Case Studies
Contents
Introduction: Leading and Scaling Data Innovation
Case Study A: Leading Data Innovation with Culture Transformation in Online Travel
- Organization Overview
- Business Challenges
- Transformation
- Results
- Organization Overview
- Business Challenges
- Transformation
- Results
Case Study B: Scaling Data Innovation with Technology Transformation in E-Commerce and Logistics
- Organization Overview
- Business Challenges
- Transformation
- Results
- Organization Overview
- Business Challenges
- Transformation
- Results
Introduction: Leading and Scaling Data Innovation
Scaling up is challenging. Any organizations that are scaling up in size, locations, operations or products face exponential complexities. In this process of scaling up, data also grows in volume and variety, demanding innovation to more effectively derive value from quickly growing data.
Data analytics is becoming table stakes as solutions have become more open and commoditized. Many organizations in the Asia Pacific region have adopted or experimented with emerging data solutions. Yet, according to a Data & Analytics Report by MIT and SAS in 2016, only 51% of respondents in 2015 believed analytics creates competitive advantages, down from 66% in 2012. Why this decline in perceived benefit? As was indicated in the same study, companies that successfully differentiated themselves through data innovation were five times more likely to have a formal data strategy. A comprehensive and well-executed data strategy is critical to success.
A multitude of concerns face growing organizations. What should your strategy be after encouraging outcomes of analytics pilots, or departmental adoption? What is the most suitable and future-proof enterprise architecture?
Many organizations face challenges in driving a company culture that appropriately supports scaling data innovation across the enterprise. These businesses find it hard to attract and retain talent in this competitive field. A Gartner survey conducted in 2015 found that more than half of business leaders surveyed felt their ability to carry out analytics efforts was restricted by difficulty in finding the right talent.
Without a supportive culture and capable talent in place, organizations start to feel growing pains as they scale at a fast pace. Decreases in employee engagement hinder innovation, and leadership teams often experience friction in releasing product changes to their customers. Internal metrics, such as the number of feature releases per month, indicate a clear slow down in productivity.
Adam Drake takes a prescriptive approach to advising companies on scaling data innovation - one that is tailored to the organization’s current stage in its journey of innovation. As described by one client, Drake acts as both an organization’s emergency room doctor and world-class athletic coach during his engagements.
Highlights
Prescriptive strategy: Drake’s approach is to analyze the root causes of the key business challenges and provide a tailor-made strategy to drive data innovation.
Culture transformation: Drake offers leadership coaching and proposes viable solutions to align culture to strategy in order to attract, hire, retain, and motivate talent.
Extensive domain knowledge: Drake has extensive knowledge in data and technology across multiple industries. He draws from experience as Chief Data Officer and Chief Data Scientist at successful companies in online travel, affiliate marketing, mobile marketing, logistics, and others.
Institutionalize processes: Drake is able to advise on fundamental building blocks of data innovation to operationalize data-empowered decisions.
In-depth technical expertise: Well-versed in data infrastructure technologies, Drake advises on technology investment, designs roadmaps, and optimizes systems for data innovation.
Case Study A: Leading Data Innovation with Culture Transformation in Online Travel
Organization Overview
As one of the fastest growing online travel booking platforms in Southeast Asia, Company A had a young and passionate core team. With a mission to mobilize people, Company A partnered with hotels and airlines to offer over 100,000 routes and hotels in Southeast Asia and beyond. Within four years of its inception, the team had expanded to over 1,000 employees across five countries.
Business Challenges
As Company A scaled geographically at a fast pace, the young executive team had a strong need to grow more leaders internally and attract external talent to support its long term growth. Some executives were unsure about the best ways to organically grow, and felt their job scope becoming increasingly undefined when managing the complexity of a geographically-distributed firm.
Transformation
Drake was engaged to provide executive guidance. In the initial coaching engagement, Drake helped company executives re-evaluate the key elements that drove the company’s mission. To further diagnose current challenges, Drake conducted over 20 one-on-one sessions with the executives’ direct reports during a week on-site.
The sessions uncovered issues in internal culture. Managers lacked the autonomy or sense of ownership to lead as their work was often micromanaged. Some even felt their voices were often not heard. It was clear that building a strong culture to motivate leadership was necessary to reinvigorate the company’s growth trajectory.
