How long should data consolidation take?
Twenty-seven percent of manufacturers report spending three to five days a month consolidating data to support category management insights, with a further 26 percent spending a full five days on the task.
That’s according to the third global Category Management Survey from Symphony GOLD, a provider of a unified software platform for omnichannel retail. In the U.S., data consolidation takes notably longer: 31 percent say three to five days; 38 percent report it taking five days.
The survey also found that the demand for increased granularity is increasing while the lead times for performing major and minor assortment reviews are shortening. Sixty-one percent of manufacturers globally reported on average a three-month lead time for major reviews and one month for minor ones.
Moreover, demands from internal teams for analysis is growing with manufacturer organizations, reducing the time available to serve retail partners. When asked how serving internal teams affected their availability to work on analysis and recommendations for retail partners, 57 percent of respondents said that they now felt a noticeable or significant impact on their availability.
Symphony GOLD said the lengthier time in certain regions for data collection could be due to an increasing amount of data sources being reviewed in order to understand and predict customer behavior.
The survey polled over 250 leading CPG manufacturers from across the U.S. and Europe.
Overall, the survey found strong disagreement among trading partners on assortment priorities. Retailers are focused on category innovation through new product development, rationalization, and planogram design in their assortment reviews. CPG manufacturers are keen to drive revenue by increasing distribution and listing opportunities with products that already exist.
Discussion Questions
DISCUSSION QUESTIONS: Do you see the cloud or other technologies speeding up the process of consolidating data for category management purposes? How can retailers and manufacturers balance time constraints with data demands in assortment planning?
Poll
BrainTrust
Ricardo Belmar
Retail Transformation Thought Leader, Advisor, & Strategist
Tom Redd
Global Vice President, Strategic Communications, SAP Global Retail Business Unit
This set of functions should be in real-time (no matter the size of the operation). Queries should take less than one to three minutes as a maximum — no matter the size of the consolidated data.
The cloud and vertical data storage are key elements required to make this happen. When it does — as we have seen many times — it is a joy to watch the user’s response.
While there needs to be extreme and significant heavy lifting during the data consolidation process, this is an absolute requirement when entering into the world of assortment planning, localization, clustering and store planning. Retail merchandising organizations may view this time as an opportunity to perform data cleansing and perhaps a reorganization of their merchandise and organizational hierarchy to better suit the growing organization.
So to answer the question, this task should not be underestimated. Enable your buying and planning organization to be far more strategic and focus on the valuable insights rather than running reports to consolidate data into Excel. Once everything is in motion, and the data has been consolidated, the possibilities are limitless for leveraging these real-time, digital and mobile-enabled insights.
There needs to be a cloud-enabled infrastructure as well as a queue of data ready to be accessed in seconds, rather than minutes. This is the standard that all consulting companies need to meet.
This challenge can be effectively addressed today with some of the technologies you’re hearing about, including machine learning/artificial intelligence. There is quite often no need to rip and replace your assortment planning and other systems and incur that massive expense. What you can do is literally augment your current applications with the help of “cognitive” APIs in a cost-effective way to help these applications “learn” as more and more data is consumed over time. Analysis will be completed in less time with better insights.
This is certainly something crying out for more automation, and more real-time data flows. The cloud (and mobile) have great potential to help with assortment planning. I wonder how much of the overall data demands are being limited by network performance issues vs any people resource issues, especially as the number of data sources increases. The more real-time data needs to flow to the cloud, the more important your network connectivity becomes and the greater impact that has on application performance. If users have to wait for analytics, then the usefulness of that information diminishes.
We find this to be true all too often with the clients we work with, who tend to be mid-size to large CPG companies competing across multiple categories. Typical internal processes for data acquisition, organization, integration and reporting are manual and labor-intensive, so no wonder it’s taking these organizations five days before they get insight deliverables out to the field! Over many years of working with CPGs of all shapes and sizes, we’ve come to understand their pain points in this area intimately … which is why we’ve continuously developed business user-friendly features into our solutions for everything from data prep and integration of disparate data sources to powerful drilldown and iteration capabilities. All of this has been done with an eye toward the end goal of increasing speed to insight, which drives speed to market, which creates competitive advantage.
As the pace of business increases and the retail market gets more competitive, the pace of data to support business decisions must also increase. This means the collection of real-time data to better track consumer behavior and store inventories is required. These are the needed inputs for better decisions on products and inventory for all categories.
As the Internet of Things (IoT) technology continues to roll out, retailers will be able to collect real-time data more quickly and accurately. Then the challenge will be to integrate and rationalize the data and prepare it for the business analysts. The ultimate challenge for the retailer will be how to respond to this actionable intelligence with new products, discounting slow-selling items, moving items to better selling locations and having a responsive supply chain to make all of the recommendations happen.
For once, we see how cloud technology reins in on profits. Big data means big investments for hardware and software over and over again. Moving away from this may seem suicidal to most of the mavens, but a functional approach to the amount of information we need to run a business might be more effective than how to decrease man hours again, and again, and again forever.