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NESIC: Leveraging Process Mining and Cluster Analysis to Optimize Sales

Discover how NEC Networks & System Integration Corporation (NESIC) has been pursuing improvements in sales efficiency with 10 essential process patterns extracted through mining data from business meetings.

10

Key process patterns unveiled to inform strategic optimizations in sales negotiations

1

Robust model that evaluates workload capacity and optimizes resource allocation

33%

Reduction in time required to develop a data pipeline

 

NEC Networks & System Integration Corporation specializes in the design, construction, and installation of private branch exchange and networks for both private and public clients in Japan. In recent years, NESIC has expanded its portfolio to include SaaS resale, systems integration, and operational services. This expansion notably includes the resale of web conferencing tool Zoom in Japan.

But that’s just the beginning. Keep reading to uncover how NESIC navigates diverse markets with innovative strategies, optimizes sales processes, and utilizes advanced analytics to drive business growth and staffing efficiency.

Navigating Diverse Markets With Standardized Sales Strategies

With recent advancements across various industry sectors embracing SaaS solutions, NESIC has adjusted its sales organization to better cater to specific industries. However, managing the complexity of sales methods and workflows remains challenging, as the absence of standardized processes makes it difficult to provide quantitative recommendations.

The organization operates with subdivisions, where each employee is responsible for conducting business negotiations within specialized industries. Therefore, it’s essential to make recommendations suitable for individuals or allocate staff accordingly for the best negotiation methods. Given these circumstances, there is an urgent need to visualize the negotiation process in the sales domain, reassess human resource allocation, and formulate measures for personnel evaluation to identify and address any performance gaps among employees.

In the past, each sales representative at NESIC was tasked with conducting business negotiations independently, despite encountering a diverse range of clients and pricing tiers.

However, this approach presented several challenges:

  • Lack of standardization in the process of acquiring sales from customers.
  • Inability to quantitatively evaluate personnel performance based on sales activities.
  • Suboptimal staffing allocation according to sales representatives.

To address these issues, NESIC utilized the following models:

  • Process mining for sales processes.
  • Cluster model based on the volume and value of business negotiations.
  • Reports integrating process mining and cluster models.

Streamlining Sales Processes With Process Mining and Cluster Analysis

Dataiku offers a unified platform for data preprocessing, feature engineering, machine learning, and model monitoring. Data preprocessing tasks are managed using Dataiku recipes, while Business Solutions are utilized for the learning model’s predictive output method and process mining.

The project, led by a team of 10 individuals including two recipe creators and a service planning advisor, closely collaborated with the sales department, acting as the end user, to address two critical issues:

  • Process Mining of Business Meetings Registered in SFA
    • To optimize business meetings, a process mining technique was employed, analyzing the classification of meetings recorded in the SFA system over time. This analysis revealed the 10 most common business process patterns, providing valuable insights. Initially, creating the first process mining model took about a month. However, simply presenting the results wasn’t enough to guide end users effectively. To address this, two important innovations were introduced:
      • Presenting Model Process Sales Representative Performance
        Sales representatives were interviewed to identify individuals showcasing exemplary negotiation practices. By focusing on these role models and narrowing the scope, a visual representation of the negotiation process was developed as a reference for others. Notably, findings revealed that sales activities often involve a dynamic process, with significant movement and negotiation concerning amounts and delivery dates.
      • Visualizing Process Mining Results by Sales Team
        Recognizing the diverse customer interactions across sales teams, the approach was customized accordingly. Analyzing process mining outcomes unique to each team allowed for the recommendation of negotiation strategies tailored to their respective industries. This process facilitated the identification of biases within the sales organization and ensured that each team adopted a process aligned with their unique requirements.
  • Cluster Analysis of Deals Registered With SFDC
    Business negotiations encompass both high-value and low-value projects, leading to significant variations in the amount, range, and number of projects handled by different individuals. To address this variability, clustering techniques were employed.

