Head of Enterprise Applications: An Often Untapped Orchestrator for Growth and Scale

Key Insights:

  • Many scaleups are seeing the need for a new role to handle daunting internal systems complexity, back-office business systems, integrations, and data.
  • Hiring a Head of Enterprise Apps and Architecture role in the organization can help scaleups proactively navigate key security and tech process questions while prioritizing growth and innovation.
  • The most common time to hire this function is in the ScaleUp stage — when a company is at $50-$100M annual revenue.
  • This role usually reports to a CIO, COO, or CFO.


Boards of directors are seeking digital acceleration from their CxOs and expect enterprise architecture to be orchestrated to enable growth and scale. For ScaleUps already on their digital path, that means transformation of business processes through technology and the deliberate integration of complex digital landscapes. It also means application rationalization to keep operating expenses in check, especially if mergers and acquisitions continue to be part of the growth strategy.

In early-stage companies, many CxOs must also absorb responsibilities for the company’s back-office business technology in addition to their core role. CxOs in these cases can tend to stand up internal business systems in silos while enterprise applications remain poorly integrated with the organization’s IT infrastructure. The repercussions are significant, resulting in low-data quality for internal users to work with, the inability to produce key business KPIs, and ultimately, a poor customer experience. However, there is a solution: The main strategy for dealing with daunting internal systems complexity is to form an enterprise applications and architecture team, responsible for back-office business systems, integrations and data. The head of enterprise applications and architecture thus becomes the master orchestrator of processes and applications for all business units.

Assessing the Need for a Head of Enterprise Apps and Architecture

The need for a master orchestrator was identified in a 2018 survey conducted by threat-assessment company F5. The survey revealed that 38% of the respondents could not name all the applications used by their organization, despite considering 34% of their web applications to be “mission critical.” So how do you determine if your company needs a head of enterprise applications? Below is a simple checklist:

  1. Unmet technology needs. Does the business have capability needs that aren’t supported by current back-office applications? This can happen as the company matures, when the customer base shifts and departments expand their tooling, both to meet demand and to deliver greater value to consumers.
  2. Software ownership. Scaleups often struggle to decide whether to buy off-the-shelf software or to build it themselves. In some cases, it can make more sense to purchase while, for others, an in-house solution works better. Left unchecked, these decisions can result in complex system landscapes.
  3. Architectural vision. Is there a clear internal vision for the company’s business systems architecture? The company should identify which systems add competitive advantage through advanced “best of breed” feature sets and where cost savings can be achieved with mid-market options.
  4. Gaps and overlaps. Which systems offer necessary features and which are redundant? With off-the-shelf enterprise software there will always be gaps in capability, and some redundancies. The problem goes further than unnecessary spending: if different teams use different software to achieve the same objective, progress can be hampered and KPIs can’t be reconciled. Leaders who are dedicated to managing the life cycle of enterprise applications will be able to identify these gaps and overlaps, and make effective rationalization decisions.
  5. Software integration. Are the company’s enterprise applications interoperable? The ability of applications like ERP systems to integrate with sales and marketing eliminates redundancies in capability and provides the functionality enterprises need as they scale. Business leaders have made interoperability a critical part of purchasing decisions, especially as technology needs evolve with the business.
  6. KPIs. Key performance indicators (KPIs) help you understand whether the company’s enterprise systems are delivering required outcomes. If they’re not, then the ScaleUp will likely re-evaluate the organization’s app development and management strategies.
  7. Projects. Perhaps the strongest signal that the company needs a cohesive application strategy – and leadership – is the failure of systems and data projects to deliver on time and/or to offer the expected business capabilities and KPIs.

head of enterprise applications

Scope of the Role

A head of enterprise applications and architecture straddles a wide scope of responsibilities covering the range of tech strategy. Responsibilities include the choice of enterprise platforms for the organizations to adopt, as well as its implementation and testing processes. Improving DevOps and predictable agile delivery also fall under their purview. They are bilingual, well-versed in the languages of business (including SLAs and KPIs) and technology. The head of enterprise applications and architecture connects back-office business technology to core revenue-generating product applications.

