The inefficient procurement processes and workflows that companies face now require fundamental innovation. As market uncertainty intensifies and supply chains become more complex, corporate procurement professionals are being forced to make increasingly difficult decisions under heavy responsibility.
The biggest problem with current procurement processes is the absolute shortage of market information. In rapidly changing market environments, collecting and analyzing reliable information has become a task that exceeds the limits of time and human resources.
Decision-making based on incomplete information inevitably causes massive losses to companies.
Inefficient procurement processes lead to excessive cost expenditure and quality problems in the short term. In the long term, they can cause greater risks of weakened corporate competitiveness and reduced growth potential.
Particularly in the current situation where supply chain risks are increasing, inappropriate supplier selection can even threaten corporate survival.
We can no longer maintain processes that rely on individual procurement professionals' experience and intuition. Innovation in procurement processes that matches the era of accelerating digital transformation is needed.
This article will present procurement process innovation strategies utilizing AI technology and examine the practical value that companies can obtain.
The procurement team's work doesn't stop at simply purchasing goods. Production departments demand stable quality and on-time delivery, R&D teams require high-specification materials with new technologies applied, and finance teams demand cost reduction.
The procurement team experiences significant stress in the process of coordinating these conflicting requirements from each department.
Particularly when new projects arise or specifications change, close communication with multiple departments is essential. However, since each department has different positions and priorities, considerable time and effort are required for opinion coordination. Sometimes situations arise where they must serve as mediators for inter-departmental conflicts.
In these situations, procurement teams bear the burden of finding optimal solutions that satisfy all departments. They must make balanced decisions by comprehensively considering various factors such as quality and price, delivery time and technical capabilities, but this is realistically a challenging task.
Moreover, since these coordination processes are often not documented or managed systematically, they frequently depend on individual employees' capabilities and efforts. This becomes a factor that hinders work continuity and efficiency.
Another major challenge facing procurement teams is the lack of market information.
Particularly when reviewing new items or alternative products, difficulties due to information absence become even greater. While there is much needed information such as market price trends, supplier reliability, and quality levels, systematically collecting and analyzing this information is realistically very difficult.
Most procurement professionals have no choice but to rely on information provided by sales representatives or internet searches. However, such information is often biased or lacks timeliness.
In rapidly changing market situations, information timeliness is very important, but current information collection methods make it difficult to meet this requirement.
As global sourcing increases, the importance of overseas market information is also growing. However, accurate information collection is becoming more difficult due to language barriers, time differences, and cultural differences. This is a major risk factor that can lead to wrong decisions.
Consequently, procurement professionals bear the burden of making important decisions with insufficient information. This increases work stress and sometimes leads to conservative decision-making, causing opportunity losses.
An unavoidable hardship in procurement processes is complex approval procedures and document management. In most companies, procurement approval must go through multiple stages, with various supporting documents required at each stage.
While these procedures are necessary for transparency and control, they become a significant work burden for practitioners.
Even in situations where urgent purchases are needed, the reality is that all prescribed procedures must be followed. When approval is delayed due to absence of approval authorities or incomplete documentation, this can immediately lead to production disruptions or cost increases.
Procurement professionals must invest additional time and effort to manage these risks.
The inefficiency of document management is also a serious problem. With numerous documents such as quotations, contracts, and inspection reports being managed without proper systems, much time is wasted finding necessary information.
Particularly since past transaction histories and negotiation processes are not systematically managed, similar situations often fail to properly utilize past experiences.
These inefficient processes are becoming factors that hinder the strategic capability enhancement of procurement teams. The reality is that time that should be concentrated on core tasks such as market analysis and strategy development must be allocated to administrative work.
The most important aspect of market analysis is securing reliable data.
Deepflow provides procurement professionals with rich information they need through comprehensive global data collection. Supply and demand data ranging from past price information to production, consumption, and import/export volumes are utilized to understand basic market supply and demand conditions.
Market environment data such as competitive raw material prices, substitute prices, and market competition situations are added to enable more comprehensive analysis. Particularly by integrating macroeconomic indicators such as major countries' GDP growth rates and inflation, various factors affecting the market can be comprehensively considered.
