Most businesses shy away from tinkering with their data strategies because there is too much at stake especially for businesses relying heavily on digital technologies. That is why it is imperative for businesses to create a data strategy with caution and care.

You don’t want to end up creating a data strategy that needs to be completely revamped every year. Yes, there is nothing wrong in making small changes to the data strategies but you can not afford to create a new strategy from scratch every year.

So, how can businesses create a winning data strategy? By avoiding some of the common mistakes. What are these mistakes? That is exactly what we are going to discuss in this article. In this article, Anti-Dos will learn about seven mistakes you should never make when creating a data strategy for your business.

Table of Contents

7 Common Mistakes You Should Never Make When Creating a Data Strategy
1. Ignoring The Mission and Goals
2. Not Leveraging Unstructured Data
3. Data Silos
4. Decentralized Data Teams
5. Neglecting Data Governance
6. Poor Quality Data
7. Lack of Visibility into Real Time Data

7 Common Mistakes You Should Never Make When Creating a Data Strategy

Here are seven common mistakes you should avoid when creating a data strategy for your business

1. Ignoring The Mission and Goals

One of the biggest mistakes businesses make when creating a data strategy is neglecting the mission and goals of the organziation. This is one of the main reasons why their data strategy fails. Businesses need to understand that data strategy is not all about collecting and analyzing data. Yes, it is an integral part of your data strategy but there is much more to data strategy than that.

With no mission, businesses will find it difficult to prioritize their data initiatives. As a result, they could not allocate the available resources efficiently. Moreover, this makes it harder for businesses to keep their employees engaged and focused. All this can take your data initiatives towards failure. Data strategy must closely align with business mission and goals and enable businesses to achieve those goals.

2. Not Leveraging Unstructured Data

The sheer amount of data organizations collect, analyze and store is mind boggling. The problem is that most of this data is in unstructured form. This makes it harder for businesses to make the most of that data. Secondly, most businesses collect data for the sake of it. With no purpose behind data collection, they end up with a pile of unstructured data that they won’t use.

If you are collecting data, make sure you know the purpose and have tools and processes in place that can help you make sense of large volumes of unstructured data. Otherwise, there is no point in collecting data in the first place. It would only add to your hardware bill and provide no value to your business.

3. Data Silos

Every business has different functional units and each has their own data and systems. Since all these systems work in isolation and are not integrated, this creates data silos. As a result, one department doesn’t have access to the data of other departments. This leads to operational inefficiencies and inconsistencies, which can hamper your business progress.

Consolidate all these systems into one and create a unified data environment. This makes data more accessible and easier to manage. Moreover, it can provide you visibility. This can assist your business in identifying issues and fix them before it can negatively impact your business progress.

4. Decentralized Data Teams

If your business has many small data teams working in isolation, it can create issues for your business. You will struggle to scale your data strategy. You need data teams to collaborate, share information and work together to achieve a common objective.

When data teams work together, it will refine your processes, give you access to actionable insights and remove frictions and obstacles that are preventing your business from achieving its goals. This will make your business operations more efficient.

5. Neglecting Data Governance

The quality of data and inconsistencies in data along with compliance and regulations can all impact the effectiveness of your data initiatives. If your data have quality issues and does not ensure compliance and meet the regulatory standards, your data initiatives and your data strategy will fail. That is why you must always keep data governance at the heart of your data strategy.

Start off by creating a data governance framework. This will make it easy for your business to create and implement guidelines to ensure data accessibility, security and accuracy. You can even use data intelligence platforms in order to manage data governance and compliance requirements. To secure your website from attacks, you should get advanced malware protection.

6. Poor Quality Data

Quantity of data is not as important as quality of data. Just because you have collected tons of data does not mean that you can extract useful insights from it too. You need high quality data to help you make the right business decisions at the right time. If the data you have collected have quality issues or contain bias, it can force you to make wrong business decisions. That is not what you want as a business. Use data clearing tools to remove all the inconsistencies from data sets, normalize, structure data before using it.

7. Lack of Visibility into Real Time Data

The rapid pace of evolution in the business world forces businesses to have access to real time data. Sadly, businesses who have access to real time data lack visibility into it, which makes it useless for them. As a result, businesses end up missing opportunities and could not capitalize on them.

They fail to anticipate customer demand and deliver personalized products and service offering along with efficient customer support. Businesses must have a solid understanding of different stages involved in the data lifecycle to do a better job at it. Keep the stakeholders informed about upstream data movement in real time so they can enjoy visibility into real time data.

Which of these mistakes have you made when creating a data strategy for your business? Share it with us in the comments section below.