Democratising Data by Breaking Down Silos

We need to stop taking a siloed approach to data analytics. Silos are inhibiting companies in terms of the successes they can achieve through analytical insights into their data

Companies need to focus on breaking down silos – regardless of how difficult this task may be. This is an increasingly challenging task given the current data literacy divide that exists. In fact, reports from Gartner showcase that by 2020, more than half of organisations will lack sufficient AI and data literacy skills to achieve business value.

One of the most powerful tools in the business world is data. With capabilities to unleash some of the deepest insights when it comes to data analysis, businesses are set to reap the benefits if they learn to utilise their data in their day to day operations. The problem, however, is that data is still in the hands of the few – and not the many.

Putting data into the hands of the many

Whilst data in the hands of a few experts can be powerful, we must question whether this is enough to facilitate positive change. Think of it like this. Business users work with data each day, but are currently confined to basic reporting, reliant on making requests to the data scientists in the organisation when analysis and interpretation is required. This is because they are not equipped with the skills, knowledge or tools required to analyse the meaning of the data.

We need to move away from the existing elitist idea that companies are solely reliant on data scientists to really excel, because this simply isn’t sustainable for the workplace today. In fact, Gartner expects that by 2020, 80% of organisations will initiate deliberate competency development in the field of data literacy to overcome extreme deficiencies. The real value of data can be found when data is made available in a usable format – and crucially, is made accessible to employees across every business division and function.

You may ask why this is the case. Well, data silos cause businesses to be inefficient. Ultimately, in any business, it is not possible to make a data-driven decision without high-quality data to inform it. Within every business, management teams need to be focused on breaking down the pre-existing data silos, ensuring that information is accessible to employees across the company. The more accessible data insights are to business users, the more enterprise-wide value they can get out of them.

No more silos

Ultimately, any organisation can only start to break down data silos by deploying a holistic data strategy. Good data analytics comes from a solid data management foundation. This means understanding that data exists and in what systems. By properly managing, cleaning and combining data, we can then get the right data to the right people, at the right time.

Currently, one of the biggest barriers to this is a lack of data strategy. This often leads to a disparate approach, meaning that basic business questions cannot be answered without significant data preparation work or without specialist data scientists being deployed. Good data management will break down these silos and offer a more holistic view of the data, making it accessible to all. This is often referred to as the democratisation of data.

To achieve real data democratisation, we need to first understand the areas we need to implement change.

  1. Bridging the current skills divide – Companies need to think about whether or not they have employees with solid data management skills before they start thinking about employing even more data scientists. It’s about building a solid foundation before the tower blocks go up.
  2. Use of technology – The right tool for the right user is essential. Most questions do not require a complex deep learning model to answer them. They simply require tools that can surface well-structured data. Whilst there are always going to be some questions that require the input of a highly skilled and trained data scientist, this isn’t necessary every time.
  3. Understanding our data – Disparate systems, transactional messy data, data warehouses and lakes that don’t quite meet expectations are becoming the norm. It’s time to go back to basics. We need to think about the questions we need answers to and start from there. This means caring for data – especially if we want to reap the results.
  4. Changing company processes – Understanding your process is the first step. However, to take it to the next level, we need to map the data that underpins those processes. Where is it coming from and what format is it in? Will this work for the desired outcome?
  5. Focusing on culture – Today, data is no longer a specialism. It’s a fundamental skill expected of anyone in the business world.

Whilst it’s not possible for us all to learn a data scientists entire skill set, it is possible for us to learn the basics. By breaking down existing silos and making data accessible to everyone – businesses will reap the rewards. Ultimately, data is gold. So we need to mine it. It takes more than one person to extract a valuable amount of gold.  What are we waiting for?


About the Author

Joanne Taylor is Director of Digital Strategy at Software AG. The Digital Transformation and Intelligence Platform of Software AG helps enterprises achieve new levels of innovation to adapt to future changes.

 

 

 

 

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