Pump condition monitoring

Client Issue

An international pump manufacturing conglomerate was planning a transition from a product-centric to a service-oriented business model based on the Internet of Things (IoT) technology, Big Data, as well as data analysis and machine learning techniques. The initial step towards this goal was the creation of analytical values in respect of improvement of the pump and pump line utilization efficiency by analyzing historical operational data, technical characteristics of pumps and information on water consumption.

As a part of the project, it was necessary to develop a system of monitoring and control over the condition of pumps and pumping units that would enable analysis of operational efficiency and the causes of pumping unit failures.

DAI Solution

Before embarking on system development, Deloitte consultants held joint discussions with stakeholders to identify system use scenarios, user roles, and the composition of input data required to implement the solution. This helped to minimize the risk of failure or missing project deadlines. At the same time, Deloitte analysts examined the subject area of the task to be able to assess the results of algorithm design and modeling quality quickly and effectively in the future.

As a result of these discussions, the Deloitte team created a step-by-step action plan and prepared a schedule of system development in short steps (sprints) in accordance with agile methodology. The Microsoft Azure cloud platform was chosen to implement the solution. Deloitte experts with extensive experience of working with the platform were employed to clarify the issues of system security and usage. To obtain fast results for the pilot project, the user interface was set up using Power Bi service. Before work on the solution began, the Deloitte team created a detailed system architecture, taking into account the unique nature of the platform.

At the first stage of development, the back-end team of developers prepared effective data stores for different types of input data.

For the pilot project, the client provided a wide range of data on the pumps and pumping line infrastructure: metadata on pumps and pumping units, plant characteristics and pump performance indicators, data on breakdowns and repairs, historical data from pump sensors, etc

In parallel with the back-end development team, data analysts developed a module for pump performance indicators modeling and calculation, and implemented test scenarios.

After the development of algorithms, interactive analytical dashboards were created using the Power BI service based on the agreed-upon user scenarios, with the final version available via web interface through a link. The dashboards reflected the operating condition and performance indicators of the pumping line, as well as individual units and pumps.

As a result, within a very tight time frame, Deloitte consultants developed a system of online monitoring, calculation of the performance indicators and analysis of pumping unit data, making effective use of Big Data components of the Microsoft Azure cloud platform. The results of system module operation were available to users through the web interface in the form of interactive analytical reports created using Power Bi.



  • Cloud solutions
  • Interactive dashboards
  • Agile methodology
  • Data analysis methods
  • Best global practices


  1. Reduction of workload related to manual calculation of pump efficiency indicators by 80%
  2. Tool for monitoring and control over the condition of pumping stations in the form of interactive analytical reports on the operating condition of pumps and their efficiency, available through a web interface
  3. Detailed analysis of the causes of equipment breakdowns based on historical data using data analysis and visualization methods

Shareholders value

Shareholder Value

  1. Revenue Growth
    1. Volume
      1. Acquire New Customers
      2. Retain & Grow Current Customers
      3. Leverage Income Generating Assets
    2. Price Realization
      1. Strengthen Pricing
  2. Operating Margin (after taxes)
    1. Selling General & Administrative (SG&A)
      1. Improve Customer Interaction Efficiency
      2. Improve Corporate/ Shared Service Efficiency
    2. Cost of Goods Sold (COGS)
      1. Improve Development & Production Efficiency
      2. Improve Logistics & Service Provision Efficiency
    3. Income Taxes
      1. Improve Income Tax Efficiency
  3. Asset Efficiency
    1. Property, Plant & Equipment (PP&E)
      1. Improve PP&E Efficiency
    2. Inventory
      1. Improve Inventory Efficiency
    3. Receivables & Payables
      1. Improve Receivalables & Payables Efficiency
  4. Expectations
    1. Company Strenghs
      1. Improve Managerial & Governance Effectiveness
      2. Improve Execution Capabilities
    2. External Factors