The volume and diversity of data generated by companies have reached unprecedented levels. As this data accumulates, its intelligent exploitation becomes a genuine strategic lever for remaining competitive. At the same time, markets are becoming more complex, as are supply chains, which are subject to increased risks and stricter regulatory requirements.
For Chief Procurement Officers, managing directors, and all decision-makers, the speed and precision of decisions now determine overall performance. It is in this context that business analytics has become an indispensable tool. It contributes to transforming the procurement function whilst enabling margin optimisation, process rationalisation, and anticipating market developments.
What is business analytics?
Business analytics refers to the collection of methods and technologies that enable the analysis of company data to extract actionable insights for decision-making. Unlike business intelligence, which focuses on collecting and reporting past data, business analytics goes further by integrating predictive and prescriptive models. It also differs from data analytics, which is broader and includes purely exploratory analyses without immediate decision-making purpose.
Its main objective is clear: to enlighten decision-makers in order to improve operational performance, optimise processes, and identify new opportunities.
The different types of data analysis
Business analytics relies on four complementary approaches:
- Descriptive analysis: provides a factual and synthetic view of past data (turnover, purchase volumes, service rates, etc.).
- Predictive analytics: uses statistical models to anticipate future trends, such as demand evolution.
- Prescriptive analytics: recommends optimal actions based on identified data and constraints.
- Statistical and analytical data analysis: evaluates data reliability, correlations, and variations to improve decision quality.
Why choose business analytics for business?
Adopting business analytics presents many advantages. It improves decision-making through objective and updated data whilst optimising procurement processes, eliminating inefficiencies and negotiating on more solid foundations. Business analytics also enables cost reduction and increased profitability, particularly through supplier rationalisation and better stock management. Lastly, it facilitates the identification of new opportunities, for example unexploited markets or strategic partnerships.
Strategic applications of business analytics in the procurement function
For the procurement function, business analytics is not limited to simple expenditure analysis. It transforms practices in depth by providing access to a more detailed and predictive view of challenges.
Supplier performance analysis
Measuring and comparing supplier performance becomes more rigorous thanks to key indicators, such as deadline compliance, compliance rate, and quality of delivered products. Sectoral benchmarks help identify best practices and evaluate gaps compared to the competition.
Demand forecasting and stock management
By exploiting historical data, business analytics enables better anticipation of demand fluctuations. Predictive models help adjust stock levels, thus avoiding stockouts or costly overstocking.
Risk management and compliance
Business analytics tools detect anomalies or inconsistencies that could reveal fraud. They also facilitate regulatory compliance monitoring by alerting potential non-compliance in procurement processes.
Cost analysis, margins, and budget forecasting
Business analytics offers a detailed view of actual costs and their evolution. It helps evaluate the profitability of acquired products and services, and establish more reliable budgets that are better aligned with strategic objectives.
Purchasing behaviour analysis
By studying purchasing habits, decision-makers can identify opportunities for consolidation or negotiation, and rationalise their supplier panel to optimise costs and quality.
(Inset) "We exploit data to analyse purchasing behaviours and offer complete visibility to our customers. This allows us to conduct benchmarks, identify best practices, and optimise procurement processes." - Xavier Laurent, Mergers and Acquisitions Director, Manutan
Case study: How business analytics transformed a company's procurement function
At the heart of volatile markets and increased pressure on margins, the procurement function is forced to reinvent itself. A concrete example illustrates how business analytics can become a decisive transformation lever.
A distribution company, faced with sudden demand variations and chronic delays from its suppliers based outside Europe, decided to place data analysis at the heart of its procurement strategy. It implemented integrated business analytics software, centralising all data relating to procurement, stock, and supplier performance.
Thanks to this analytical platform, the company began by automating data processing and making its indicators more reliable. Predictive analytics enabled anticipation of seasonal demand peaks and proactive adjustment of stock levels, thus limiting stockouts whilst reducing costly overstocking.
At the same time, business analytics highlighted imbalances in the supplier panel. The company therefore undertook to rationalise its partnerships, selecting strategic suppliers based on objective indicators such as deadline compliance, delivery quality, and contractual flexibility. To secure its supplies, it also diversified its sources for critical components and negotiated automatic revision clauses in its contracts in order to better absorb market fluctuations.
Continuous analysis of performance and risks also enabled detection of several billing anomalies, generating immediate savings, and identification of vulnerabilities in certain logistics chains. Corrective measures were implemented, including partial relocation of some flows to European suppliers, which are more resilient and manageable.
At the end of this data-driven transformation, the company recorded significant results: notable improvement in service rate, 15% reduction in annual procurement costs, and better operational continuity during periods of high tension. The procurement function thus gained agility and resilience whilst contributing to strengthening the company's overall competitiveness.
(Inset) "Companies that leverage data and analyse it gain a competitive advantage and see a strong return on investment" - Pierre Capelle, Partner responsible for Data Analytics and Artificial Intelligence activity, PWC FRANCE
How to implement business analytics in business?
Whilst the benefits are clear, the success of a business analytics project relies on methodical implementation.
1. Needs assessment and objective definition
The first step consists of identifying priority business challenges (cost reduction, better forecasting, quality improvement, etc.) and formalising clear and measurable objectives.
2. Choosing appropriate tools and technology
Technical solutions are numerous, from business analytics integrated into ERP systems to specialised platforms based on big data and data science. The choice depends on data volume, desired analysis complexity, and available resources.
3. Team training and change management
The transformation requires developing employees' analytical skills. Change management support is essential to foster team buy-in and integrate new practices into company culture.
4. Best practices for successful business analytics projects
It is recommended to structure data collection, cleaning, and analysis processes to guarantee their reliability. Defining performance indicators and regularly monitoring results to adjust strategy are also indispensable.
What are the prospects for business analytics in procurement?
Technological developments continue to expand the realm of possibilities for the procurement function.
Artificial Intelligence and Machine Learning
The integration of AI and machine learning enables automation of certain analyses, detection of weak signals, and formulation of real-time recommendations.
Real-time analysis and IoT
Thanks to connected objects and real-time analysis solutions, the procurement function can make informed decisions instantly based on updated data, which strengthens reactivity in the face of unexpected events.
Business model transformation
Advanced data exploitation opens the way to new economic models, centred on personalisation, sustainability, and shared value creation with partners.
Business analytics has become a strategic lever for transforming the procurement function. It enables decision-makers to make faster, better-informed, and more sustainable decisions whilst optimising costs and strengthening supply chain resilience. It is time to fully integrate the power of data into your decisions to strengthen your company's overall performance.
