Blog post

Planning the Algorithmic Retailing Journey

By Robert Hetu | April 28, 2021 | 1 Comment


Retail digital business transformation leaders know that data is one of the most valuable assets, but consistent and meaningful use during the course of business remains elusive for many retailers. Business users across all functions rely on widely varied data sources, sometimes questionable data and often Excel-based calculations to make critical business decisions. Algorithmic retailing connects big data to results through knowledge and insight.

Even if your business is strong you must begin now to understand the dynamics that are impacting the market.  Customer experience has replaced product as king, as product is evolving into an experience. Algorithmic retailing use cases are emerging and yielding results for those who are aggressive and willing to experiment. However, this doesn’t mean a ‘blind start’.  Look for examples in and beyond retail, learn from others quickly and be aware of what is going on around you.

Six Steps to Algorithmic Retailing Success:

  1. Find and Organize Data
  2. Pick the Right Processes to Automate
  3. Automate Existing Business Processes
  4. Target Opportunities With the Largest Impact
  5. Prepare People for Algorithmic Retailing
  6. Redesign Processes

Automation is One of the Keys To Success

While the ultimate goal is to develop modern business processes that are highly automated and focused on new strategic goals, don’t overlook the value of automating the existing process.  This can provide valuable time for business partners and begin the change management process through the benefits of robotic process automation.  

Gartner clients can read the entire research 6 Steps to Tenable and Quantifiable Results Through Algorithmic Retailing

Where they can:

  • Understand algorithmic retailing and its role in the advanced analytics journey
  • Identify 6 steps to build prescriptive capabilities through algorithmic retailing
  • Explore AI and the future of algorithmic retailing

AI use cases are having significant impact on retail  Read my blog on AI use cases

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1 Comment

  • Aussie Joey says:

    Great writeup Robert! Many modern organizations use de-identified data as the biggest source of direction. Especially when key investment decisions are made, it gives us the confidence to use past data as an indicator but most importantly smart algorithm to do predictive analysis based on future conditions. The biggest challenge we face is in finding the correct data sets and using the right algorithms!