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6 Steps to Winning at Innovation

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The focus on technology and innovation is so high today that It seems like a new financial technology solution for advisors springs up every month, if not more frequently.

As firms evaluate a dizzying array of ever-expanding options, how can one assess the options and choose and implement those that best suit their needs?

Here are six key insights our team has gained over the last two decades that we believe can help during the selection and implementation processes.

1. Start with a clear strategy.

Clear business goals and requirements help drive the initiatives and measure outcomes.  Beyond that, Initiatives that start with clearly defined strategies for data management, integration and user experience, tend to have a better chance of success.

2.Consider solutions built with the end users in mind.

Gone are the days that a firm can say “if we build it, they will come.” It must already be built, with the users in mind and designed to streamline complex data and workflows between every persona of consideration.

Every role you can consider for the scenario– advisors, investors, executives, salespeople, operations, etc. – needs to be considered from the beginning. For example, automating a business process around customer relationship management will have to include every single persona that touches or interacts with a customer. 

This should ideally consider every aspect of the customer’s lifecycle with the firm, right from the stages of a prospect. Great fintech products of the modern era must make the work of every person easier, providing advisors with tech solutions that create fewer barriers for clients, not more.

3. You need access to your data and programs wherever you are.

It is table stakes now for organizations to enable their users and customers to be able to access solutions from anywhere, anytime. Firms are increasingly favoring cloud-based data and automation solutions. Such models typically enable easier accessibility not just in terms of geographical location, but also provide device independence. 

Most current cloud-based products/solutions offer functionality on a wide array of browsers and mobile devices.  Additionally, such products usually make sure that they stay in compliance with fast-evolving technology standards through regular updates. 

4. A strong integration strategy is critical.

We see that system integrations consistently constitute the most expensive line item in the implementation budget of an enterprise solution. This means it is very important for a firm to get the integration strategy and execution right.

Most organizations have multiple products/solutions catering to different business needs and data requirements. Connecting them together to create a unified landscape is often a complex initiative.

We strongly recommend leveraging pre-built integrations offered by product vendors and considering industry standard integration platforms. Developing point-to-point integrations on a custom basis may sometimes seem like a less expensive solution but may end up being more expensive in the longer term.

Additionally, siloed development patterns of such integrations may result in maintenance challenges.

5. Structure and manage data effectively.

While our industry has traditionally deployed account-centric data models, a very strong trend is to structure solutions more holistically and look at data through a household/client-centric lens. This has to be a consideration right from the planning stages. A good culmination of effective data, integration and user experience strategies will result in data being captured once and shared efficiently with other required solutions on a timely basis.  This improves user productivity, promotes process automation across the enterprise and creates the foundation for clean KPI reporting/analytics.

6. Consider current trends.

While one may deploy a solution based on current needs and challenges, it is always a good idea to watch where the industry is headed and what the peers are doing. We see mature and forward-thinking firms enhancing the intelligence of their technology stack.

Well established data models with clean data can enable organizations to implement machine learning and AI solutions. When done right, these can elevate predictability of business outcomes and elevate service levels.

Classic examples are of pursuing the appropriate advisors to add to the team, or analyzing customer behavior patterns to determine the right service action. Ultimately, these enhancements enable organizations to be more precise in their actions and accomplish more successes with a higher efficiency.

So, as you evaluate the next piece of fintech that you will add to your tech stack, consider these best practices to see if they can add value to your initiative.


Sanjeev Kumar is Co-Founder and Chief Executive Officer of Skience.

(Image: Shutterstock)


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