Drake presented these insights to the executive team and proposed a number of programs that would strengthen internal culture as well as increase the effectiveness of inbound recruiting. These included setting up an API resume submission process that would filter for candidates with technical knowledge, as well as encouraging current employees to share their knowledge and work experiences through writing journal articles and giving conference talks. This allowed potential candidates to assess their fit in the company culture, thus resulting in a more efficient hiring process. At the same time, encouraging employees to share knowledge and experiences embodied “openness” - a core company value - and also served to demonstrate the company’s innovative capabilities, facilitating corporate development.
Results
“Adam made me understand that large changes come slowly,” one executive commented. “We need to allow experiment, be patient and let people learn to become better decision makers.”
After gaining a better grasp of the challenges the company faced, executives embarked on a journey to develop additional internal leadership. Leading by example, executives became more inclusive and began to listen to new ideas. Instead of micromanaging, executives emphasized the company’s vision but allowed teams autonomy to develop their own specific goals and determine the tasks required to achieve the vision. New processes were set up to ensure review sessions with management occurred, but sufficient autonomy was given to individual managers. In addition, Drake also helped Company A modify their KPIs to emphasize communication skills, and to correctly account for leadership growth. Though driving leadership and employee engagement was a focal point of Company A’s long term roadmap, within a short three months, the executive team had already observed greater openness and engagement within the firm.
Case Study B: Scaling Data Innovation with Technology Transformation in E-Commerce and Logistics
Organization Overview
Company B is an e-commerce and logistics player set out to disrupt the retail and logistics industry in Southeast Asia. The wide range of products carried and its fast delivery have attracted not only a large number of customers, but also notable investors within a short span of four years. Known for its customer-focused approach, Company B strives to satisfy fast-growing customer demand and offer responsive customer support.
Business Challenges
Carrying a wide range of products and optimizing delivery were key to customer satisfaction in Company B. However, fast growing demand started to cause challenges in inventory management. With problems manifesting in physical warehouse space, vehicle availability, and routing constraints, over-stocking of certain products increased while fulfillment rates continued to drop. The limitation of the existing in-house sales forecasting spreadsheet was apparent. Operations spent a lot of effort to make manual estimations beyond the forecasts to improve fulfillment. A more accurate sales forecast became crucial to optimize warehouse space and free up cash in inventory if Company B was to enable continued expansion.
Transformation
Drake and his team of data scientists examined the issues and started to build a new system to replace the in-house sales forecasting tool. The existing forecasts used the same model for all products and was largely based on historical sales. This failed to address the specific characteristics of individual products such as seasonality, variable lead time from suppliers, and product volume.
In the first prototype of the new system, Drake’s team designed an entire set of possible models and dynamically forecasted sales by using machine learning techniques to fit the most appropriate model to the data. Since processing times for over 32,000 inventory items was significant, a Spark cluster was leveraged to handle the computation on a more efficient timescale. This approach significantly improved the accuracy of sales forecasts on over two-thirds of the inventory. However, the models still took nearly 25 hours to process.
To address these issues, Drake’s team further optimized the model selection using iteration and relevant data-processing heuristics. As a result, the machine learning and computation time was reduced to 10 minutes using only a medium EC2 instance. The new version of the solution saved significant cost, processing time, and reduced the maintenance burden for the system. Additionally, it had the capability to automatically extend with new data and product features as the dataset expanded.
Beyond sales forecasting, the new system was also able to recommend optimal ordering times for each product, automatically prompting operations personnel to place orders. This simultaneously maximized availability for customers and minimized overstock storage.
Results
The new system was successfully launched in 2 months. The more precise forecasts significantly improved order fulfillment and reduce redundant inventory. The bottom line was improved by a double-digit percentage on top of the growth rate of the company. In addition, operations saved resources and time in manual ordering, allowing employees to focus on creating greater customer value.
Conclusion
Leadership and data innovation are vital to the long-term success of any company in the chaotic stages of exponential growth. Organizations benefit from an outside perspective and expert guidance in leadership strategies, resulting in increased engagement and talent retention. A focused and scalable data strategy provides valuable internal insights as well as the necessary perspective to anticipate customer needs.
By taking an individualized approach based the needs of a growing enterprise, Adam Drake helps create data-driven cultural and leadership transformations that prepare organizations for scalable long-term growth.