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TDWI Upside - Where Data Means Business

Executive Q&A: Solving Integration at Scale Issues with IPaaS

What role can integration-platform-as-a-service play in unifying enterprise data? Jan Arendtsz, founder and CEO of Celigo, advocates its adoption to automate information access.

Upside: What technology or methodology must be part of an enterprise's data or analytics strategy if it wants to be competitive today? Why?

For Further Reading:

Emerging Tech Trends Pave Path to Integration-Platform-as-a-Service 

Staying Ahead of Data Management Challenges

AI as a Platform-as-a-Service

Jan Arendtsz: Today there are tens of thousands of business applications that are easy to set up to address every conceivable challenge any company faces. However, as each department adopts its own set of apps, the number of apps across the organization grows, creating data silos, broken manual processes, and a lack of visibility.

Making good decisions in a timely manner requires that the right data is in the right place at the right time. Therefore, it is critical for data to flow seamlessly and automatically through the organization. At some point, the lack of visibility becomes unsustainable, particularly when foundational SaaS apps such as CRM, ERP, or human capital management (HCM) are implemented, whose data is touched by many different processes that span across departments.

To address this, many companies spend a lot on technical resources who understand development and APIs in order to connect these applications and automate getting the data into the right place. However, making a technical project of every integration is time-consuming and expensive and cannot easily scale, especially as the number of applications and amount of data in the organization increases exponentially.

When companies are looking to automate how information moves from one application to another, there are a variety of choices. They can automate manually, hard code, or implement point-to-point connectors, but with these solutions they must manage multiple systems.

A better strategy to solve the integration problem at scale is to adopt integration-platform-as-a-service (iPaaS) technologies that allow companies to easily automate processes by standardizing how applications are connected to each other. By providing essential integration functionality out of the box -- such as prebuilt guaranteed data delivery, error handling, data monitoring, and data governance through a visual user interface -- integration platforms remove many technical aspects of building integrations.

A key benefit of leveraging a platform for a data and analytics strategy is that it makes it easier for functional resources who truly understand data to design the architecture and build the integration themselves, with less of a need for bringing developers into the process. In turn, the developers can be reallocated to other, more strategic initiatives for their skill set, such as building products.

What one emerging technology are you most excited about and think has the greatest potential? What's so special about this technology?

We are clearly biased, but we do believe that integration platforms are the emerging technology with the greatest potential when applied to an organization's data and analytics strategy. Although technologies such as AI and blockchain get all the attention, the iPaaS market has been one of the largest segments of the enterprise software space for several years now.

Fluid sharing of information between different parts of the organization and applications is essential to improve decision making. This is where integration platforms shine, why this market segment has been so hot, and why Salesforce paid $6 billion to acquire Mulesoft.

What is the single biggest challenge enterprises face today? How do most enterprises respond (and is it working)?

For Further Reading:

Emerging Tech Trends Pave Path to Integration-Platform-as-a-Service 

Staying Ahead of Data Management Challenges

AI as a Platform-as-a-Service

One of the biggest challenges enterprises face today is the lack of automation of business processes. As companies scale and grow in complexity, there is a constant struggle of trying to do more with fewer people, resources, and time, yet complexity seems to invite the addition of more resources to be thrown at it.

Companies must strike a balance between controlling and centralizing internal processes while empowering employees with the tools they want, and need, to do their work. As a result, they need to find the right balance between keeping control of internal systems in the way that works for everyone so they don't go rogue and create their own ad hoc systems and processes behind operations' backs.

For example, let's say the company creates a controlled, inflexible process for how data must be shared. If this is too technical and requires regular IT involvement to set up and make changes, employees may end up bypassing the whole process by using unvetted file sharing sites and applications or reverting to manual processes.

Although automation is critical for scale, this approach to automation doesn't scale.

Is there a new technology in data or analytics that is creating more challenges than most people realize? How should enterprises adjust their approach to it?

A technology trend that is creating more challenges than people realize is the consumerization of the enterprise as it relates to SaaS applications.

Today, we find ourselves in the second decade of SaaS apps. As consumers got used to apps such as Gmail, Facebook, Box, and Spotify for their personal use-–applications that are easy to use, offer beautiful interfaces, and require no training---it changed expectations of how business applications should work, and enterprise applications began to embrace the new design philosophy.

Over the last 10 years, ease of building, purchasing, implementing, and adopting this new category of apps has led to an explosion of business applications that tackle just about every problem an individual or team may come across.

For example, in 2011, there were approximately 150 marketing SaaS applications. Today, there are over 8,000 applications to choose from.

The ability of individuals to choose affordable, easy-to-use, best-of-breed applications has enabled companies to quickly scale without having to add more resources. The average company has adopted well over 100 SaaS applications across the organization -- many in isolation of each other. As wonderful as these apps are, it is possible to have too much of a good thing. Too many apps has led to the creation of data silos, fragmentation of data, and volume of data.

There is no slowing the adoption of best-of-breed technologies. To adjust, companies need to consider a federated approach to automation. This means there is a central, standardized framework and technology for integration, with a top-down, holistic approach to automation, but that framework and technology also provide a means for individual departments to contribute in building their own automation from the bottom up.

Integration and automation need to also follow this consumerization of the enterprise model, where it is easy enough for every user to participate in getting applications talking to each other.

What initiative is your organization spending the most time/resources on today? In other words, what internal project(s) is your enterprise focused on so that your company (not your customers) benefit from your own data or business analytics?

In terms of business analytics and data, the project our company is spending the most time and resources on today is in business process automation.

Historically, our company spent many hours manually collecting data across different departments to build the necessary reports for analysis. This often would take weeks, with few insights that would come on a relatively infrequent basis.

With our funding round in 2019, our focus has been on scale. In terms of our ability to efficiently make timely decisions based on data, we've needed to make sure everyone has the data they need at their fingertips, so we've focused on a few key areas:

  • Centralizing and automating how our data comes into a data warehouse for analysis
  • Automating how data is synchronized across multiple applications (to minimize manual data entry and errors)
  • Automating more transactional business processes, such as lead-to-cash, which helps ensure there is immediate visibility into the financials of an account, and Customer 360, which allows the customer success team to understand the customer's experience with our company at all times

Describe your product/solution and the problem it solves for enterprises.

Celigo is an integration platform built both for IT and business users that easily connects and automates processes across thousands of applications. It allows users to quickly build, manage, and handoff complex integrations at scale, requiring fewer IT resources and lowering the total cost of ownership. Celigo makes it possible for everyone to have the right data in the right place at the right time.


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