It’s hard to believe that another year is over. 2015 is behind us; 2016 is ahead. As I looked back over this year, I recalled starting last year at the National Retail Federation Big Show. I presented in the SAS booth on “Optimizing Pricing Decisions.” The presentation was simple and used the concept of a lemonade stand to explore the challenges retailers face when executing pricing decisions, embracing price optimization, and finding ways to make strategic pricing decisions profitable. As I thought about the audience’s response, my memory was jogged, and I found myself jogging down memory lane to when I started as a pricing analyst many years ago. Back then, I found myself trying my best to embrace pricing analytics and evangelize a new concept in an organization that was not ready for change. I didn’t know then, but I was about to start my own pricing journey.

Ironically, over 12 years later, many retailers are embarking upon their own pricing journey: A journey designed to discover incremental margin gains, competitive advantage, and increased revenues. However, there are many roadblocks that make success difficult. Here are the most common:

• Poor data quality and insufficient data.
• A pricing strategy that's reactive instead of proactive.
• Limited analytical techniques and skill sets.
• A lack of clear measurements for adoption.

While roadblocks exists, there is a path to pricing journey success that has worked well for the companies I've supported along the way. It’s a four-step process that ensures roadblocks are tackled, challenges avoided, and helps make success quick and easy.

Step one: Data readiness
Data readiness requires the most courage and, sometimes, a leap of faith. This stage elicits sighs, cowering and trembling among even the greatest organizations. The proverbial “garbage in, garbage out” always comes up, because as we know all too well, you're only as good as your data right?!

Fortunately, there are many new advances in data readiness to better harmonize, profile and store data across many disparate sources. With advances like Hadoop or event stream processing, managing big data has never been easier. As you know, your data is your most precious asset. By leveraging it fully, you can improve competitive insights, understand customer satisfaction, and provide personalized offers to customers in localized markets and channels.  This is why the data readiness stage is all about meaningful preparation. Preparation brings perspiration, but perspiration breeds success! The hard work you put in here pays off.

Step two: Pricing strategy
Next to data readiness, pricing strategy is the most critical step on your journey to success. Pricing strategy is more than just setting lofty corporate goals. It's about establishing a strong ‘pricing foundation.’ What are your product's pricing roles? Are they basket builders, margin drivers or value offers, etc.? What is your test and learn approach to measuring strategy success? Pricing strategy employs data-driven insights to set the vision for how analytics and optimization will be applied, along with measurable results to realize adoption. Simply stated by Vance Havner, “The vision must be followed by the venture. It is not enough to stare up the steps - we must step up the stairs.”

Step three: Analytics & optimization
This step is probably the easiest. Once your data is ready and your strategy is clear, you can apply modeling, forecasting, and pricing analytics to provide the insights you're seeking. Scenario analysis plays a vital part in understanding competitive advantage, financial risks, opportunities to localize, and tweaking the right levers of goals and targets to maximize outcomes. The greatest opportunity in this stage is embracing the pricing lifecycle and quantifying the impact along the way. It’s not just about price sensitivity, promotion lift, or setting the right markdown price anymore. It’s about providing a pricing experience that aligns to the customers’ shopping experience, product timing, and channel demands seamlessly. Insights from predictive and prescriptive analytics make it happen.

Step four: Change management
The final step, change management, can be the trickiest if you don’t have a clear pathway for adoption. Adoption is easier said than done; as you begin impacting merchandising and operations processes, showing profitability is just not enough. Taking the four steps outlined here ensures that you create a better enterprise data model for your end users. The result is improved strategy with a clearer vision. As you apply analytics to understand impact and gain new insights, you thereby provide results that encourage greater adoption. My recommendation is to always start small, build internal evangelists within, and ensure there are measurement milestones every step of the way. Change is inevitable, but when fear is removed with measurable results, adoption is won!

Over the next several weeks, I will be uncovering these steps in more detail as we lead up to NRF 2016. I look forward to seeing you there! If not, please join me on January 26 for our webinar: The Price is Right! Omni-channel Data Readiness for Pricing Analytics  where you'll hear from other thought leaders in the space of data management and pricing. Cheers!