Unlock the Power of AI for Business
I recently wrote a Forbes article on leveraging the power of AI for your business. In this article, I highlighted two specific items from a broader framework to accelerate the generation of value. The first is the application of design thinking to analytics and AI initiatives. I explained using a realistic use case why it is vital to step back and understand not only the problem we are trying to solve, but also consider whether the solution truly meets the needs of users. In addition, it’s also important to think about the future business strategy and how our technological solution will support that desired direction. The second principle was that of creating closed loop analytics to amplify the ROI of your investments. I mentioned constant improvements of the data sources used for insights generation, and also the actual incorporation of insights into operations. These problems are not trivial so a robust data architecture and data pipeline model is important to set up. To provide a fuller perspective, in this blog I wanted to briefly outline the overall framework for data science that we follow at Ignitho. This framework truly allows us to bring alive our mission of using human-centric engineering and AI to our clients. The framework has 2 parts: The data science loop The underlying principles Together these 2 parts help us unlock the potential of AI for our clients. The article further adds to our journey of igniting thought through Ignitho’s strong focus on AI driven human centric digital engineering and thought leadership in digital innovation and transformation. This comes on the back of Garner’s study on Business Composability and CIO’s increasing dependence on AI for an accelerated business growth – Ignitho’s strong expertise in the area. Enterprises and service providers often struggle with their data cycle management which needs a holistic view and not just restricting within the constraints of the service agreements. Data cycle management when backed by an efficient design thinking principle continues to dominate the AI and Data Science space, keeping the users at the centre of business growth and increased efficiency in business operations. Design thinking and end-to-end data framework generally do not get discussed by enterprises – a major phenomenon that is engulfing enterprises, not for good. In my experience and in sync with what we continue to do at Ignitho Technologies, one needs to close the loop between the following 5 step Data Lifecycle: Data Strategy – Leverage decision insights from data derived out of a solid foundation Data Ops – Create resilient and effective data pipelines Compliance and Security – Reduce risk of data loss and privacy from the ground up Insights Generation – Generate insights that are not just predictive but also prescriptive Insights Operationalization – Making sure the insights are internalized into the right business processes The closed loop Data Lifecycle Framework works as a self-sustaining model with set of processes and constant optimization. But how does one ensure that this Data Lifecycle is brought to life? The value add of bringing the above framework to life is powered by Design Thinking – asking the right questions at the right level and focussing on internal and external user needs. Design thinking when done right, evaluates the customer’s point of view, while also considering the goals and objectives that the business itself needs to accomplish. Not sure how to take the first step towards accelerating your AI adoption? Here’s our short Online Analytics Maturity Assessment which has been appreciated by CXOs across enterprises for the eye opener it has been for them. We are sure it will help you gauge your organisations AI adoption, do give it a try. The results are realtime across 5 dimensions and you can compare how your organisation scored over others. We would love to know your feedback. We are at the cusp of new opportunities coming our way and our POD based tribes led by our CTO, Ashin Antony continue to scale up as experts in AI enabled human centric engineering. We are excited about this journey of igniting thought. Do let us know your feedbacks and queries.
A CIO’s guide to the need for Frugal Technology Innovation in Enterprises
In our previous two blogs in this series, we discussed what Frugal Innovation is, and the five principles that guide Frugal Innovators. While still relatively unknown in an enterprise context, the Frugal approach to Technology Innovation in the Enterprise may just be the golden ticket for CIO’s and business leaders to help escalate the pace on effective innovation at a time of rapid business disruptions caused by COVID-19. CIO’s and business leaders already recognize that innovation is no longer a luxury but a necessity for an enterprise today. Recent corporate history shows that innovation could well be the difference between exponential success or rapid decline in the enterprise. Consider the well-known examples of Kodak and Blockbuster, giants in their time but who no longer exist today out of poor reactions to the changing business environment and consumer behavior. Kodak underestimated the potential of digital photography which later disrupted the entire industry and replaced its film-based photography. Similarly, when Blockbuster CEO John Antioco and his team laughed at the proposal of partnership with Netflix in the year 2000, little did they know what waited for them in the coming years. In an enterprise context, innovation is normally a result of a burning need, an emerging trend or a popular new technology platform, or a convergence of these. For example, look at how the enterprise landscape has changed because of the coupling of a need with a new technology trend, such as gaming, social media and the emergence of super-powerful smartphones and tablets. When mobile took over the user experience factor, businesses had to adapt and deliver mobile-friendly applications to attract and retain their customers. While clearly recognizing the need to innovate quickly, enterprise CIOs face practical challenges in using a one-size-fits-all, big bang approach to all technology innovation. Our discussions with over 100 CIO’s have thrown up the following top issues. Lots of ideas but no sufficient bandwidth to nurture Innovation in an enterprise is often not a problem of finding ideas. In many scenarios, the CIO or innovation group is bombarded with a plethora of ideas coming from various internal sources. The problem therefore really lies in finding the necessary bandwidth to nurture these ideas, to run alongside larger transformation initiatives and business-as-usual. Need help in qualifying ideas and creating business cases The CIO’s we spoke to tell us that they would welcome advice and extended bandwidth to qualify ideas based on factors such as effort, capital, output, and success. Often though, this comes at a high financial cost and may also be time-consuming, resulting in ideas either being dropped or a loss of the window of opportunity. Identifying ideas that require minimum effort and provide maximum output is easier said than done using conventional approaches to innovation. Not enough good ideas that qualify While there may be a long list of potential innovation ideas, sometimes innovators face the issue of good quality ideas. When the success rates of these available ideas are compared with certain metrics such as the effort, capital and output required, many of them fall off the scale, resulting in a lot fewer ideas. Limited budgets can only nurture a few ideas Big bang transformational approaches to innovation are normally very expensive and time-intensive, thereby consuming whatever little budgets were available in the first place. Once again, this may cause other potentially brilliant ideas to fall by the wayside for lack of available budget and resources. No designated budget for innovation in non-core solutions Surprising as it may sound in today’s digital era, CIO’s are still often stifled by the lack of appetite within the enterprise to invest in new ideas. They must work very hard to push an agenda of innovation to run alongside business as usual initiatives. As a result, most ideas fail to get off the ground using the traditional big bang approach to innovation. Frugal Technology Innovation may be the answer Ignitho’s Frugal Technology Innovation methodology (Doing More with Less), built-in conjunction with Jaideep Prabhu, one of the world’s leading authorities and best-selling author on the subject, helps tangibly demonstrate ideas to the business stakeholders using limited resources through Rapid Prototyping, which can be ramped up to Scalable Solutions based on early success. Ignitho’s Innovation Labs, its unique peer ecosystem, and proven high-quality business and technical resources, are already translating business ideas into successful reality for enterprises. Talk to us today to find out more and get started on your own Frugal Technology Innovation journey in your Enterprise.