    • A BIN was created to map and visualize the revenue, number of cases, and number of customers handled by each sales representative. This provides insights into the sales representative’s workload, pricing range, and capacity for managing projects.
    • Additionally, the distribution of cluster results by organization was examined. This helps in organizing and optimizing the workload of sales representatives effectively. Nearly 30 recipes and one model were developed within the design node after data cleansing in Snowflake.

Leveraging Visualizations, Performance Assessment, and Quantitative Metrics

Benefits for the sales department include:

  1. Visualizing the business negotiation flow based on industry standards, providing a reference for the negotiation process through the negotiation process shown by the model.
  2. Assessing the performance of individuals based on project pricing, volume, and customer base, utilizing clusters as a reference for organizing sales teams effectively.
  3. Incorporating clusters and process results as quantitative evaluation metrics, alongside reference information, for comprehensive performance assessment.
By using sales activities in the education of new employees and mid-career employees, I was able to have an image of the process as a guideline.

Empowering Users to Enhance Sales Efficiency

Dataiku enhances NESIC’s sales activities efficiency. By incorporating sales activities into the training of new and experienced employees, a clear process guideline is established.

Dataiku delivers valuable capabilities accessible to users of all skill levels in data science or programming:

  • Streamlined Process Mining: With Dataiku’s Business Solutions, users can quickly construct process mining flows, even without advanced technical skills, streamlining the process.
  • Interpretable Cluster Models: Dataiku enables the creation of easily interpretable cluster models through tools like partial dependency graphs, important feature graphs, and correlation analysis, enhancing understanding and insights.
  • Integration of Latest Analysis Methods: Users can seamlessly employ the latest analysis methods from a variety of business solutions within Dataiku, enhancing their analytical capabilities and keeping up with industry trends.
This solution makes our sales activities smarter and more efficient.

Expanding Data-Driven Decision-Making Across NESIC

To drive AI adoption across the organization, NESIC evaluated 10 AI tools and selected Dataiku for its flexibility and robust governance. Dataiku provides NESIC with a centralized, accessible way to store data and AI models, preventing silos and enabling efficient model management. This approach simplifies governance across the organization and supports NESIC’s strategy for unified data insights. The platform also integrates seamlessly with other systems and APIs, offering advanced capabilities and the latest algorithms for comprehensive analysis.

In less than a year with Dataiku, NESIC has successfully implemented AI models across 20 projects, showcasing an agile, data-driven approach to decision-making. The platform supports every stage of NESIC’s process — from data acquisition and preparation to analysis, model development, and report generation — significantly reducing project timelines. For example, tasks that previously required 10 weeks of development and tuning are now completed in just 2 weeks, thanks to Dataiku’s streamlined interface and optimized workflows.

Dataiku’s intuitive interface empowers employees at all skill levels, from beginners to advanced coders, to incorporate data insights into their daily work. This accessibility enables teams in sales, operations, and HR to leverage AI confidently, fostering a data-driven culture across the organization. Sales teams, for instance, use Dataiku to enhance order forecasting and better prepare for client meetings. This shift has increased confidence in data-driven decisions and improved overall client engagement, bringing NESIC closer to its vision for an AI-powered organization.

Dataiku's appeal is that it allows users to explore data and its possibilities in a fun way without the sense of entrapment that is often associated with data preparation. Ryotaro Suzuki Manager, Business Creation Division, DX Solutions Business Unit (at the time of interview), NESIC

Envisioning the Future With Data-Driven Transformation

Looking ahead, NESIC plans to expand AI across all business units, applying Dataiku’s capabilities to ESG reporting, IT investments, and aquaculture projects. Since implementing Dataiku, the number of data-conscious employees at NESIC has steadily increased, with more individuals across departments actively engaging with data in their work.

As NESIC moves toward its 2025 goals, Dataiku will continue to play a key role in maximizing value from data, supporting NESIC’s strategy for sustainable growth and innovation. 

In the future, any company has no choice but to not use AI. We selected Dataiku with the expectation that it will eventually be used by our entire company of 5,000 people, and our goal in using AI is to create value from the data by linking it to actions, such as decision-making and changes in business processes. Hirotaka Nakano General Manager of the Business Creation Division, DX Solution Business Unit (at the time of interview), NESIC

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