Digital Transformation for Coca Cola Istanbul

Client in numbers

since 2015Member of BIST Sustainability Index
60 yearsFounded in 1964

Problem statement:

  • Optimize processes across the company and streamline everything
  • A partner to co-lead the digital transformation efforts and help deliver several large internal projects spanning Digital Customer Experience, Loyalty Management, and NextGen CRM

Approach and solution:

  • Program structure, goals and progress audit and Improvements Report 
  • Introduced cross-functional squads and increased technical leadership 
  • 4X improvement of the velocity of the delivery teams
  • Enabled monthly delivery life cycles and better management visibility over the progress

Impact achieved:

  • Increased Velocity: Achieved a 4X improvement in the delivery teams’ velocity.
  • Monthly Delivery Cycles: Enabled efficient monthly delivery cycles and improved management visibility over progress.
  • Enhanced Planning: Improved team planning and commitment to the program goals.

Overview:

We partnered with CCI which is headquartered in Istanbul, Turkey and is the 6th largest bottler for Coca-Cola that takes care of the entire production, sales, and distribution. With a total of 26 plants in 10 countries close to 9,000 employees, CCI produces, distributes, and sells sparkling and still beverages of The Coca-Cola Company to a consumer base of 400 million people. 

CCI aspired to become a digital-first company and in 2018 they started a Digital Transformation initiative to optimize processes across the company and streamline everything. CCI trusted us to co-lead the digital transformation efforts and help them deliver on their goals.

Challenges:

CCI had a large IT legacy organization that relied on many different vendors so in 2018 with Digital Transformation as a priority #1, they started a new Digital Unit to perform a major cleanup job across the company and streamline all processes. CCI was seeking excellent external partners that could speed up the implementation of the initiative and help them deliver several large internal projects spanning Digital Customer Experience, Loyalty Management, and NextGen CRM. 

The NextGen CRM project was the highest priority and the first one CCI wanted to kick off. CCI had bought an eBest SFA solution that automates the sales process to increase the sales reps’ efficiencies and productivity, which, however, didn’t exactly meet the needs of CCI and didn’t support integration with CCI’s ERP system out of the box. 

Time was of the essence and all modifications and integrations had to be completed in an extremely tight deadline. The final solution had to meet the needs of CCI and serve all distributors across Turkey and then be launched in all countries where CCI operates.

Solution:

CCI entrusted us to co-lead their digital transformation. We provided tech guidance and consultancy to ensure successful project delivery. Key actions included:

  • Management Audit: Evaluated the program structure, goals, and progress, presenting a Management Report for Improvements.
  • Team Restructuring: Introduced cross-functional squads and enhanced technical leadership.
  • Agile Methodology: Improved requirements gathering processes, procedures, and templates in line with agile practices.
  • Standardized Criteria: Enhanced technical design and standardized DoR (Definition of Ready), DoD (Definition of Done), and acceptance criteria across all teams.

Maximizing Productivity and Profitability for MachineMax

Client in numbers

over 90%Accuracy in predicting machine needs
100,000+Machine hours tracked annually

Problem statement

  • Incrementally refactor the code base and release new features according to new standards without collapsing the legacy code base
  • Extend the existing product with new features and improve UX by enhancing user interfaces 

Approach and solution

  • Developed a new customized UI component system and redesigned the whole UI of the app
  • Enhanced user engagement through detailed weekly analytics and reports 
  • Profound visualization of the data & ML predictions

Impact achieved

  • Custom UI Component System: Created a new, customized UI component system and redesigned the entire UI of the app.
  • Enhanced Data Visualization: Implemented profound data visualization tools.
  • Customizable Email Templates: Developed highly customizable email templates for effective user engagement.
  • Improved UX Satisfaction: Enhanced user experience with new UI tools.
  • Smooth Transition: Achieved a smooth transition from the legacy codebase without breaking functionality.

Expertise and scope

  • Tech Stack: React.js, Redux, Go, Python, Google Cloud Platform, SQL

Overview

MachineMax is an award-winning global company based in London UK that provides an equipment management platform for off-highway heavy machinery users to maximize the profitability of every machine in their fleet… any make, any model, anywhere!

20-30 Million Heavy Machines worldwide are unable to provide meaningful insights to industries such as Construction, Mining, Manufacturing (material handling), Agriculture, Forestry, Waste recycling, and Infrastructure (e.g., ports).

Leveraging Internet of Things (IoT) technology, MachineMax is a breakthrough machine analytics service that helps construction and mining companies maximize profitability by increasing machine utilization and reducing fuel consumption and CO2 footprint.

Challenges

The company has an MVP that worked well and was developed three years ago. After gaining a pool of constant customers and attracting new investors the company decided to extend the product with new features and improve UX by enhancing user interfaces. The old codebase didn’t fit well with new requirements so the company decided to incrementally refactor the code base and release new features according to new standards. That created an issue of properly processing legacy code and incorporating new functionality with the old one. 

The Machine Learning module was added to the product to be able to give predictive analytics based on the deep learning of existing data and analysing trends. Therefore, predictive analytics results should be well represented in the front end.

Additionally experienced UX designer joined the team and worked closely with the existing UI designer. As a result, new flows of usual processes have been developed and implemented in the front end.

Also, the company decided to enhance user engagement and start sending detailed weekly analytics email reports for the users with key indicators.

Solution 

All the new and refactored code has been stored in a separate Portal folder to avoid collapsing with the legacy code base.

There was developed a new Design Component system based on Material UI but customised for its own purposes including supporting several coloured themes. 

Main flows were implemented as multistep forms with a focus only on grouped data with the ability to check selected information in the final step. All main user actions were gathered in the user panel right under the main navigation bar. This user panel contains an icon button for applying filters, searching, downloading reports and adding new machines/groups/geofence etc.

All table pages with aggregate data and dashboard were enriched with sticky horizontal and vertical headers, the ability to scroll by many means (scrollbar, mouse dragging, special button indicators) and a predefined filter and date range. Additionally, new metrics have been added like shifts and off-hours.

Data analytics including ML predictions were implemented with the D3 library for profound visualisation and the ability to see all data segments. The general stats were represented with popular graphs in the Chart.js library.

New email templates have been developed to support images of graphs with data analytics for a week. Also, these templates were optimized to render conditionally supported/unsupported pieces of analytic data with the support of all popular email agents including Outlook Windows. We use a combination of tools such as MJML email framework, Handlebars template engine and integration with Quickcharts.io based on Chart.js.