In a previous blog, we have covered the need for the fashion industry to take note of the rising competitive advantage offered by data analytics and why fashion brands need to embrace it right now.
However, like with any major technology initiative, implementing a data analytics strategy in your business’s digital backbone is not easy. Data analytics works best when there is a steady and strategic flow of data from across business systems. Such a consistent flow allows analytical modeling of scenarios which is further used for the wide range of analytics use cases we have covered earlier. Setting up this workflow, however, requires careful planning and execution to ensure that all aspects of a fashion brand’s business are covered while data collection happens. That apart, it is also essential to create processes and systems that allow prompt action to be taken based on the available insights. There would need to be processes created to monitor, track, and report on actions.
Let us explore 5 ways for businesses in the fashion industry to get started with implementing a data analytics initiative in their operations.
Set up a culture of being data-driven
As mentioned earlier, the foundation of data analytics is a steady flow of data into the analytical systems. For this to happen, it is important to have every stakeholder in a fashion business contribute their operational data freely without boundaries. From the warehouse to accounting, sales, marketing, logistics, partners, suppliers, and even social media and advertising agencies that work for the firm, there is a need for everyone to be on the same plane in terms of contributing valuable data. For this, it is important to establish a culture focused on data-driven decision-making across the length and breadth of your organization. Every stakeholder needs to be made aware of the need to contribute data and how their contribution adds up to decisions that the business takes after deriving insights from the data through analytics.
Identify the real metrics that need to be tracked
Once all parties within a fashion business agree to contribute data consistently, the next task is to identify the key metrics that need to be tracked to monitor the performance improvements bring driven by data analytics. It could be the turnaround time of raw materials or finished goods, seasonal pricing boundaries, operational throughput of factories, retail space utilization, etc. The real metrics that can have an actual impact on the business’s strategic progress should be tracked and accounted for in analytics initiatives if the right decisions are to be made with the insights generated.
Create data acquisition strategies for different departments
It is quite natural for different stakeholders to be stuck with legacy methods, processes, tools, or channels that obstruct the seamless generation of datasets needed for analytics. Data scientists and technology specialists need to work closely with each department and identify data generation or acquisition workflows that must be set in motion so that a steady supply of data is guaranteed. The data acquisition strategies for different departments may be differing vastly but contribute with due importance to the underlying metrics that have been decided to be tracked.
Invest in the right tools
Today, the market is flooded with options when it comes to investing in a suitable platform for data analytics. Fashion businesses must ensure that they evaluate all options that have a history of successfully serving customers in the fashion industry. This guarantees the availability of the right analytical modeling capacity and data flows required to address the unique nuances of the fashion industry. This precise capability can help in quickly realizing benefits and ROI from the analytics initiative. Additionally, it is important to have the right guidance in identifying and implementing associated business workflows and data acquisition strategies. This will lay the foundation on top of which the analytical tools will operate.
Innovate further as data pools expand
As business operations scale, it is likely to have enough sets of data needed for the enterprise-wide adoption of analytical processing. That said, getting the right amount, quality, and type of data does take time. Businesses need to be patient for their analytical models to be mature enough with rich data to provide accurate insights. It is usually safe to start with pilot programs to see how the data initiatives take hold. That done, it’s on to evaluating findings and tweaking strategies. Over time, when data pools expand, the analytical capabilities can also be expanded. Further, as the business starts to move in a direction dictated strongly by data-driven decisions, more innovative technologies like AI and machine learning can be applied to the analytical systems to boost their potential impact, increase the time-to-value, and cause dramatic change.
The fashion industry can benefit tremendously by leveraging data analytics across its value chain. From predicting trends to ensuring a sustainable customer experience, the possibilities are many. However, the path to integrating analytics into the heart of the fashion business is a long and hard one. It requires a very strategic roadmap that ensures end-to-end coverage of key metrics and elements within the business that are vital for insight generation. Get in touch with us to know more about leveraging the right analytics platform with the right roadmap to realize ROI faster in your fashion business.
