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Article Summary: AI Can Transform Integrated Business Planning


Companies aspiring to develop better strategies and forecasts are turning to AI-driven integrated business planning (IBP) platforms to do so. The latest research from Boston Consulting Group shows that if you hope to better navigate uncertainty and remain competitive, adopting an AI-driven IBP system can enable you to create more accurate forecasts, while increasing the ease and speed of your planning process. But the transition from conventional IBP approaches to an AI-enabled one isn’t easy – gain valuable insights into how to drive the most possible value, harness the full potential of your data and optimally manage your transformation.


  • Better navigate uncertainty with AI-driven integrated business planning (IBP).
  • AI-driven IBP platforms are faster, better and easier to deploy than conventional approaches.
  • Get more value from your AI-driven IBP platform in five steps.

Article Summary: AI Can Transform Integrated Business Planning


Better navigate uncertainty with AI-driven integrated business planning (IBP).

During and following the COVID-19 pandemic, it became clear that many companies were strategically unprepared for the crisis. To better navigate uncertainty going forward, companies are leveraging AI-driven platforms as an alternative solution to conventional IBP, which has few optimization or predictive capabilities. AI-enabled IBP platforms can help your company create a “rich data fabric,” while providing algorithm-driven decision-making support and automating your entire planning process. Adopting AI-driven IBP can also boost job satisfaction by systemizing work, freeing team members to focus more on innovation and strategic tasks.

“As uncertainty shrouds the global economy and technological change accelerates, business planning will become more relevant – and complicated.”

You’ll likely encounter challenges when switching to an AI-driven IBP system though, as it’s not simple to design or deploy and can cost your business tens of millions of dollars. In fact, large corporations should expect to invest more than $100 million. Many invest heavily in AI-driven IBP, only to discover that they didn’t realize as much value as they’d hoped. Such challenges arise due to common mistakes: misaligned processes, a poor adoption rate and a lack of connectivity between IBP tools. To stay ahead of your competition, invest time in developing strategic capabilities that seamlessly integrate data, processes and people.

AI-driven IBP platforms are faster, better and easier to deploy than conventional approaches.

Leveraging AI-driven IBP platforms can help your business gain the following:

  • Speed – Using AI-driven forecasting models and automated data feeds, your company can develop forecasts in a shorter time frame, while minimizing the number of planning iterations with automation. By migrating to an automated IBP platform, you can reduce your planning cycle time by between 30% and 40%.
  • Ease – When you harness the power of AI-driven IBP solutions, your company can align demand, supply and financial plans in real time across business units, teams and functions. This eliminates the cumbersome need to rely on Excel spreadsheets, while enabling companies to better identify opportunities and challenges using common data sources.
  • Visibility – Connecting supply scenarios and demand forecasts with AI-driven IBP will increase visibility into your operating constraints, enabling your company to better close gaps by reshaping demand or increasing supply. This increased end-to-end visibility will reduce your supply chain costs, as it boosts efficiency, lowers warehouse expenses and improves order management. Expect to see the accuracy of your forecasts improve by between 10 and 25 percentage points when using IBP platforms.

Get more value from your AI-driven IBP platform in five steps.

Implement your AI-driven IBP platform using the following steps:

  1. Harness all data – Diversify your data, drawing on a variety of quality sources (for example, between 15 and 20 data sets for demand planning), which should include both early-warning signals and standard inputs. When you implement a SaaS platform, be sure to deploy rigorous, systematic data governance systems.
  2. Orchestrate the solution – Avoid the temptation to use “a single out-of-the-box package” as the basis of your IBP solution, and leverage a SaaS IBP platform that supports multiple orchestrated solutions, connecting and integrating your existing systems, while closing any gaps.
  3. Customize algorithms and scenario and forecasting models – Eschew “off-the-shelf algorithms” for your own customized ones, as you’ll increase the accuracy of your forecasts by between five and 20 percentage points.
  4. Manage your transition patiently – You can’t rush your transition to an AI-driven IBP platform, as it requires extensive worker training across organizational levels and functions. While you can execute your transition in sprints, you should consider institutionalizing it as more of a marathon.
  5. Ensure your top management team’s support – Your transition is more than just a new planning process. Think of it as a company-wide performance-boosting initiative. Getting buy-in and involvement from your top management team can be a critical element in creating your vision, developing clear objectives and ensuring alignment throughout your organization.

About the Authors

Tristan Mallet, Lana Klein, Aneesh Saxena, Abhijeet Shetty, Olivier Bouffault, Daniel Sack and Rachel Wegman are professionals with Boston Consulting Group.

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