The enterprise applications team will oversee most major enterprise software systems, including:

  • customer relationship management (CRM) systems
  • marketing automation platforms (MAP)
  • enterprise resource planning (ERP) suites
  • human capital management (HCM) tools
  • enterprise data systems (EDS)
  • overall integration layer

This team does not need to own every business system, of course. Instead, they focus on those tools that require major investment, integrations or that affect business processes like quote-to-cash or hire-to-retire. These are tools that need to be properly integrated and governed if they are to deliver maximum business impact. ScaleUps are finding that a dedicated enterprise applications team is the optimal way to accomplish this.

head of enterprise apps-IT scope

As mentioned earlier, a key function of the head of enterprise applications is to navigate the build versus buy decision. While engineering is almost entirely a “build” team (they build the product the company sells), enterprise software leaders often lean towards “buy” in order to optimize cost and deliver the best value. However, some companies do give enterprise applications teams the freedom to build internal tools. As a result, enterprise applications leaders are often well-versed in the intricacies of building, integrating, and deploying software and DevOps.

business and IT scope

Timing Based on Growth and Cash Flow

Exactly when a business will need a dedicated enterprise apps team is difficult to predict. Innovation and scale are significant drivers — innovating and investing in digital transformation are top priorities in today’s tech landscape. For most companies, this point arrives as the company transitions from the growth to the ScaleUp phase, typically with between $50 million and $110 million in annual revenue. In later stages, we recommend a CIO, who reports directly to the CEO.

enterprise apps timing

Not all companies manage this transition successfully. Some continue early-stage practices of bringing in consultants to improve processes, but this is a stop-gap measure at best and, when consultants depart, their expertise goes with them. By contrast, organizations with a unified head of enterprise apps and architecture can avoid this churn. This role can serve as a focal point for specific knowledge within the company about business capabilities and managing enterprise applications.

From a cash-flow perspective, companies that struggle to fund and prioritize this role, often have to divest operationally first before they can re-invest strategically, or ask business CxOs to wear a more technical hat.

Reporting Structure

Many companies that create an enterprise applications team assign it to the CIO’s area of responsibility. In the absence of a CIO, the head of enterprise applications typically reports to the COO or CFO.

The CTO is the least-preferred executive to oversee this critical function. That’s because CTOs need to focus on innovating and driving revenue by building out the core product and finding the right product-market fit.

org chart

How does one find qualified IT leaders to occupy this position? The truth is, it can be challenging. Since this is a technical role, the best candidates will have a technical background. IT operations candidates that have only managed networks, desktops or help desks are not good candidates because they lack the business skills needed to speak to sales, marketing and finance executives.

Enterprise applications candidates will have deep experience building software integrations and navigating the complicated web of interoperable enterprise systems. They will also have experience with global implementations, doing configuration or code reviews, and building out proofs of concept for customer relationship management platforms, marketing operations, finance, and accounting systems. Because of the complex nature of the role and the need for outstanding technical, business and interpersonal skills, you can expect to spend at least three months searching for a qualified head of enterprise applications and architecture.

Aligning Business and IT Goals

The ability to unite the company’s business goals with the IT department’s priorities is a unique and critical skill for a head of enterprise architecture to have. That’s because enterprise apps teams serve the entire organization.

That makes this role strategic instead of operational — rather than just managing the status quo, a good head of enterprise architecture will be able to identify areas of business capabilities improvements and drive long-term business value. These skills are part of a wider trend in IT and business leadership – a radical shift from just “keeping the lights on” to planning and driving growth.

IT and business goal alignment

The process includes the ability to get stakeholder buy-in, especially for large-scale changes such as introducing new ERP or CRM systems, or a shift to cloud-based architecture. It also requires a solid understanding of the rest of the organization’s pain points. The best candidates for this role have the ability to identify and implement solutions that align with the organization’s business priorities.

Security Counts

Another critical skill set is a thorough knowledge of application security. As the number of applications a company uses increases, so does its security overhead and the risk of a breach. The diversity of applications also makes the task of securing them more complex.

Furthermore, since many of these systems are used by non-technical staff (such as sales, marketing or HR) there’s an increased burden on the enterprise apps team to educate staff on proper security, release management, and control procedures. ERP systems are notorious for vulnerabilities because they are large, complex applications often used by multiple teams. Their size and flexibility mean that different departments often configure them with customizations or plugins.

However, integrating these systems is not the only concern. Most modern enterprise software is based on cloud technology, which makes IT architecture leaders with strong cloud deployment and cloud security awareness an asset. The nature of cloud technology means there is some overlap between the IT-focused enterprise apps role and the infrastructure engineering role responsible for providing DevOps support to core engineering. While both enterprise app teams and infrastructure teams might work on cloud-deployed technology, they are very often different cloud environments to manage. Enterprise apps are usually deployed to dedicated, vendor-owned (and made) cloud platforms. Infrastructure engineers, by contrast, work much closer to the code on platforms that deploy the company’s core product.

