Where do search firms struggle with data?
It's a story as old as time; bad (unorganised) data in, bad (spotty/ineffective) data out.
“Bad Data” has acted as a blocker for search firms for too long, causing serious long term consequences like slower client growth, frustrated teams, and missed opportunities for the firm to demonstrate market expertise.
It's an obvious [and frustrating!] statement.
So why is this the case? Can 2026 FINALLY present real solutions to this problem?
Let's first identify where search firms struggle in collecting and organising data. Next, let's apply some needed (and business critical) context by asking:
How can these data pitfalls prevent overall growth?
Why doesn't the use of AI make this problem go away?
…and (the question we all want to know)
3. What are some strategies to combat bad data habits?
A land of new [tech] opportunity
As we enter 2026, the tech landscape is looking more like a "land of opportunity” previously not seen. AI empowered tools and systems are changing the game, ensuring everyone can be part of the data revolution. It’s now more possible than ever to start building your “one source of truth,” and FINALLY drive business through your CRM and overall search execution tool suite.
So if you're now asking yourself, “great - so where do I start!?” consider understanding how “healthy” (i.e. how complete, organised, & structured) your data really is (check out “Data Quality in AI…” for some additional reading on this topic!) and where your data actually lives across your systems. After all, how can you expect your business to successfully embrace AI empowered technology if 1) you don't know what data it's drawing from and 2) it's not getting captured consistently across the firm?
Insights generated from AI don't come from nothing! Unpacking data health [as it relates to search] is akin to getting a health diagnosis before you select a medicine - only when you know what's causing the symptoms can you then come up with a plan for finding a cure.
So let's dig in: where exactly do search firms struggle with data capture?
Collecting Market Intelligence
Tracking and aligning compensation data
We've all been there - you've been speaking with candidates for years on multiple searches, and then you're asked to consolidate the compensation data…and you honestly don't know where to start! Frustration and panic set in; and you spend 10 hours manually scraping all of the data you can find to put together a report you know has some major holes…Re-surfacing general market intel
Need to pull up company competitor insights quickly? Consolidating market intel can be a difficult task at the best of times. What's more frustrating? Not knowing how to re-surface juicy conversations without remembering who said what, and where it's all kept!
Research
Tracking where you've been on an assignment
It's all sun and roses when a search is going smoothly. But when a search goes sideways and you need to demonstrate how you've mapped the market (and make sure your team is aligned on next steps), the inability to “show your work” on any given assignment can seriously make recovering an assignment a difficult task.Target list creation
You know you've got a great list of target companies for this next search somewhere - but where is it?! Perhaps your CRM doesn't have a great way to collect them, or you haven't even bothered to put in the CRM as you prefer working in excel. Instead of spending a few hours finding where it lives, you instead go back to creating it from scratch…again.
Business Development
Demonstrating your firm's expertise
You know you've done loads of work with a few clients, and you need to demonstrate that breadth of experience for your next pitch (in 2 hours!). Instead of going to the system (because you know your team has logged this information across multiple systems) to find what you need, you desperately call a team meeting to brainstorm and manually think through relevant placements to include.
Knowing who your team is speaking to!
You're a new consultant joining a firm and need to understand the firm's client universe. You've found no one's actually logged any BD meetings and no real “relationships” are clearly marked in the CRM; so you resort to scheduling in person meetings with each internal team member (on a regular basis) to uncover where some potential opportunities lie.
Admin & Organisation (ie the finer details of search execution!
Avoiding manual processes
You're a seasoned EA, who knows your space through and through. You also know that at any moment, your team will ask for some data related request that will involve hours of long, manual processes to put together. Instead of going to the CRM, you go to your own process which you've developed over time to cut down on those hours - one that only you know!
If this all sounded all too familiar, you're not alone. What happens if these “bad data behaviours” go unchecked?
Missed opportunities / slower client growth
If your team isn't seeing (or able to access) all relevant data, opportunities will be missed. You'll be less able to generate key market intel that you KNOW your team has collected, and less able to win those key engagements.
Reduced ability to deliver “best in class” service
With a lack of process, assessment, and admin tasks, it becomes harder to deliver a "best in class" service for clients. We all want to deliver the best for our clients - so if we had the chance to deliver better work, wouldn't we?
Slower development for internal teams
If the team is bogged down in administrative tasks, there is less time to develop and progress.
We all want to bring our value to the workplace - and see it develop over time! If certain team members are required to conduct hours of manual processes, it's that much harder to promote and witness that individual and group transformation.
CRM fatigue. “Better the devil you know” mentality
A killer for overall business growth and success. Frustration in systems breeds overall dissatisfaction and could affect retention.
So now that we've laid out some key areas search firms are struggle with data - how do we start to solve for it?
Decide on the roadmap
Where do you want to be next year? In 2 years? 5 years? Knowing where you want to go (and establishing that internally) is the first major step.
Prioritise largest issues
You can't conquer Rome in a day. Identify the largest issues faced by the firm, and prioritise them accordingly.
Set Goals, Objectives, & Expectations
Make sure you know what's expected of your larger team. Every person has a part to play, so make sure you bring them along for the journey.
Be bold - there's no better time than now!
Understand the pain points
Dive in and get detailed. There's often more to discover under the surface which will always effect overall outcome.
Outline each process
Always relate it back to search. Make sure you understand how each new process will be positively impacting yours and your team's workflows!
Measure success; and adjust as needed!
Often the last step requires the most patience. Remain flexible for changes in circumstance or technology, and keep an eye on what you've built to make sure it's successful for the long run.
Each firm's data transformation is indeed just that - a journey. It is a process that requires long term vision, strategic insight, and a detailed knowledge of workflow and what's actually being done.
