1. Start with Compliance in Mind. If you are developing any solutions that depend on data, first identify what legal requirements your customers must satisfy, and be ready for the interrogation from the customer’s compliance department. Identify the customer’s vendor assessment procedures and be ready from the start.
- For financial tech (“FinTech”), your processes (and your business model as evidenced in your contract templates) must meet the complex regulatory requirements.
- For HealthTech, your data collection must satisfy HIPAA’s rules on data collection, storage, usage and destruction.
- For IoT device management, you can minimize security risks by using layers of security in all devices, limiting the processing capacity of the IoT devices, putting the processing capacity in secure servers, and designing the hardware for future software and security updates.
- For consumer data, position your servers strategically (for limiting jurisdictional long-arms) and choose self-certification for Privacy Shield or practical alternatives.
2. Start Lightweight for Agility and Adaptability. You can identify a spot in a complex process (e.g., customer onboarding for banks) and optimize constantly with feedback from customers. The process of customer onboarding is complicated by the need to get data from a broad spectrum of reliable data sources. If you simplify the bank’s compliance with its “know your customer” (KYC) requirements, the prohibitions on dealing with “specially designated nationals” (“SDN’s), anti-money-laundering (“AML”) rules and export and import controls, etc., you will have a big win. The “waterfall” development process works fine if everyone has time. Scrum and agile development require close controls of each iteration. Maybe you might develop an API that is more agile than scrum software, since you are integrating with multiple data sources rather than redefining existing (“old”) methods.
3. Start with Cheap or Free “Big Data”: Find Value in “Digital Exhaust.” People and businesses have become so focused on social media, mobile applications, etc. that you can mine the Internet for data that you might otherwise need to pay a data broker for. Free is better than cheap.
4. Integrate with the “Big Dogs”: Be Disruptive yet Collaborative within the Ecosystem. You can be disruptive and yet add value to enterprise customers within traditional ecosystems. Fill a gap that “big dogs” do inefficiently or with unnecessary layers of middlemen. For example, LendingClub.com uses its own customer evaluation process to generate and issue loans to qualified borrowers and then sells off the loan portfolio for a profit, shifting the future revenue stream and risks to the banks that want to purchase and administer the portfolios. As such, the traditional banks become a distribution channel for new FinTech generators of new loans as a portfolio.
5. Find and Support the Change Agent at the “Big Dogs.” Big companies are in conflict between the need to centralize controls under a CTO or CIO function and the need to be nimble and responsive to customers (the line of business functions). Your sales team should identify the “early adopters” of new technologies and new processes, as well as be in touch with the nominal head of the IT organization. Even if your big customer has appointed an “innovation” department to enable some form of novel thinking, understand that such teams might not have the capacity to be advocates of the changes that the Big Customer needs.
6. Train and Support the “Big Dogs.” Disruptive business models can easily fail without handholding (technical and commercial reinforcement) to ensure adoption and integration of change into daily processes. Don’t let the customer down. Give them a 90-day period of training, support, internal review, adaptation and consolidation of the changes. Otherwise, inertia will defeat the innovation.
7. Use Process Automation for Low-Value, High Volume Tasks. You can get love and affection from the big banks which would prefer to spend their precious skilled resources on devising and implementing strategies for big customers for big fees. You can make good money taking care of the smaller customers whose needs are defined, repeatable, measurable, and time-sensitive and, most important, unloved and uncompensated.
8. Design for Key Performance Metrics. Whether in the Cloud or on premises, design your processes for the most important Key Performance Indicators, beyond the SOC Type II protocols. In the Cloud, flexibility in process integration across data sets and low latency seem to trump other operational factors. Keep processing fast by using few resources and avoiding unnecessary pre-processing of unnecessary data.
The success rate for the integration of disruptive data-driven businesses (typically, startups) with global enterprise customers is very modest. The chances for success can be improved if you simplify processes (at least for the end user), integrate your tools into existing Big Data and economic processes and provide customer engagement and support. If you have all this, you can look forward to faster and more positive evaluation as a qualified vendor and less angst in contract negotiations on limitations of liability, indemnification and risk management.
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