Imagine a startup CEO running a founder-led sales team. The first hire is a BDR who misses her numbers in the first quarter. The founder fires her, hires another, fires that one too, and ends up concluding that good BDRs simply don't exist. But the BDR isn't usually the failure. The system underneath her is. Once the founder accepts that, the right question changes from "Why can't I hire a good rep?" to "Why is the process failing the reps I hire?"

The BDR role runs on activity. Most of the day goes to calls, replies, and meetings with prospects, and the first metric anyone assigns a BDR is exactly that: activity. Look at any open BDR role on LinkedIn, and you'll see it. Daily activity targets, front and center. But activity is the input, not the goal. The goal is qualified sales leads. So as a manager, maximizing the activity for a BDR will mostly make her burn out before observing performance. The job of the manager is to design the process that turns the most activity into the most qualified leads. In systemic terms: activity is the input, qualified leads are the output, and the BDR role itself is the process sitting in between.

The BDR role is harder to manage than it looks. Because BDRs spend most of their time heads-down on activity, the process behind them has to be robust enough to carry that activity all the way to a qualified lead. The BDR alone can't compensate for a broken process, no matter how hard she works.

That's also why BDRs, more than almost any other sales role, need a manager actively one level up from the daily grind. The manager's job is to set the sequences, select the accounts, and read the telemetry the rep doesn't have time to read herself. On top of that, there’s the coaching and training that role requires too. AEs, by contrast, are usually experienced enough to already understand most of this instinctively, and they can operate with more independence. BDRs can't, and they shouldn't be pulled away from activity to try.

Today I want to walk through the telemetry behind one specific, critical part of the BDR function: pipeline generation. Why the distinction between its stages matters, and what a manager can actually do with it.

The Sourcing metric is the input stage; the raw material entering the process. It measures whether BDRs are sourcing new accounts consistently rather than filling up altogether before a board meeting. Most organizations set a minimum sourcing number per rep, because activity is the first rung of the pipeline ladder, and a drop there moves everything downstream.

There’s a distinction between accounts and contacts that is worth mentioning: the Sourcing metric accounts for accounts rather than contacts. Adding two contacts at the same company is adding one account; one potential deal, not two. Whether the right number is higher or lower depends on the motion. Opening new logos in a greenfield market needs more raw volume than working an established base.

Consistency matters here more than the raw total does, and it's worth separating the two explicitly. A rep who sources steadily, day after day, is easier to manage and less taxing to sustain than a rep who bursts and stalls. Five zero-activity days followed by one huge push looks identical to a lighter, steady pace on a weekly rollup, but the two are not the same underlying process. A zero-activity day breaks momentum in a way a merely light day doesn't. Pipeline compounds, and a full stop resets that compounding more than a slowdown does. Looking only at the weekly or monthly total, this distinction might be invisible. That’s why it needs its own line of telemetry rather than a floor on the aggregate number.

Fit against the ICP matters just as much as volume or consistency. Say the ICP is law firms incorporated in Texas because of a specific regulation. A contact at a California firm won't convert no matter how well the rest of the process runs, so it's not neutral. Instead, it's wasted motion that looks like progress on a dashboard. Part of the manager's job is controlling what gets added to the pipeline in the first place, not just how much.

And raw account count is really only the first layer of the Sourcing metric. It monitors the number of accounts being sourced by the BDRs, but it doesn’t monitor the quality of those accounts. Two reps can both post 20 new accounts a week and be doing entirely different things: one spreading across 20 different companies, the other concentrating most of that volume inside two or three accounts. The count alone can't distinguish spread from depth, and each carries its own risk. Too shallow and you're not multi-threading key accounts; too concentrated and you risk exhausting or even flagging a domain before it's had a real chance to convert. That's a separate layer of telemetry worth building once Sourcing volume itself is under control, not something the top-line number can answer on its own.

Early in a new territory, Sourcing tends to be easy because the greenfield is full of untouched accounts. As that territory matures, new accounts get harder to find, which is exactly why Sourcing needs to stay monitored on an ongoing basis rather than being treated as a solved problem once the initial ramp is over.

