A recent Gartner survey found that 49% of AI adoption still needs to demonstrate business value. The survey also highlighted that only a meager 9% of organizations are AI-mature.
If we look more closely at the AI and analytics deployment landscape, we see that these projects tend to suffer from siloed development processes, where teams work without a single vision. This leads to disconnected solutions that may crack a unique problem but do not add anything of value to larger business goals. The result? The value derived ends up being short-lived.
Building point solutions is no longer the echoing mantra despite the buzz around it. Rather, today, the focus is on building integrated solutions to business problems while ensuring lasting impact.
Data science practitioners need to evolve from providing specialized point solutions to developing comprehensive platforms and products, which enhance efficiency, scalability, and usability for businesses. To achieve this, a product-thinking mindset may be a game changer in how teams operate, develop and implement AI projects.
Having been an active part of the advanced analytics industry, we at Tiger Analytics anticipated this direction by developing strong capabilities in building robust platforms and productized solutions.
Bringing in Product Thinking to Contrast Traditional AI Deployment
When deploying AI, the typical focus is on solving immediate problems or delivering quick solutions. Product thinking takes a different approach, looking beyond the short term and focusing on creating value that lasts. Here’s what sets it apart:
- Holistic integration: Ensures AI works smoothly with current systems and future plans.
- Scalability and adaptability: Builds solutions that grow and change as needed.
- Continuous improvement: Keeps refining and improving based on ongoing feedback.
- Strategic vision: Aligns AI projects with the long-term goals of the company.
Ultimately, AI projects turn into integral components of an all-encompassing strategy
Why Should AI and Data Science Experts Embrace Product Thinking?
At its core, product thinking focuses on the user and what they want to accomplish. Adopting this user-centric approach ensures that AI projects are not just technically sound, but also relevant and impactful in terms of greater user satisfaction and higher adoption rates. A product-thinking mindset also helps data experts align solutions more closely to business objectives and bridge the project value gap.
- It encourages continuous improvement, adaptability, scalability and creative problem solving
- It ensures relevance in a rapidly changing landscape
- It shifts the focus to long-term product quality and maintainability
So, organizations must embed product thinking into their foundation so that they remain aligned with market shifts and are always ready to tackle new challenges lurking around the corner.
At Tiger Analytics, we began experimenting with various use cases, developing AI solutions with a product-thinking mindset.
Using A Product-Thinking Mindset To Enhance Planogram Compliance And Store Digitization
One of the most compelling examples of product thinking in action is our collaboration with a leading American multinational in the consumer goods sector. The client was looking to transform its approach to planogram compliance and store digitization.
Identifying the challenges
Their existing process relied heavily on manual store visits, where representatives would physically inspect store shelves to ensure they aligned with planograms. This process was error-prone, labor-intensive, and expensive.
Hence, the first phase was to establish the objective of building a scalable solution for automating the compliance audit and digitizing store operations through a mobile application.
Developing the solution
In the next phase, we developed a mobile application that could function without constant internet connectivity. The architecture was modular, enabling global features with market-specific customization.
This cross-platform solution leveraged various frameworks, standardizing the process around ONNX for model optimization. It included developing capability modules, such as tools for video analytics, smart annotation, and image stitching.
Our team also adopted an iterative development approach, continuously improving the solution based on feedback. Data challenges, like the lack of historical data for new SKUs, were addressed through few-shot learning and heuristic-based decision rules for rack identification. The result was a high-performance model that could be deployed on mobile devices.
Unlocking the impact of product thinking
Previously, store representatives had to physically visit each location, manually inspecting the shelf layouts. Audit reports were also generated by hand, which only added to the inaccuracies and costs.
With the implementation of Tiger Analytics’ automated solution, the process was streamlined.
Now, representatives can take a picture of the shelves using a mobile app designed for real-time processing. The app immediately checks the images against the planogram, automatically generating key performance indicators that guide them to execute rack adjustments.
Once the adjustments are made, the data is synced to the cloud for instant report generation and real-time monitoring.
Driving measurable business outcomes
This shift from a manual to a digital process reduced the time required for audits from 30-40 minutes to five to six minutes— an 85% improvement. Creating an end-to-end workflow, from strategy to compliance, reporting, and analytics, automated this process across 10 different markets globally.
The accuracy of the audits too improved, rising to 90% from the previous 60%.
On the technical front, the size of the machine learning model was reduced from 25MB when deployed on the cloud to just 5MB on edge devices. Image stitching, a crucial component, improved significantly, reducing the completion time from four minutes to five seconds.
Product Thinking For Data Scientists – The Tiger Way
Establishing a culture of product thinking ensures we deliver services and solutions that are tailored to the dynamic needs of today’s market. Here’s how we are building this culture of product thinking at Tiger Analytics:
- Integrating product thinking into every project
- Crafting efficient and scalable solutions that solve real-world problems
- Ensuring our cross-functional teams collaborate seamlessly, so that each solution is not only data-driven but also built on a comprehensive ecosystem that is efficient and scalable
We believe that embedding product thinking into every project aids us in creating smarter and more responsive solutions and ultimately, refined product development journeys.
Impact of Product Thinking-Led AI: The Time Is Now
Adopting a product-thinking mindset in AI projects can transform how we approach the development process. The focus has shifted from AI projects for short-term pain points to creating solutions that get to the root of the real-world problems and drive tangible business impact. Considering the speed at which AI is becoming an integral force of daily operations, a product-thinking mindset empowers AI projects to thrive – not just survive.
For instance, instead of only optimizing a predictive model’s accuracy, the goal can be expanded to consider how the model can improve user experience, such as recommending products based on customer behavior. This mindset also encourages cross-functional collaboration with larger teams like product management and engineering, leading to better-aligned solutions
Then, instead of only crunching the numbers, AI solutions can continuously deliver insights that matter, help predict user behaviors, fine-tune features, and more. As AI systems learn and improve using the data they process, this iterative cycle of data collection, analysis, and application will strengthen a continuous feedback loop.
Thus by focusing on building a resilient data analytics framework based on AI advancements, tomorrow’s products will be increasingly responsive, predictive, and to business owners’ and data science practitioners’ collective relief, more successful.
