Interview with Yinglan Tan for an APAC CIO Outlook piece on partnering with enterprise startups in digital transformation.
This article was originally written for APAC CIO Outlook. You can find the original article here.
If data is the next currency, then businesses without digital transformation are still stuck doing barter trading. Pursuing a digital strategy can vastly unlock unrealized customer values, improve customer satisfaction and drive operational efficiencies. However, in emerging markets, the rules of each industry are still set by existing standards and a complex spider web of incumbent corporates, SMEs and sole proprietor family businesses. Thus, businesses embarking on digital transformation can be split according to the following categories:
- Corporates in industries where the adoption of technology is at a more mature stage.
- Corporates in industries where the adoption of technology is still early and most players are beginning to explore digitization.
- Smaller companies or individual business units which would benefit from digitization and have less extensive tech infrastructure requirements.
Matching traditional businesses with the right type of B2B Enterprise startups
With the commoditization of cloud technology, more B2B Enterprise startups in Asia are serving corporates as well as smaller businesses in their digital transformation efforts. These startups solve the different needs within the enterprise’s digital transformation path and adopt different customer service models:
- Enterprise startups providing point solutions that fixes a particular problem or provides a specific function.
- Enterprise startups providing an end-to-end service beyond software licensing. This usually includes extensive customer education and deployed engineers to provide professional services during software implementation.
- SaaS startups adopting a lower touch model where less sales outreach and staff support is needed. This is typically for simple, easy to use solutions with lower technical complexity.
Corporates which are more mature in their technology adoption
Majority of such corporates have their own technology departments with engineers dedicated to managing a full tech infrastructure and information systems which is often driven by industry regulatory requirements.
Corporates prioritize critical functions within the business based on internal and external imperatives. Examples of such functions could be KYC / AML and data security & privacy. Thus corporates require specialized point solutions to innovate on existing solutions to better solve emerging problems in these areas. Relevant enterprise startups in this case would tend to have strong deeptech capabilities which can be deployed globally.
For example, financial institutions in Singapore are required to implement IT controls to protect customer information from unauthorized access or disclosure. In this day and age, a mobile workforce creates problems because the employees’ devices become a backdoor for hackers to indiscriminately access customer information. Startups like Reaqta use AI to power real-time behavioural analysis on remote devices and offers cyber protection on all endpoint threats.
Corporates in early-stage technology adoption
When day-to-day business interactions happen offline and digital data sources from stakeholders (suppliers, service providers, governments) are lacking, it is unlikely that extensive customer data will be tracked. Many less technologically mature corporates in industries are aware of the disruption faced but they do not have the fundamental infrastructure in place, or do not deem building such tech infrastructure as efficient for the business. This type of corporates require end-to-end solutions where customer education can help upper management make data-driven decisions and where professional services can provide customization to legacy systems.
In industries like FMCG and traditional retail, a corporate’s main engagement with end consumers goes through intermediaries or offline channels. Such corporates may have room to improve in terms of meaningful datasets to gain important insights about their consumer’s buying preferences. With the boom in big data, startups like Appier have deployed teams of top engineers with data and marketing expertise to tailor their AI solution for branded corporates across industries like Carrefour, Estee Lauder, Audi, and Minute Maid.
The key lesson here is that corporates can well benefit from working with regional enterprise startups which (i) understand problems faced in the local market and; (ii) employ tech talents who value add functional and technical expertise to the corporate.
Smaller companies and individual business units
With a smaller scale of operation than traditional corporates, smaller companies or individual business units have lesser need for extensive data integration or tedious software implementation into legacy systems. However, many businesses seek a more data centric solution that can transform a certain part of the company’s operations.
In recent years, we have observed some cases where local Enterprise SaaS startups rival global incumbents with highly localized, niche point end solutions. They build features and capabilities which tackle specific problems faced by a particular set of customers. For example, an industry-specific SaaS startup called Intelllex has built an AI-powered knowledge bank that allows lawyers or paralegals to research relevant cases, statutes and commentaries from local and global jurisdictions with a secured system.
Businesses can find the right solution in enterprise startups
Ultimately, digital transformation shouldn’t just be a cosmetic procedure. Corporates do not necessarily need a Corporate Venture Arm or organize hackathons to seek innovation for their business. Likewise, it is not necessary for every business to build a mobile application.
The most important step that each corporate or traditional business can take is to choose an enterprise startup partner with the right solution to their digital transformation needs.
This article was contributed by Tan Yinglan in collaboration with Allen Chng and Dila Karinta.