time and energy able to be dedicated to implementing and embedding new processes and technologies;
  • Data quality & complexity: in general, the better the current quality of data, the more likely that any type of planning platform choice will be successful but this is rarely the case so the question is what to do if current data quality is poor? Similarly, off-the-shelf and ERP-based platforms are less likely to be able to handle complex data sets. Member experience has clearly shown that the amount of data work should not be underestimated so, given this, the choice seems to come down to how much work is involved and how likely it is that you might have to do that work all over again if, a few years down the road, you want to move to a different platform.
​Member experience of recent planning platform implementations
The key points below reflect contributions from multiple discussion participants, not any one in particular except where stated, and have been anonymised and edited to adhere to our 'Chatham House Rule' policy.
  • A recurrent theme: the ‘soft’ challenges around ownership, buy-in, behavioural change and adherence are often the trickiest;

  • A common assumption is that sticking with an incumbent technology provider should make transition and integration easier but that often not the case, even though some incumbents seem to be overly relying on this assumption;

  • It was noted that some ‘next gen’ platforms seem more mature than others, including some of the bigger names. This is often notable by whether or not the vendor is able and willing to perform a live demo using sample customer data and the extent to which capability is already built or on the development roadmap;

  • Multiple platforms are being used for different aspects of planning and, generally, they serve their purpose well, often supported by some in-house developed solutions. However, the interfaces between those systems is a persistent challenge which makes getting reliable output a real challenge;

  • For those with experience of ‘next-gen’ tools, there has clearly been an improvement in forecasting capability, not least as a collaborative platform where commercial and planning can come together to enrich the forecast;

  • There is still a role for more traditional, univariate statistical models to play, particularly for some demand profiles;

  • Business units who already had a good grasp of price and promo data have seen much bigger improvements than those without demand driver intelligence;

  • Lessons learned on implementation include that it pays to have a clear PMO structure and different main roles with ‘super users’ training the trainers, data scientists improving the algorithms and innovative approaches and the planning analysts who run the routines, identify and handle the exceptions and outliers;

  • ‘Next-gen’ platforms have certainly helped improve and embed best practice planning processes but leadership is critical to that and, also, the perception of it being a business / IBP process and not just a ‘supply chain thing’.



Top SC Planning Best Practices...Digested

Real lessons learned distilled from a series of practitioner exchanges on...

Digital Transformation of Supply Chain Planning

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Supply Chain Design Modelling and Analytics

Supply chain network (re)design used to come around every few years or so, often based on quite a high level view of customer segments and associated costs. Now, competitiveness and even business continuity relies on the capability to dynamically adapt network flows based on a much more granular understanding of cost drivers.

Volatility, Agility & Resilience: Next-Level Planning

Volatility, uncertainty, complexity and ambiguity was already an increasing factor before the pandemic but, now, it is clear that we need the next level of demand forecasting, sensing, planning and execution.