Modern IT Strategy

Take next steps confidently with a customized modern IT strategy playbook, taking advantage of advances in analytics, AI, and automation

Driver

It can be dizzying to keep up with technology trends, particularly if your team relies on a mix of older and newer solutions. Maybe you have more data than you know what to do with – other than throw it into a spreadsheet and add some formulas and charts. Perhaps you want to take a closer look at generative artificial intelligence, but with fewer complicated techy words.

The FlexPoint team is passionate about deploying technology in the service of people. So, while we are indeed keeping up with the latest generative AI models, and we’ve been working in and around data since data warehouses were cool, we're far more concerned with how advances in technology can serve you and your team. At the heart of our approach is understanding your business needs, matching those to potential technology enablers, and charting an achievable path forward.

If you’re seeking a strategy to make your technology work for you in the long run, we can help.

Outcome

You’ll walk away from this engagement with a modern IT strategy playbook that’s been tailored to achieve your goals.

Your modern IT strategy playbook will include a phased approach to address your specific opportunities to make technology work for you. This strategy and recommendations will be customized specifically for you, so we can’t fully predict the content, but it will include these elements and more:

  • Key stakeholders and how they can be served well by technology

  • Critical insights that stakeholders are seeking, and how we can collect, cleanse, standardize, and serve up information to support decision-making

  • Processes that unlock opportunities, likely with a phased approach to standardize, streamline, and scale them with the help of technology

  • Technology foundation, and the process to modernize, optimize, and transform it with minimal disruption to everyday operations

  • Delivery practices and cadences, being intentional to build on what you have toward effective collaboration across technology and business teams

You can be sure that we’ll recommend making use of data and technology solutions to enhance decision-making, coordination, and delivery in service of key stakeholder groups.

Approach

Our approach will directly address your specific needs and areas of opportunity.

Given the importance of data, analytics, AI, and automation in today’s landscape, here are examples of our approach to addressing each of those in your modern IT strategy.

These are certainly not the only areas we’ll address, but we’d rather be specific about illustrating a few elements than hand-waving toward all of the options.

To address data and analytics, we will guide you through a series of framing questions, including:

  • What are you and your customers seeking to achieve? How do you know if you’re succeeding?

  • What questions take hours or days to answer? What presentations or reports do your team dread each month/quarter/year?

  • What does your current system architecture look like? We’ll focus on core systems and how they’re connected.

Data and Analytics

Then we’ll shift into any gaps between what you want to be able to do and what’s currently possible. Depending on what we find, we can focus on:

  • How to collect, cleanse, and combine data

  • How to bring disparate data sources together for greater insights

  • How to get those insights to the right people at the right time

  • How to take advantage of emergent technologies to level up data-driven decision-making

We'll take a structured approach to exploring key AI and automation use cases, focusing on meeting business needs rather than adopting shiny new tools. This will include discovery and art-of-the-possible discussions with functional and technical leaders in your organization around key processes, data flows, and stakeholder interactions.

AI and Automation

Key Processes

We'll facilitate discussions around key processes, starting with repeated and high-stakes activities as the best initial candidates for AI and automation.

  • What information, activities, and people do these processes rely on?

  • What steps take the most time, or people, or hand-offs? What contributes to this? Can we estimate direct or opportunity costs, even simply level of effort, for taking these steps?

  • Where have we seen errors or rework? What has root cause analysis pointed to on these? What risks or costs are associated with these?

With a good sense for your critical processes, we'll discuss how tools like Robotic Process Automation (RPA), workflows, alerts, and more can help.

Data Flows

We'll also lead discovery and visioning sessions around data flowing into, within, and out of the organization.

  • Where do you rely on information getting from one place to the next? This could be documents like invoices and purchase orders, forms like orders and specifications, and structured or unstructured data flowing between applications.

  • Which of these data flows are predictable?

  • Where have you seen errors, gaps, delays, etc. in processing?

With an understanding of your data flows, we'll discuss how tools like integrations, Optical Character Recognition (OCR), automations, and more can help.

Stakeholder Interactions

Finally, we'll seek to understand critical stakeholder interactions.

  • Where do you have meaningful interactions with stakeholders? This could be prospects, customers, vendors, investors, employees, etc.

  • To what degree does the interaction benefit from well-crafted content? personalization? divergent thinking (like brainstorming)?

With a sense for meaningful interactions, we'll discuss how various well-designed prompts for generative AI chatbots can help.

AI and Automation Case Study

What does this look like in the real world?

We worked with a financial services firm that was seeking to identify ways to protect and gain competitive advantage, as they had seen some disruption by digital-first firms in adjacent parts of their industry.

We examined their key processes, data flows, and stakeholder interactions, and one of their needs ticked all three of these boxes!

One of their core offerings was servicing loans, which includes a lot of predictable, rather tedious activities. Often this included processing similar forms and/or payments each month -- a critical interaction with customers, where errors could result in a loss of trust.

The servicing team was eager to offload these tasks, several of which turned out to be excellent candidates for automation and artificial intelligence. Among our recommendations was piloting robotic process automation for daily/weekly/monthly servicing activities that followed a reliable template. (RPA is a great fit for automating routine, manual tasks, as long as you can specify the steps and/or outputs very clearly.)

We expected some of those to need optical character recognition processing (for instance, of PDFs and checks), which was an additional area where technology could provide a helping hand. (OCR is a corner of the artificial intelligence landscape where machines make sense of handwritten or scanned materials, converting scribbles into text. If you deposit a check and it automatically tells you the amount, hopefully correctly, that was OCR at work!)

In this servicing example, we were talking about a repeated and high-stakes set of activities, that took a lot of time (key processes benefiting from automation) with predictable data flow timeframes and templates, and very meaningful interactions with stakeholders. So, this was a great opportunity to leverage AI and automation.

Interested in learning more?