31st Mar, 2020
, , Designation
Data has become an essential asset for all organisations. Before discussing anything further, let us understand the meaning of ‘strategy’ – it is a thoughtful plan aimed at changing the current state in order to reach the vision of the future. In other words, all strategies need to start with a vision, which eventually leads to a series of changes, usually requiring innovation and out-of-the-box thinking, to achieve the vision.
Every organisation should have a business vision and business strategy in place before having a data strategy and analytics strategy. Both data and analytics strategy should be aligned to the business strategy and serve the business vision.
There are four areas that we should focus on to know how to get the data and analytics strategies on the same page:
1. Alignment with the business strategy
This is probably the most important aspect, the importance of having data and analytics strategy on the same page is widely accepted, however, its implementation is still a big question for many organisations. This is mainly due to, the business people are not confident in the technology. Alignment can happen only if both sides focus on business results.
2. Architecture: Data Volume Matters
When working on data architecture, comprehending the existing and future data assets is the key. Important questions that need to be addressed here are what type of data is used to solve the business requirement? What is the volume growth in the next 3 to 5 years? In case data sizes are different for different sources and applications, there should be different strategies for addressing each case, with different ways of thinking and planning from the beginning. Given the complexity, the analytics strategy will also change with the increase in data volume.
3. Organisational Structure
As already mentioned, both data and analytics strategy should be aligned with the business strategy. Many times your business strategy is aligned with the client or customer needs/ interest. Therefore, the teams closer to the client or customer demands often have more innovative and new ideas. Hence, companies should have a ‘decentralized’ team structure where Data scientist, IT person, business development work together. The reason for its existence is clearly evident: the decentralised resources will be able to meet the business requirements faster and will be successfully meeting the customer needs as both data and analytics strategies will be on the same page.
4. People: Talent and Culture
People play a crucial role in any strategy and there is no exception. The challenge here is that in order to have both data and analytics strategy in the same place, an organisation needs people who have the technical talent and at the same time have institutional knowledge as well. Building teams with diverse and complementary skill sets at multiple levels of experience should be an important aspect of bringing both the strategies on the same page. Building data competency and data culture is another important aspect in the organisation Most people are capable of working with data within the Excel sheet. For people to access the data efficiently through a common method within the enterprise, the same degree of scope and competency should be created, so that people can take, evaluate and use the data to enhance their decision-making and job performance without the help of technical staff.
An organisation should take a holistic approach to adopt a long term data and analytics strategy with optimal investment, people and processes to continue smooth business growth. After all, as Jim Rohn puts it: “Success is 20% skills and 80% strategy. You might know how to succeed, but more importantly, what’s your plan to succeed?. Click Here to know about B2B database cleansing services by Denave.