When optimizing your data and analytics tech landscape, how do you balance business outcomes that you need vs those that will differentiate your business? For example, fixing core challenges in the architecture that hold you back vs adding new offerings that make your business stand out?
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The best way to start is to prioritize different projects using a clearly defined rubric. Some of the areas to score are as follows:
How quickly can you get it done
The feasibility around making it happen (based on capabilities and costs)
Alignment with your strategic values and your mission
Expected revenue/margin
Advanced nature of the project (is it a true differentiator?)
Customer interest/requests
Number of competitors in the same space
Looking at those different things, you can score the different projects and then plot them in a quadrant priority matrix (like a Gartner magic quadrant) to understand what things you want to go after. You might need to have a portfolio of scoring dimensions on the tech side vs those on the business differentiation side, and make sure that you have at least some in each bucket reflected. So maybe you have two separate prioritization matrix charts. Or maybe you weigh things differently to make sure that you have somewhat of a balance between the two.
What it often boils down to is resources. If your revenue is the issue, it's like the chicken or the egg scenario: the things that we want to do to increase revenue we can't do because we need to fix the tech stack, but we can't afford to fix the tech stack until we get the revenue. If you don't have the revenue, then obviously there needs to be a conversation about how you get that money.
This is a global problem and to me the 80/20 rule worked well. 80% efforts to fox core challenges as it is your bread and butter. Also this will help strengthen your core capabilities for future technologies. 20% efforts on new value adding features as a delighted for the consumer. This means not just research but providing all resources to successfully implement the new offerings as well.
Finding the right balance between growing the business vs. running the business can often be a challenge. In my experience your cost model here will have a big influence. IT organizations that are directly allocated $$ from lines of business to operate can have far more flexibility vs. those who are only allocated a block of money on an annual basis. In either scenario it's critical to have full alignment between IT and the business on your roadmap and the priority of all the top initiatives throughout the year. IT leaders need to establish a baseline for the minimum spend required to keep the lights on and maintain all existing services. The resources left over can then be allocated across any business-led initiatives based on priority (which should be based on a combination of strategic imperative and expected ROI). Optimally, a PMO organization would be heavily involved in managing this process on behalf of IT/Data leaders.
A complex question. The simple guidance on "How do you eat an elephant?" comes to mind here. The first step is to create a cross-functional collaboration between business and engineering teams to ensure business and "IT" goals are aligned. Evaluate the investment required against the potential ROI. Choose a candidate that can support the Proof of Technology and Proof Of Concept and then agree mutually a way forward(Agile approach). Embrace change management! Regularly assess against your objectives , and adapt to changing needs.
In optimizing the data and analytics tech landscape, a careful balance must be struck between addressing fundamental business challenges and pursuing innovations that set the business apart. In my experience, the first priority is to identify and rectify core challenges in the existing architecture, ensuring a stable foundation for day-to-day operations and scalability. This involves investments in upgrading legacy systems, improving data governance, and addressing data security concerns. Simultaneously, the business must evaluate opportunities for differentiation, considering new offerings or features that align with market trends and customer expectations. By strategically allocating resources, the focus should be on quick wins within core challenges, and maintaining a long-term vision for innovation, organizations can achieve a harmonious balance. Additionally, cross-functional collaboration and an iterative mindset are key elements in ensuring a successful and sustainable optimization journey.