These data are not simply collected but stopped there. Deepflow's AI engine analyzes correlations between collected data and derives meaningful patterns. Through this, procurement professionals can understand complex market situations more clearly and make rational decisions based on data.
Deepflow's greatest strength is its future prediction capability. Based on vast collected data, AI prediction models are built to predict market conditions for the next 6-12 months with high accuracy.
This goes beyond simply extending trends of past data to sophisticated predictions considering interactions of various variables.
Particularly in predicting shipment and order volumes, Deepflow shows excellent performance. It captures even minute patterns that are difficult to grasp through human intuition or simple statistical models, providing more accurate prediction results. Through this, procurement professionals can proactively respond to future demand changes.
Furthermore, by predicting even first-quarter sales volumes before new product launches, it provides practical help in establishing procurement plans. This leads to inventory management optimization and cost reduction, ultimately contributing to corporate competitiveness enhancement.
Deepflow doesn't simply provide prediction results but also provides clear explanations for those results. By quantitatively analyzing and showing key factors that serve as grounds for predictions, it helps decision-makers fully understand and trust the results.
This 'explainable AI' function effectively combines procurement professionals' expertise with AI's analytical power. Based on analysis results presented by the system, procurement professionals can derive optimal decisions by adding their experience and expertise.
Additionally, Deepflow provides forward-looking insights. Rather than relying only on past data, it enables more strategic procurement decision-making by selecting and presenting best and worst products based on predicted future sales and shipment volumes.
Another strength of Deepflow is the automation of data analysis processes. By automating the entire process from vast data collection to preprocessing, analysis, and result derivation, it significantly reduces procurement professionals' work burden.
Particularly by automating processes requiring professional knowledge such as data standardization for AI model training, feature engineering, and model training, even users without specialized knowledge in data analysis can easily utilize it. By automatically calculating optimal purchase quantities and order schedules based on prediction results, it further enhances work efficiency.
No matter how excellent the technology, its value is diminished if it's difficult to use. Deepflow is designed so that even users unfamiliar with AI technology can easily utilize it through an intuitive UI.
It supports understanding complex analysis results at a glance using the latest data visualization technology and helps users easily understand the system's operating methods through detailed tooltips and manuals. Through this, the entire procurement team's digital capabilities can be enhanced and a data-driven decision-making culture can be established.
Deepflow provides a 3-month short-term pilot program so companies can verify the solution's value without burden. Through short-term paid trials rather than annual contracts, companies can directly experience the accuracy and practical utility value of AI-based demand forecasting.
It's provided at a dramatically reduced cost compared to regular contracts, allowing companies to fully verify the solution's effectiveness while minimizing risk.
The pilot program proceeds through a systematic step-by-step approach. During the first month after contract, company data integration, AI model training, system construction, and onboarding take place.
During the following two months, actual prediction model performance is verified, and the process of optimizing model performance by reflecting customer feedback proceeds.
The pilot program is provided in an optimized form tailored to company characteristics and needs. It can demonstrate the greatest effect particularly for companies with abundant daily sales data, such as food manufacturing/sales companies or retail companies.
Particularly, departments directly related to demand forecasting such as SCM (production management), sales-marketing (sales management), and procurement (raw material management) can obtain immediate benefits.
Deepflow's Forecast function supports inventory management optimization through sales volume prediction, while the Materials function supports procurement timing optimization through raw material price prediction.
The ultimate purpose of the pilot program is to resolve uncertainties about AI adoption that companies may feel. By experiencing the actual value of the solution during a sufficient verification period of three months, companies can lay the foundation for subsequent long-term digital transformation.
Particularly since decision-makers from CEOs to executives can directly verify the solution's value, it greatly helps in promoting company-wide digital innovation. Based on performance during the pilot period, companies can pursue AI-based procurement process innovation with greater confidence.
Pilot program implementation can be applied for through consultation via the Deepflow homepage, and detailed guidance from professional consultants is available. Start your company's procurement process innovation through a 3-month pilot program now.
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