7 Habits of Effective Data Leaders

CxOs are realizing every executive in the organization is a data leader in the age of digital transformation. Whether their background is in data analytics or not, successful CxOs are navigating this transition by actively engaging with data departments to fill gaps in knowledge. They proactively build a set of practices and habits that drive useful insights. In doing so, leaders have pivoted from a defensive to an offensive data strategy and culture.

Analytics teams previously collected data, analyzed it and offered insights directly to leadership. Instead, modern data teams are much less siloed. They work with, and in support of, multiple executive officers and stakeholders in different departments, in a decentralized way, throughout the company’s digital transformation.

Data Results | By Company Size

How the leadership navigates this spectrum varies from company to company. However, highly effective data leaders have established a series of best practices to guide them through the growth curve, and continue to follow these practices until they become habits. As Pulitzer Prize–winning writer and productivity expert Charles Duhigg wrote in The Power of Habit: Why We Do What We Do in Life and Business, “there’s nothing you can’t do if you get the habits right.”

1. Shift the culture and strategy

The role of data executives can be transformative. Their ability to collect and analyze data, then create real operational value from the business insights that data reveals, makes them a transformational force.  It’s in any executive’s interest, therefore, to embrace data technologies. Every department stands to gain, from finance (maximizing revenues and minimizing costs) through enhancing sales and marketing practices (buyer intent, lead generation and opportunity conversion to order), to the C-suite (organizational transformation, long-term growth, customer churn and competitive strength).

Data leaders rely on data to actively predict customer behavior, and refine their own engagement practices and pipelines. How sophisticated they are often depends on where the organization is in its digital journey.

Data-driven organizations are maturing as they move beyond relying on low-level automation tools such as chatbots, to measure successful customer experiences, using this insight to predict future customer behavior. A 2021 Gartner report confirmed that customer service departments get most value from technologies that analyze customer data.

Objective | Pivot from a defensive data strategy to an offensive, democratized strategy. Approach > Key Objective > Core Activity > Data Elasticity

Data Culture & Strategy | Approach and Focus

2. Refine the business context

The business context in which data is collected is changing too. Increasingly, organizations are focusing on customer-centric research to enrich their analytics strategies. A large part of data leadership has focused on identifying short-, medium- and long-term metrics to better understand and predict customer behavior. Although some customer trends stay the same, others fluctuate, year by year, as the ways customers interact with technology slowly evolve.

shows 7 criteria meant to drive customer adoption.
Data Strategy | Customer-First Principles

In response, business leaders are learning to modify their organization’s operations, sales and analytics strategies and to adopt more customer-focused data solutions. Data pipeline company Rudderstack provides a data platform to help organizations implement this data-driven strategy for improved customer support. The platform allows enterprises not only to track customer data, but to directly engage with the customer.

3. Grow the data pipeline with the company

As mentioned above, data strategies shift as companies grow. Early-stage companies often have a very different set of tactics — and see very different results — than multi-million dollar scaleups. As they scale, though, data leaders realize that the range and level of data-driven insight must scale with them.

Leaders often progress from planning a data strategy that merely harvests data, to one that focuses on action by using data to shape organizational decision-making at every level. This is a crucial transition, as it requires data departments to undergo a fundamental intellectual shift, from being passive collectors of data to active advisors. In this way, data streams and enterprise systems are integrated so that predictive data can actively inform decisions.

Data analytics innovator Kubit, for instance, provides a self-service behavioral analytics platform. It harnesses behavioral insight that allows organizations to optimize sales and marketing conversion.

4. De-silo the architecture

The shift towards more proactive data strategies also involves rethinking the data architecture. Previously, organizations might have organized their data by team or purpose. Now that companies need greater volumes of better quality data, siloed datasets can hinder proper access to the data.

Many data leaders are migrating from a data warehouse-centric architecture to a data lake-centric one. Data lakes provide much greater reporting capability and analytical flexibility thanks to their accommodation of unstructured data. Conversely, data warehouses require structured data while data lakes can accept almost anything: Structured data, unstructured data, media and more.

