“Outcome-as-a-service” as an answer to drive real value for retailers.
China might have led the way, transforming retail with a combination of online technologies and physical channels, but Southeast Asia is rising fast.
Zebra Technologies’ 2017 Retail Vision Study predicts that retailers will have to enhance their operations via technologies such as machine learning, automation, and internet of things to better the consumer experience, improve inventory management, and increase revenue as well as reduce costs, just to stay in the game by 2021.
Against this backdrop of the rapidly changing retail landscape, KrASIA caught up with Wendy Chen, the CEO and founder of Omnistream to talk about the future of retail.
Omnistream – recently moved its headquarters from Hong Kong to Singapore – is a data+consultancy startup that relies on data to come up with actionable solutions for retail customers in Southeast Asia.
Albert Einstein once said, “Try not to be a man of success but rather try to become a man of value” and this has become the fundamental basis for Omnistream’s revenue model. The startup uses a unique “Outcome-as-a-service” that only charges a client when it’s actually making a profit. For every single dollar of profits made, Omnistream will take a cut of it and this essentially gives retail customers the confidence in the services of this startup. However, this also implies that Omnistream has to be selective when it comes to onboarding new customers or it will risk not earning any revenue.
According to Chen, the demand for constructive solutions to drive growth amongst retailers in ASEAN is there. Specifically, the region’s retail market is projected to hit US$1 trillion in sales by this year.
Yet, among the numerous other data analytics companies and large foreign consultancies/technology providers, few are able to implement solutions with positive measurable outcomes. And that’s the gap Omnistream is looking to fill – the ability to deliver measurable outcomes for clients that lead to more profits.
Omnistream shared with us a case of a convenience store owner who is rapidly expanding in the region, opening up many new stores very quickly. While more stores will enable more sales revenue, they also raise costs that might eat into revenue if the stores fail to optimize their operations efficiency.
Omnistream offers a way out here.
By merging 2 years worth of daily store-level SKU data with Omnistream’s proprietary external data sources (Shopper Decision Tree method), the convenience store chain is able to find the optimal product range for each store. Next, tailoring to the retailer’s specific operational restrictions to provide suggestions.
Ultimately, this convenient store owner would be able to operate in a leaner fashion, reducing stock weight and driving revenue/gross profit growth. In this illustration, the store managed to increase sales by 40% and reduce unnecessary SKU by 23%, after employing a customised solution by Omnistream, the startup told us.
Emerging markets focus
With approximately 20% of retailers in modern trade – supermarkets and hypermarkets that retail FMCGs (fast moving consumer goods) in emerging markets, Chen believes in the wealth of opportunities in ASEAN.
That realisation hit her when she moved back from New York to Asia as a quant trader. Leveraging on her experience with automated trading, she believes that by applying data and automation, there will be many advantages for traditional retail in emerging markets, where data can be used to better the profits of retailers.
However, ASEAN is a fragmented market, bringing along with it many potential challenges. Cultural, government and language differences vary, making it harder to develop a scalable system to grow in the region. Chen shared that while there are inherent differences, these will only affect the inputs. By ensuring consistent output, a scalable system would be possible. And the company has expanded to a few markets in the region this year, including Myanmar, Vietnam, just to name a few.
The ultimate goal is to grow with clients, essentially looking at each deal like a partnership and some of the next steps in play for Omnistream include product refinement, data refinement etc. After all, the term “garbage in and garbage out” runs very true for data and a robust data pipeline is a lifeblood for Omnistream.
Written by Robin Moh
Editor: Ben Jiang
ORIGINALLY PUBLISHED ON KrASIA