Why A Data Strategy Is Important To Have
Today most companies globally have realized the value of data and have started thinking about how to use it for better decision making. However, realizing its importance and being able to use it strategically are two different things. And this is exactly where most companies falter.
We are also familiar with the term “enabler” – technology is an enabler that allows us to better do what we do. It is actually the ability of technology to process huge volumes of data at great speed that makes it an “enabler” for efficient delivery of products and services.
We all now know that data is being generated all around us at amazing speeds. In fact, 90% of all the data we have today (more than 2.5 billion gigabytes every day) has been generated over the past 5 years or so – such is the speed. One can imagine that the efforts needed to collect and analyze this data would be enormous. And this is precisely why it needs to be done strategically. The main questions to ask are:
- What type of data is needed?
- Where to find the data?
- How to collect and structure the data in a manner that it can be analyzed for a specific purpose?
- Who in the company should have access to what type of data?
- How can this data be analyzed?
- How can insights been gained from the interpretation of the analysis?
Data on its own is not useful. Its like a library (data lake?) where the books (data) on their own will teach one nothing (no insights) unless one selects a book on the subject one is interested in (the right type of data?), read it (interpret/analyze) and then draw conclusions from what one has read (insights?).
Similarly, depending on the type of business and the target clientele, a company should source, collect, analyze, interpret and gain insights from relevant pieces of data.
This is where technology comes in. In 2018 we all speak about leveraging technology the improve the way in which we deliver products and services (finance, health, groceries, transactions, etc.). We are also familiar with the term “enabler” – technology is an enabler that allows us to better do what we do. It is actually the ability of technology to process huge volumes of data at great speed that makes it an “enabler” for efficient delivery of products and services. It is therefore important that we are sourcing and processing data that is relevant to what we want to achieve (the age-old “GIGO” principle). And that is why it is important to have a strategy around the use of data – and this strategy must be aligned with both the business strategy and the digital strategy of the company. The business strategy itself must also be data driven.
Let’s take an example of a bank whose business strategy is to increase its share of small businesses from 20% of its portfolio to 30% (in numbers) over the next five years. Let’s assume that this means they need to acquire an additional 10,000 new small businesses. To achieve this growth, the bank must onboard new clients and offer them the relevant products and services. Today, this is much easier to do by leveraging the enabler (i.e. technology). But the bank would need to first identify the type of technology that is required, and then leverage that particular technology (i.e. have a digital strategy). Again, lets assume that for the bank the biggest pain point is the KYC requirements and the credit risk assessment of the new clients – both of which are time consuming and cost a lot. So, the digital strategy of the bank would (amongst other initiatives) prioritize the digitization of these two processes (KYC and credit risk assessment). Thus, the digital strategy should identify leveraging of the appropriate technology that is aligned with the business strategy. In terms of the data that the bank would require for processing both the KYC and credit risk assessment, the bank’s data strategy should identify what type of data is needed, where it can be found, how it can be analyzed and interpreted to gain insights into the behavior, demand, credit appetite, credit history, etc. of these new clients. Such data analytics while being more meaningful would also enable the bank to: (i) much faster on-board new clients; (ii) offer credit and other products to them in less time (quicker turnaround); and (iii) reduce costs owing to higher efficiency. Hence, having well thought out strategies that are aligned with each other enables the bank to meet its objectives on increasing its penetration into the small business segment within a specific period.
In summary, before companies start their digitalization journey (which they must to stay relevant in the face of enhanced and rapid disruption and competition), it is important that they first ask the questions “why?”, “what?” and “how?” and then commence this journey by formulating appropriate strategies that are relevant to their business needs and in line with the targeted segments of the market.