How To Develop A Custom Data Analytics Strategy For New Zealand Businesses
- September 8, 2024
- Posted by: FOYI
- Category: Blog
Need for custom data analytics strategy
Most New Zealand businesses look to develop their own custom data analytics strategy because of the unique size of the country’s economy, customer base and the IT budget.
What works in the rest of the world is at best a guideline and needs a significant amount of customisation to have any meaningful impact on the business performance.
Why is data analytics strategy important?
Before we begin to go through the steps of a custom strategy for data analytics, here are a couple of insights drawn from our experience that helps in understanding how it all fits in with a bigger picture.
Business strategy Vs technology strategy
Most businesses look at information technology in isolation from the business. Therefore, it’s only natural to consider business and technology strategies in isolation. However, we observed that technology strategy depends on and enables business strategy. They are inseparable.
What makes a good IT strategy great?
In this day and age, data is more important than ever. Most businesses are sold to the idea that data is their biggest asset. Including a robust analytics strategy makes an IT strategy great.
Here are the steps to customise an analytics strategy for your business.
Step 1: Begin with business questions
It all begins with relevant business questions. The scaffolding of the strategy can be built using a set of business questions. A sample of key questions and how they help in drafting the strategy are as follows.
|
Sample Question |
Reason |
|
What does the business want to achieve in the next 3 years? E.g. 50% increase in annual profits, 30% new customers from overseas etc |
Identifies the objective of the strategy. |
|
What are the key outcomes expected in the next 12 months? E.g. 10% increase in annual profits, Identify customer preference overseas etc |
Identifies the tactical quick-win projects for the first year. |
|
Who contributes to and benefits from the strategy? E.g. Head of supply chain operations, Chief Marketing Officer etc |
Identifies the key stakeholders and beneficiaries of the strategy. |
Thus, the purpose and audience of the strategy can be derived from asking relevant questions.
Step 2: Get your budget sorted
One of the major reasons for delaying new projects or stopping an ongoing project is funding. When it comes to projects concerning advanced reporting, data science and artificial intelligence, businesses often consider it a good-to-have but not a must have.
Therefore, addressing the budgetary constraints right at the beginning of analytics strategy is key to understanding the funding limits. This also goes a long way in setting the right expectations for everyone involved.
The budgets allocated to analytics projects are generally less than what is needed. Furthermore, any financial challenge that surfaces along the way is often used to justify funding freezes.
The primary reason for budgetary concerns is lack of visibility into the impact on business performance.
Therefore, the strategy must include measurement of the business impact and a way to allocate/reallocate budget for the execution of the strategic initiatives.
Step 3: Improve adoption with tactical quick-wins
Another major reason for most challenges in any technology project is lack of adoption. Whether it is machine learning or artificial intelligence, for any technology to be adopted, people need to trust it. In order to trust a technology, people must be able to see how it helps them.
Therefore, the first step to adoption is to state how the analysis and insights will help the stakeholders in reaching their goals better. This creates a visibility of the benefits of the technology and how they align with their goals.
Next, the low hanging fruits i.e. the tactical projects with quick turn around and highest impact need to be undertaken first. A 90 day quick-win project improves the confidence in the strategy and thus builds trust.
Thus, the strategy needs to include a path of least resistance by people and highest return for business.
Step 4: Optimise for strategic wins
The final and the most important part of the strategy is to deliver long term i.e. 3 year objectives of the strategy. This is only possible when the key business questions, budget and adoption are all sorted.
The long-term projects must address two key areas of the business i.e. customers and the product/services.
Firstly, the foundational work must be laid out. In other words, the first step is to understand the customers and product/services.
Secondly, the actionable projects must be initiated. In other words, working to move customers to more valuable products from their perspective and more profitable from the business perspective.
Therefore, strategy must lend itself to learning from early successes and build on them for more strategic outcomes
Step 5: Install guardrails for data privacy and information security
Data security and privacy is an underlying bedrock for any technology initiatives. In New Zealand, most businesses transitioning into advanced analytics generally do so using reputable international leaders in cloud strategy such as Microsoft and Amazon.
The technology platforms such as Azure and AWS provide for a robust security infrastructure, it is really the data privacy that needs more careful attention. A good place to source information about what needs to be included is the New Zealand legislation around data privacy.
Thus, partnering with well established software vendors and sourcing information from the New Zealand Privacy Act must be included in the strategy.
In conclusion, every business is unique in its own way and drafting a custom data analytics strategy must include more than just IT department to succeed.