Diagram showing Data Warehouse (Late 1980s), Data Lake (2011), Data Lakehouse (2020)

Data Architecture Evolution | Source: Databricks

However, the structured data of a warehouse works well for analytics, but is too rigid for advanced AI or machine learning (ML) models to work with. Data lakes are not without their challenges either: They provide great flexibility for AI-driven processes but are unsuitable for reporting dashboards. As a way to overcome the gaps in functionality for both alternatives, the data engineering company Databricks offers data lakehouses for both advanced reporting and agile AI.

Regardless of the implementation, executives are leading the move to a more unified, de-siloed architecture where data from multiple streams and teams can be integrated to inform better decision-making. A new trend is to master customers in the data lake versus the CRM systems, allowing for a complete 360 view of the customer available for real-time AI.

5. Build trust in data

Earlier, we described the growth trajectory of early-stage startups as they scale, in terms of their shift in focus in data strategy. This doesn’t mean, however, that DataOps principles such as governance and security take a back seat. Privacy, compliance and security remain critical to maintaining customer trust in any organization. Data leaders are always sensitive to these concerns and are constantly working to enhance trust in their company’s data policies.

Proper governance is a huge pain point for startups —  Gartner’s 2021 outlook predicted that, through 2025, 80% of organizations will see efforts to scale their business fail because of a lack of modern data governance. To make matters worse, some businesses don’t even have visibility into how effective their governance policies are. Over 40% of executives surveyed had no metrics to measure whether their data governance policies were actually working.

Fixing this problem is an ongoing challenge as executives struggle with perception as much as reality. Every time a data breach becomes public knowledge, company leaders confront a tide of general suspicion and distrust from customers, even if the breach happened to a different company.

Credit bureau Experian, for instance, saw its brand tarnished by the infamous Equifax breach that exposed the financial data of 143 million Americans.

Displays different tiers (lines of defense) for data governance

Data Governance | Prioritization & Lines of Defense

To deal with much bigger threat vectors, executives have begun instituting strict policies at every organizational level: From the adoption of tools like multi-factor authentication (MFA), to precise cloud-access control policies and updated engineering best practices for sensitive data.

Many companies prefer to buy — rather than build — their governance and security infrastructure. Rather than rolling their own authentication and security suites, enterprises opt for third-party offerings like Privacera. Privacera provides a unified suite of access control, data governance and security solutions for data warehouses. This type of third-party, all-in-one solution reduces the workload of a company’s IT and engineering teams by removing the need to maintain and constantly update security code. It also leaves security in the hands of the experts, promoting greater reliability.

6. Focus on people

Building a scalable data department in today’s dynamic, post-pandemic workplaces requires leaders to have an innate ability to collaborate with stakeholders from across the enterprise. Data teams are more decentralized, as previously mentioned, with data scientists embedded within teams from other departments such as engineering, product sales or marketing and finance.

Mission | Establish a Center of Excellence with Standing Teams for ML & Data. Somain Business SME; Product Manager/ Data Analyst; Sata Scientist; Data Engineer

Data Standing Teams | Framework

Just as the remit of the data department has expanded, so has the role of its leaders. Previously siloed chief data officers are now chief data and analytics officers (CDAO), forming skilled teams in an environment where data-driven insight is viewed as a key competitive advantage. And for both growing and large businesses practicing new habits, “Small wins are a steady application of a small advantage,” Duhigg wrote. This collaborative mindset often becomes a culture through the entire department, enabling data teams to work more smoothly with other stakeholders.

7. Drive value

The final responsibility modern data leaders carry is the job of driving consistent and tangible value for an organization. In bringing modern analysis techniques to company teams, data executives have an opportunity to influence genuine change. Evidence shows that by being responsive to customer behavior companies can improve satisfaction, loyalty and drive new revenues.

It’s often the case that one successful project will breed curiosity in other parts of the business. Where successful proofs of concept are adopted by other departments, overall efficiencies are amplified. Data-driven optimization initiatives that help companies transition from insight to action have led to real gains. Driving this kind of optimization helps establish the importance of the rise of data leaders and CDAOs as an engine room for company credibility and growth.

New data habits enable successful digital transformation

The emergence of every CxO as a data executive has cemented the importance of data to a company’s digital transformation. As analysis methodologies become more sophisticated, and the use of data continues to evolve, the ability of leaders to form new habits will be crucial. Storytelling using data and visuals can change a company’s trajectory from being a follower to becoming a leader — as well as a disruptor — in an industry segment.

Note: Insight is an investor in Rudderstack, Kubit, Databricks and Privacera

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