Questions You Need To Ask About Your Data Analytics Strategy

 

When devising your business data analytics strategy, asking the right questions will steer your analysis effort in the right direction and deliver maximum value to your project. You should look at your data strategy from different perspectives, like data sources and systems, data processing and storage, as well as data visualization and communication. 

These big data questions have the power to connect you with insights and support your business goals.

What current business problems are you trying to address?

Data strategies must be tuned to your business goals. Insights obtained through business data analytics are only relevant when resources are available to follow up on them. Also, make sure to have allocated business partners to understand and act upon them.

Is your core business strategy defined for the next 2–3 years?

Your data strategy must be goal-driven to reduce cloud costs, increase customer conversion, improve customers’ LTV, or research new features. These goals guide your data analytics services team in decision-making in relation to what areas should be researched and reported on.

Are you familiar with the different ways to access your company’s data?

Data can be accessed from the third parties you use. The advanced third-party systems offer data accessibility features through APIs or data extracts, which can be automated. Workday, Salesforce, and QuickBooks come with APIs that let users pull data through an easy and automated process, further facilitating the automation of business reporting.

Do you store data on multiple systems?

Your data can be kept in more than one system. The data can encompass business interactions, transactions, and purchase history. It can even include the pages visited by your clients, their activity and usage of the site, and customer usage of the physical goods, emails, and more.

Do you currently have a data analysis methodology in place?

Tools like Excel are a popular choice among many small and medium-sized companies. Since data can be categorized into three main categories - operational, financial, and customer data, this takes us to our next question:

Do your business data analytics include only the financial data or also focus on operational and customer data?

Financial data may be the easiest to understand and integral to decision-making, but it only tells about the output of actions and not the driving force behind them. For instance, it will tell you an increase in sales but will keep the specifics like the area, product line, or demographic responsible for it private. For this, you need to combine financial, and customer data, which is siloed away, and thus can be difficult to access.

However, a customized data strategy can help put all your data in one place so it’s easily accessible.

Do you keep your data in a central location?

A centralized data storage system is crucial for an efficient business strategy. A data warehouse lets you collect data in one place and create ad-hoc analysis without having to juggle multiple excel extracts every time.

How are you ensuring data quality?

Data quality is often a tough nut to crack, even for billion-dollar corporations, due to the need for definitive data quality guidelines. Nonetheless, it’s important to ensure accuracy in data-driven decision-making, and reputed data analytics companies can help.

Do you regularly or periodically review your data?

A little of both might be the best approach for you. Routinely reviewing metrics and sales numbers enables you to adjust your operations to accommodate market changes. On the other hand, sporadic concerns can only be addressed if your data is centrally stored. Getting the hang of some of the common techniques for data visualization can go a long way toward reaping the rewards of pictorial strengths for making data-driven decisions. 

Has your team established standard metrics or key performance indicators?

Establishing accurate metrics and KPIs requires a thorough understanding of the core business aspects so that they ease your decision-making processes. Data analytics consulting focuses on creating a clean metric that doesn’t require performing complicated math or vague data science output which are never beneficial in the form of KPIs.

Are there questions associated with your business that your team can’t answer or wishes to answer?

What features do customers visit the most on your site? - Businesses often need help to answer even the simplest questions like this. Knowing answers to these questions aids in strategic decision-making, reducing costs and improving revenue.

Do you have a well-defined business data analytics process?

A well-defined process, structure, or strategy will help you set the right approach to answering business questions. In its absence, business data analytics becomes an infinite task giving you an endless loop of questions.

What communication methods do you have to share your data?

Your data analytics strategy’s success is measured by your ability to concisely share your findings with your team. To this end, data analytics consulting professionals can help you create purpose-oriented charts, metrics, and graphs.

Does your team utilize any type of data visualization?

Tools like Tableau and Microsoft Power BI can enable you to neatly present your data and grab attention, thanks to their intuitive UI. Today’s design-driven culture places great emphasis on thoughtfully designed, impactful charts and graphs. It can now be easily achieved through smart data visualization tools.

Does your team include a data analyst, a data scientist, or a data engineer?

Data-oriented companies must have a dedicated business data analytics professional working full-time to help them regularly with analytics, reporting, and metrics. Also, have onboarding documents to support your next data analytics consulting team in the event your data analyst leaves.

Do you leverage modern predictive modeling, analytics, or machine learning?

Your data team can greatly benefit from advanced technologies like data science, machine learning, and predictive modeling. For instance, AWS offers APIs to let you use vision deep learning networks and sage makers.

Could your data strategy benefit from machine learning and other tools?

This question is important to understand if employing machine learning will have a better ROI than simpler data analytics techniques that are more impactful and significantly cheaper. It’s a relevant question as most companies still can’t easily access their data, which is crucial for creating machine learning models.

Do you have any cloud technology in place to keep your team mobile?

The cloud is an important aspect of your data strategy. Cloud-based services, like AWS, allow your team to work from anywhere and at any time.

Do you use cloud technology to leverage scalable computing?

Scalable computing is what makes the cloud an integral part of companies’ data strategy. Instead of servers, you can conveniently buy storage space as needed on the cloud and access it on the go. This is cost-efficient and can be used with your in-house servers and other key technologies.

What's your plan for determining the success of your data strategy and the value provided?

Your data analytics strategy can have a cloud storage layer, dashboards, and machine learning models, but nothing undermines the importance of having an accurate plan that measures your data strategy’s success and value delivered.

Final Thoughts

There exist numerous reasons for nearly every business to review or revolutionize its analytical structures, processes, and reports. However, the right data analytics consulting partner can help you use accurate data insights to answer critical data analytics questions and assist in the development of the complete data strategy. 

Take your business to new, exciting heights with VLink’s data analytics and machine learning capabilities. We specialize in data engineering and visualization solutions and perform web and mobile digital analytics to help you obtain and exploit business insights. Build your data analytics strategy with our tech experts. Let’s connect.