To succeed as a business, the right decisions need to be made at the right time, and in today’s world, smart decision making can be made easier by the intelligent analysis of data.
However, to really get the most out of business data, disparate datasets from different teams and across business functions first need to be aggregated and harmonized. If not, data remains “siloed,” and the ability to draw strategic insight from it is diminished.
So, what are data silos and how do you break them down? Let’s have a look:
Defining Data Silos & Their Impact
A data silo is defined as any collection of information in an organization that is isolated from and not accessible by other parts of the organization. Siloed data typically has its own norms, conventions, and terminology, inhibiting a free flow of information and impeding the ability to derive and share insights across business functions.
Consider the following scenario: Company A’s marketing team, by tracking and storing digital and social media marketing metrics, has a deep insight into the segments and audiences that respond best to the company’s messaging, while the sales team has been diligent in logging prospect and client data in the company’s CRM system. However, there is no effort to integrate CRM and marketing analytics data. This results in disjointed efforts and a lack of strategic alignment: Marketing initiatives and messaging fail to incorporate prospect and customer feedback, while the sales team miss out on high-potential segments identified through online engagement.
Data silos like this affect all business functions from HR to Operations, Marketing to Finance, and are all too common. While data silos might be different in every organization, their impact is always the same: suboptimal decision-making leading to corporate underperformance.
Breaking Down Data Silos
In an ideal world, a single software provider could provide a solution to a business’s entire data gathering, storage, processing and analytics requirements. However, the complexity of even the smallest businesses, combined with the availability of low cost, specialist data solutions, means that data silos are – to all intents and purposes – inevitable.
So, while companies should try to standardize data software where possible, a strategy to mitigate the impact of data silos is key for any business that wishes to use its data effectively. There are two essential elements to such strategy: First, technical and second, cultural.
There is no simple, bullet-proof technical solution to data silos, and any solution requires constant monitoring and resourcing. However, you should:
- Consider a Central Repository / Data Lake
Acting as a landing zone for newly discovered information, and theoretically setting the stage for good data management, protection and compliance protocols, data lakes promise to mitigate the data silo problem. However, execution is hard in practice, and some have referred to them as ‘Data Graveyards’, where data remains unused, gathering proverbial cobwebs.
- Be smart with vendor selection
When selecting data-related software, you should always keep an eye on integration opportunities and carefully consider the plan and/or contract before committing so that you remain flexible and responsive in how they collect, store, and analyze different datasets. Also, you should assess the ROI of using integration software, like the MuleSoft Anypoint Platform.
- Democratise your Data
To the maximum extent possible, teams from different functional areas should be able to access and view each others data. Aside from the cultural barrier to this (see below), there is a technical challenge to doing this safely and securely. Yet, it is a challenge worth tackling.
Data silos often correlate with internal fiefdoms in a company, and there may be egos and careers invested in protecting these silos! This is a profound challenge that all businesses need to solve if they want to extract the promise of data-driven decision making. Here are some key tools to break down a silo mentality:
- Write a company-wide data strategy
Consider writing a central data strategy that defines general data governance rules across all datasets and sources. This facilitates communication, transparency, standardization and ultimately better results for data projects across your organization.
- Cross-functional Training
Have your managers participate in cross-functional team training, particular through business simulations, so that they get an insight into the importance of data from (and strategic alignment across) different areas of the business and its relevance to their specific function. Marketing, Sales, Operations, Finance and HR must have no doubt as to how data from other functions can impact and benefit them!
- Democratize your data initiatives
You should take steps to enhance communication and collaboration on data initiatives to ensure that your people are talking to each other about data, and how to best use it to optimize decision making.
Nothing that happens in your business happens in a vacuum. Decisions from one function impact results in another, and vice versa. And so in a world where all decisions should be data-driven, banishing data silos is key. The ability to share insights across departments is a crucial element in developing a truly data-driven corporate strategy and strategic alignment throughout an organization. If you would like to learn more about how your business could be using its core data more effectively, contact the HFX Analytics team today.