What is the Necessary First step in becoming A Data Driven Enterprise?

Today, almost every enterprise aims to become data-driven. According to McKinsey, a data-driven enterprise is 23 times more likely to acquire new customers and 19 times more likely to gain more profits. But how to achieve that? Can generating data alone add value to the business? As data grows, the enterprise creates several islands of data i.e., the data gets distributed across the enterprise. Connecting these islands of data has become a complex challenge for enterprises. Given the complexity of the enterprise tech ecosystem, the data also tends to become inaccessible across functional and departmental boundaries. This challenge has increased the need for connectivity for the data to be more useful to business users. It has created a situation where a data-driven enterprise has to start by becoming a connected enterprise.

Infosys, in its role as a system integrator for large enterprises, defines a connected data-driven enterprise as the one that brings meaning and context to different types of data and aligns them with specific functional needs to create an intelligent ambiance. To that, we could add that the connectivity is driven by the need to create business processes and workflows that are centered on the people using them, rather than the technology that makes them run. The process of becoming a connected data-driven enterprise is not easy. It could take months to reach that level. Let’s look at what enterprises can do to transform into a connected enterprise.

How Can Enterprises Become A Connected Enterprise?

  1. Create a roadmap and build an architecture for transformation

The first step towards becoming a connected enterprise is to develop an architecture and a roadmap on how the implementation will take place. Assess the existing capabilities of the enterprise, understand how the data is being used across various functions, and create a roadmap on how the data can be integrated to create a connected enterprise. A key area of focus must be enterprise users. Understanding their challenges as they go about their normal tasks will give insights about the hurdles they face due to a lack of data and where they could get that data from in a connected enterprise.

  • Identify the resources who will lead the transformation

Once a roadmap is created, the next step will be to identify the resources that will lead the transformation process. Each function should be represented while creating the transformation task force. Every function uses its own set of tools and systems. For example, the HR team will be using a completely different system than the one used by the finance team. So, it’s important to build an ecosystem that connects all of them together. That is the very essence of the problem to create data accessibility. To do that, the enterprise should:

  • Bring all the relevant stakeholders together on the same page
  • Explain the concepts of design thinking and experience to build their capabilities
  • Create data standards
  • And define boundaries of interaction for each function, action, or events
  • Find the right technology approach, like iPaaS

To ensure the seamless exchange of data across various functions, it is important to ensure that the data is exchanged at a quick pace to ensure that it does not become redundant. To achieve this, an enterprise must invest in the right technology approach. For instance, a next-gen iPaaS solution will help all the stakeholders build out their own workflows that contain connectors to varied enterprise systems. This will create an ecosystem that is flexible, scalable, and agile.

  • Prepare for change management

To become a truly connected enterprise, every function must take ownership to drive change management within their teams. For example, once an enterprise becomes data-connected, the different functions cannot work in silos. We have spoken of how business users could leverage the power of the iPaaS solution to easily create powerful workflows. The need for business agility demands that these workflows span functions and bridge systems. This calls for a more responsive enterprise. The simplest way to initiate change management and create awareness is through training workshops and simulations. The key to a successful change management exercise is to reinforce it by practicing it on the job. Create a continuous feedback loop to ensure that every function truly understands the significance of this transformation and cooperates in building a connected enterprise.

  • Measure the outcome and improve continuously

Once an enterprise becomes connected and employees get accustomed to the new culture, it’s time to measure the outcome of the exercise. One way to monitor it is by measuring the value driven by each function. For example, has connecting data islands helped sales and marketing teams to get aligned and generate more sales? Are the product teams and customer service teams collaborating more and exchanging more data to improve the customer experience? Connecting enterprise systems will bring forth all the data needed by CxOs to get a transparent and real-time picture of various organizational functions. This will help create better tracking and monitoring. Monitoring the outcomes driven by creating a more connected enterprise will help determine the success of the whole exercise and make further improvements to grow to the next level.

Conclusion

Transforming an enterprise into a data-driven enterprise must start with creating a connected enterprise. This requires building integrations between complex enterprise systems. But it’s not scalable to have to do this by building custom connectors every time. The need is for a powerful technology approach, a no-code iPaaS platform that business users can leverage. This will allow the enterprise to:

  • Build powerful workflows spanning even the most complex technology apps within the enterprise by connecting various systems in the enterprise’s tech stack – without any coding.
  • Free up their IT team to focus on more complex and value-added tasks.
  • Maximize ROI from sunk technology investments
  • Achieve data-driven, real-time decision-making
  • Save time and efforts of enterprise users through automated workflows that deliver better business outcomes.

That’s why when you scratch the surface of an enterprise that claims to be data-driven, you will find a connected enterprise.