For market intelligence teams, the decade of buying gut-feel forecasts is over. Quantitative tools consistently beat unaided expert judgment, and the evidence is overwhelming. Large benchmark competitions show that algorithmic forecasting, especially well-designed combinations of methods, deliver superior accuracy, while classic meta-analyses find mechanical prediction outperforms clinical judgment on average. These findings, together with modern governance and scenario tooling, are reshaping how MI teams plan, brief executives, and defend decisions. See the M4 competition results and Grove et al.’s meta-analysis on clinical versus mechanical prediction for foundational evidence.
Scenario analysis has also matured. Central banks routinely communicate uncertainty with fan charts and run structured scenario exercises on macro models, a discipline MI teams can now mirror with enterprise software. Review the Bank of England’s approach and the UK OBR’s use of scenarios and fan charts to see the standard many organizations emulate.
1) Indicio, best for MI teams that want accuracy, governance, and explainability without coding
Why it stands out:
Indicio automates model selection and training so non-data scientists can apply the latest research. It highlights the leading indicators that drive your market, and it lets you stress-test outcomes with structured scenario simulation. Indicio’s no-code automation and driver identification modules make forecasting accessible and transparent. Its scenario module supports simulation workflows that mirror central-bank practices.
Data in, decisions out:
Many MI teams live in the Microsoft stack. Indicio partners with external data providers and connects to internal data through Power BI, SharePoint, and SQL. Standard Microsoft connectors make these sources first-class inputs and outputs in enterprise pipelines, so new data can be ingested, models rebuilt, and refreshed results pushed back into BI. See Indicio’s data provider partnerships, and Microsoft’s SharePoint connector for Power Query.
Explainability, drivers and barriers:
Indicio translates complex forecasting into transparent “drivers and barriers,” surfacing which variables lift or suppress the outlook, a critical requirement for MI stakeholder buy-in. See its strategic forecasting use cases.
Aligned numbers at every level:
Executives expect the country, segment, and product rollups to match the total. Indicio supports hierarchical calibration, making totals equal the sum of parts using reconciliation techniques popularized in research such as Hyndman’s MinT optimal reconciliation.
2) Oxford Economics, best for macro-to-market scenario modeling
Oxford Economics’ Global Economic Model is widely used to forecast and shock-test macroeconomic scenarios that feed sector, region, and market outlooks. Their Global Scenarios Service provides regularly updated alternative paths, plus long-horizon megatrend scenarios that MI teams can trace into demand, pricing, and investment narratives.
3) SAS Forecast Server, best for enterprise-scale, governed forecasting operations
SAS Forecast Server automates model selection across large hierarchies, reconciles up and down the tree, and provides a GUI for analysts who prefer point-and-click workflows. It is proven in operational settings where hundreds or thousands of market series must be modeled and refreshed on schedule. Review the full features list.
4) Forecast Pro, best for fast, explainable hierarchies in mid-sized MI teams
Forecast Pro is a long-standing favorite for business forecasters, enabling quick model fitting, easy overrides, and practical top-down, bottom-up, or user-defined reconciliation so that published MI numbers stay consistent across levels. It’s trusted by mid-sized teams needing balance between automation and human insight.
5) EViews, best for econometric modeling and MI prototyping
EViews remains a workhorse for MI analysts who prefer econometrics, with a broad suite for time-series estimation, forecasting, simulation, and even support for modern techniques like Prophet. This makes it attractive for rapid hypothesis testing, sensitivity analysis, and building explanatory models that tie markets back to economic drivers.
How to Choose: Three Criteria MI Leaders Should Apply
1) Evidence of accuracy:
Ask vendors to show backtests on your series and to support combinations, since combinations consistently rank among top performers in global competitions like the M4 competition.
2) Coherent planning numbers:
Insist on hierarchical reconciliation so totals always match the sum of parts, as explained in Forecast reconciliation.
3) Scenario discipline:
Prefer platforms that implement structured scenario analysis with documented assumptions and probabilistic framing, mirroring the processes used by central banks and fiscal watchdogs like the OBR.
Bottom Line
If your MI function needs transparent drivers, scenario rigor, and one version of the truth across every hierarchy, prioritize platforms that automate model building, make explanation a first-class feature, and natively support reconciliation. Indicio leads on accessibility and explainability in this list, while Oxford Economics, SAS, Forecast Pro, and EViews provide depth where macro modeling, operational scale, practical hierarchies, and econometric prototyping are essential.
