Strengthening your business strategy with data, analytics, and AI

During the recent meeting at American Chamber of Commerce in Costa Rica (AmCham), I shared the evolving landscape of data, analytics, and AI (Artificial Intelligence), emphasizing their role as pivotal tools in modern business strategy and decision-making to 40 participants. In this blog, I added analyst observation and two use cases on the paradigm shift in using AI.

Today, every click, every transaction, and every interaction is a treasure trove of insights. The digital age is amassing data at an unprecedented rate. We harness the capabilities of data, analytics, and AI, to help our customers extract invaluable insights to drive innovation and operational efficiency.

As Chris Howard, Distinguished VP Analyst and Chief of Research at Gartner, highlights, “For example, generative and other types of AI offer new opportunities and drive several trends. But deriving business value from the durable use of AI requires a disciplined approach to widespread adoption along with attention to the risks.” This disciplined approach towards AI adoption underpins the transition from a reactive stance to a proactive one, fostering a culture of continuous learning and innovation.

The synergy of data, analytics, and AI allows businesses to transition from a reactive stance to a proactive one. It’s not just about understanding what has happened but predicting what will happen next. Predictive analytics, a shining star in this new era, is empowering businesses to anticipate market fluctuations, customer behaviors, and operational dynamics, enabling pre-emptive strategies and agile business models. Moreover, real-time data processing is transforming the way businesses respond to evolving situations, allowing for immediate actions, adjustments, and uncovering unmet needs.

Highlighting the real-world impact of AI with Beyondsoft

Our journey in harnessing AI began over five years ago, to drive sales growth through machine learning. One exemplary case is our collaboration with a Seattle-based premium cruise line. Through behavior-backed analytics, we were able to garner insights into the profitability of various amenities, enabling the cruise line to make informed pricing adjustments. This not only increased revenue but also enhanced their ability to upsell new services to passengers with similar profiles and consumption behaviors.

Moreover, our endeavor with a leading low-cost airline showcases the potential of AI to generate more revenue. Utilizing purchasing behavior patterns, we helped the airline identify passengers most likely to opt for additional purchases. This enabled highly targeted campaigns and dynamic pricing strategies, thereby increasing sales. Further analysis revealed new revenue streams, exemplifying how data, when utilized effectively, can significantly impact a business’s bottom line.

Fast forward to today, we’ve enriched our AI toolkit with a chatbot, machine learning, and generative AI, striving to provide accurate and contextually relevant information. The integration of BIOPs™, a familiar AI foundational engine to many of our customers, that houses the auto machine learning framework and facilitates the creation of a diverse range of AI services to the multifaceted AI platform.

AI: The unfurling horizon of possibilities

AI is not just about automation; it’s a canvas of creativity, personalization, and a wellspring of continuous learning and innovation. It enables businesses to craft bespoke customer experiences, and tailor products, services, and communications to individual needs, enhancing customer satisfaction while fostering loyalty and long-term engagement.

In the realm of strategic planning and decision-making, AI acts as a visionary, enabling businesses to foresee opportunities and challenges, and facilitating strategies that are both resilient and forward-thinking.

Next steps

At Beyondsoft, we don’t view data, analytics, and AI as mere tools but as catalysts for innovation. Our approach is holistic. By intricately weaving data strategy, AI, machine learning, and business intelligence, we aim to create solutions that are tailored, efficient, and future-ready. It’s not just about data; it’s about crafting narratives, telling stories, and driving meaningful change.

If you are looking for a leader in data and analytics and would like to consider exploring AI to strengthen your business strategy, tap into our expertise to shape your business outcomes. We’ll help you translate concepts into tangible applications and develop an AI strategy to secure leadership support. Reach out to us today.

References

Serverless architecture Series (Part 2: Deeper dive into serverless architecture)

I hope my previous blog gave you got a good start at learning about serverless architecture. As promised, here is some more information on this topic to enrich your understanding of this implementation pattern. That’s right, in my opinion it is an implementation pattern. Because if you dig deeper, it’s not like there aren’t going to be any servers or backend systems. There will still be functions deployed as microservices, but isolated to a level that it’s easy for it to be scaled quickly.

So what makes an application serverless?

There are essentially four features that help convert your traditional functions and services to serverless. These are:

Zero administration – One of the primary goals of the serverless-based microservices model is to provide the freedom to developers to deploy the code without provisioning anything beforehand, or managing anything afterward. No more dependency on the infrastructure/Ops teams. No concept of an instance, OS running on that instance, or any instance management overheads.

Auto-scaling – Secondly, serverless-by-design lets your service providers manage the scaling challenges. There’s no need to fire alerts or write scripts to scale up and down. This allows for handling peaks and turfs in traffic and also the occasional lulls on the weekends, without any manual intervention. Tech serenity, if you ask me!

Pay per use – The concept of Function as a service provides the ability to compute and manage services based on usage, rather than pre-provisioned capacity. No more paying for idle time. The results could be significant, in some cases up to 90% cost savings over a cloud virtual machine. That’s real business value right there.

Increased velocity – Driven by the quick-to-market needs of today’s business models, this whole concept of being serverless gives developers the proverbial ‘wings’ and enables them to deliver functions on the fly. This is great for the Agile model of proving a functional concept and then designing it further.

To summarize, the major advantages of a traditional cloud model vs serverless are:

Cheaper than traditional cloud – you only pay for the time these functions are running

Scalable – support your business spikes and lows more efficiently

Lower human resources – Once its set and configured, theoretically the system does not need human intervention. You do need to monitor the logs and take actions when the system performs out of the set limits

Focus on user experience – this is key for business. As discussed throughout this blog, the whole concept gives business the ability to be agile in a true sense, allows them to try out new things, and fail quicker and move on to business models that actually work. It’s a win-win for any business.

Is serverless the silver bullet?

Well, not exactly. As with any other new technology, it does come with its own challenges. Some of the obvious ones include:

Vendor lock in – At this point, the cloud service providers do not provide cross compatibility. Why would they? It’s not in their best interest. So as a consumer, you are locked in with the platform where you start. From the developer’s perspective, this is not as bad. Though when they have to integrate with services hosted on a different platform, they may have to negotiate a lot of challenges, such as connectivity, protocols, security and so on.
Learning curve – Serverless is a new concept and it does take some time for teams to ramp up to make the best out of it. Nevertheless, there are new developments happening all the time. For example, there are a Serverless Kit and a Serverless Platform being designed by some experts, which are supposed to ease all the challenges mentioned here.
- Tip: I’ll be covering the severless kit in one of my upcoming blogs. Do keep an eye out for that!

But is it secure?

Absolutely, as long as you make it so.

As the architects would tell you, the details are in the design! As with any enterprise service, you need to design with security as a primary requirement of your application. You need to account for the fact that users will be interacting with this service directly, sometimes using their credentials. So, it is important to clearly understand how to limit what resources they have access to, what they can and cannot read and write.

It is highly likely that your service would be interfacing with 3rd party services, and it is imperative to consider the access to that service. For example, with Firebase (a real-time streaming database), you write custom security rules that are executed by the database engine to determine which users can read or write from different parts of the database. If you are writing your own micro-services, then you need to ensure that your services check the authenticity of the security token passed and verify the rights of the user.

I hope this blog helped you get a deeper understanding of serverless services. I’ll continue with our series in the next installment, covering a toolkit that helps reduce the burden of starting with this great platform. It has an obvious name of ‘Serverless Framework Toolkit.’ Until then, adios!