Building a resilient business with data: choose to innovate or risk becoming obsolete
Why should you care?
Human error is inevitable, but is it avoidable? In today’s ever-changing analogue world, full of conceptually complex problems, fuelled by massive information streams and clouded by intangible personal interests, the only constant factor here is the infinite number of variables. Unfortunately, structures with four independently interacting variables is at the limit of human processing capacity. This means that whether we want to or not, we are biologically incapable of fully comprehending the world as we experience it.
Okay, if we dial down the existential dread and focus on business, where does that leave us? How can we reach a state of continuous innovation? To what extent should we leave the current realm of descriptive analytics behind and focus on building an invincible resilient business for the future? It is time to dive into Digital Transformation.
Businesses on Curaçao aspire to innovate. But many are still solving problems by making decisions intuitively and few are relying on Business Intelligence, which generally only provide business’ decision makers with statistical information of the past. Yet, what every business owner wants is a tailored infrastructure that predicts trends and behavioural patterns, while prescriptively provides actionable strategic advice. These are not just buzz words. It is the revolution we are in right now. With the huge demand for talent, the most eager to learn among us are enrolling en masse into online courses on Data Science and Machine Learning. More than 107,000 people enrolled into one course on the online learning platform Coursera on Data-Driven Decision Making in the first 4 weeks online.
The essence of this Digital Transformation revolution is not about digitising mouldy paper contracts, nor is it solely about digitalising current business processes onto apps and online platforms. Digital Transformation is about exploring and exploiting new business models by making effective use of the digital ecosystem. However, it is common knowledge that transformation is risky, costly and requires great leadership. So how can businesses bring this vision to life?
Simply stated, with data.
Data is a business’ greatest asset. Data tests our intuition, challenges us to become better and shines a light to the future. Collected and managed wisely, data can protect us from blind spots. To use it correctly though, business’ need to improve their data maturity and the analytics.
Data maturity refers to the extent to which data is collected, produced, stored, utilised and capitalised on correctly. Different data maturity models leverage different methodologies but all are somewhat in line with facilitating improvements within these four core categories: the purpose of the data activities; the method in which the model is organised and implemented; the skills, behaviour and leadership of the people working with the data; and the tools needed for a proper information architecture. Therefore, for businesses to improve their data maturity scale requires a holistic and systematic approach. In due course, businesses manage their data in a manner that is compliant with proper data governance and are more capable to capitalising on their data-insights.
The analytics scale however, requiring more of an experienced neuro-surgeon than an ER-doctor, might be more challenging to conquer on the short term. Leveraging Machine Learning, Neural Networks and Deep Learning efficiently is key in order to move from descriptively analysing the past to predicting future trends with high probability, with the vision to eventually acquiring the infrastructure that prescriptively provides actionable strategies.
How to start
It is a good argument that an effective path to a resilient enterprise is through a data-driven transformation, with the vision and discipline to eventually reach a state of data-enabled continuous innovation.
A sensible way to start your data journey would be to read everything you can find within this context from reputable sources. Join local initiatives and meetups, such as Curaçao Data Driven, and talk to inspiring local talent like Heinrich Angela, one of the co-founders of the Curaçao Data Driven community. “We need to work together towards a data sharing culture. But it would be easier if there is more sense of urgency.” says Heinrich. The community sees the awareness and momentum increasing, but it is necessary for more people to get involved.
Keep the following pointers as part of your mindset when starting your data-driven transformation:
- Start small, focus on learning.
- Fail fast and iterate with discipline to reach an effective flow.
- Be mindful to not have a clear vision of the end state.
- Have adequate funding available and do not cheap out on talent.
Writer: Tim Q. M. Martina