FEATURES
Assess The assessment phase allows the user to explore
possible scenarios to understand the tangible improvements in-memory can offer over a current technology:
Identifying and prioritizing business challenges. Where is money really being lost? Through inadequate loss prevention, mistakes at the point of sales, or too many out-of-stock situations? How would one benefit by performing sophisticated data analysis and making decisions in near-real time?
Analyzing available information and identifying any missing data. Where is information stored, and how quickly is it available? Where is information unavailable or not available quickly enough?
Assessing opportunities where in-memory computing could solve specific business issues. How can processes be transformed by analyzing data in real time instead of in days or hours?
A matrix can be constructed that includes the following
information for each issue: business priority; data availability; missing data;
main challenge solved with in-memory computing (big data, timely availability, sophisticated data analysis); and
expected benefit. In the last stage of this process, a proof of concept
should demonstrate the benefits of in-memory technology, validate the business requirements and priorities, and identify metrics for measuring performance improvements to show quick results to the organization. Proving results can in turn drive further buy-in. Moreover, the proof of concept should address transfer of knowledge between information technology and business users.
Build The right technical foundation for in-memory
computing consists of a system landscape that includes a logical and physical-data model implemented on an in- memory appliance with appropriate hardware and software. A proof of concept can generate a prioritized list of business requirements, then ensure that the required data are available, accurate and complete. Once the data are loaded into the in-memory appliance and the analytics are tested, users should closely measure performance and calculate benefits for each trial. This ensures both case-by-case delivery of quick results and longer-term benefits to the organization.
Transform In-memory-enabled scenarios can be rolled out on a
case-by-case basis, introducing new reports and processes to key users in the organization. Users can then make more informed decisions in real time, understanding that this may require a cultural or mind- set shift for employees. Processes and organizational behavior must also change (e.g., prioritization of one-on- one interactions with in-store shoppers using special, targeted offers). One should continue to monitor business benefits and adoption of new processes by the organization, and look ahead for the next in-memory opportunity.
Transforming Retail with Every Customer Interaction In-memory computing addresses the challenge posed
by massive customer and product data, allowing users to collect, manage, analyze, provide, and act on information in the moment, thus enabling real-time decision making. Retailers can have the results of complex analyses and transactions at their fingertips, streamlining processes for real-time effects on pricing, promotions, spot purchases, sales, operations, supply chain, merchandising, and multichannel transactions. The resulting insight allows users to differentiate their business from the competition. In-memory information can be employed to personalize interactions, while delivering the products and services that drive customer loyalty.
INTERNATIONAL COUNCIL OF SHOPPING CENTERS
34 5
RETAIL PROPERTY INSIGHTS VOL. 20, NO. 1, 2013
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45