Contrary to what some managers might believe, not all the accounts enter the system - the CRM. In fact, a 100% Capturing rate usually means that the organization is not capturing all of them. Records get silently blocked on the way into the CRM, often because required fields such as email, LinkedIn URL, or phone number are missing, and the CRM treats one of those as the unique identifier. A better decision is to find the missing fields rather than grossly drop incomplete accounts.

BDRs import contacts in bulk and move fast, so it's easy for the handful with incomplete data to fall through unnoticed. The volume of daily work makes going back to check nearly impossible without dedicated support. A few missed accounts a month, out of thousands, won't move the needle on its own. But it compounds, quarter over quarter.

The first step is simply measuring Capturing as its own metric, separated from Sourcing. Otherwise, a clean-looking sourcing number can be masking a leak right behind it. From there, enrichment platforms can help fill in the missing fields, a second contact from the same account can sometimes substitute, and manual cleanup helps too, though it comes with an obvious time trade-off against the expected benefit.

CRM health is worth a mention here too. After talking to plenty of sales leaders scaling their companies, I haven't met one with a genuinely clean CRM. Expecting otherwise might be a fantasy. New accounts can conflict with records already in the system, so a periodic CRM audit, alongside enrichment, is worth the time to catch what Capture alone won't show you.

Once an account is in the CRM, the next question is whether it’s reachable. Reachability monitors the working email, personal email, phone number, LinkedIn, X, Instagram, or whatever channel the sequence runs on. Usually there are more than one, if the process is built right. Without a communication channel, there's no way to run outreach in the first place, no matter how well the Sourcing and Capturing metrics performed.

Keeping the Reachability metric high usually means running multiple enrichment providers. Using deliberate regional and domain overlap, refreshed on a regular cadence, contributes to higher quality of the database. There’s a tradeoff, though, because enrichment costs money. A more efficient version of the same idea is targeting enrichment spend at the highest-priority accounts, where the expected payoff is highest, rather than spreading it evenly.

It's also worth thinking about data enrichment as a strategy decision. Some organizations run a single provider across the whole org for simplicity. Others regionalize — different providers for different geographies, since coverage quality varies a lot by region. Others layer a supplemental provider on top of a primary one specifically to fill coverage gaps the main provider misses. None of these is universally right; the choice depends on the organization's size, footprint, and how much operational complexity the team can absorb. What matters more than which model to pick is that BDRs shouldn't be the ones making that trade-off ad hoc, account by account. It should be a deliberate, centralized decision.

The Reachability metrics monitor the communication channels that exist. The Deliverability metric monitors whether those channels work. To illustrate the difference, consider a BDR that shows a 10% phone Reachability rate. After discovering that half of those conversations were wrong numbers, the actual Reachability is halved. From a management standpoint, it makes more sense to work on improving the quality of the database rather than adding more numbers to call to the BDR. Furthermore, those accounts with the wrong number might fall behind and never be reached out to at all.

There's a decay dimension to this too. People change companies, numbers, and emails constantly. CRMs age, and a contact captured ninety days ago may already be stale by the time a rep gets to it. This is why re-engagement sequences on older contacts often show a visible drop in the Deliverability metric: the data was accurate once and simply hasn't kept up.

Separating the Reachability from the Deliverability metrics matters. Doing so helps isolate two failure modes that look identical on a dashboard but need completely different fixes. Correctness means the number was never right for that person in the first place. Freshness means it used to be right and has since gone stale. Treating both as "bad data" and reaching for the same fix, usually more volume, solves neither.

After diving into layers of metrics related to the health of the database, managers can focus on how the reps convert those accounts into qualified leads. It's the first point in the funnel where managers can look at how the rep deploys her seller skills, by stripping out the effects of the underlying account database.

Some leaders use the Conversion Efficiency alone to rank reps against each other, but that's an oversimplification that can lead to the wrong conclusion. It assumes the ICP, territory, and lead quality were the same across reps, and they rarely are. It also folds in qualification judgment, which cuts both ways. Consider two reps, each working 100 accounts: one qualifies out 20 of them, the other qualifies out 50. Which one is better? Would your answer change if I told you both ultimately closed 10 deals from that same 100? Once you know that, it points toward the first rep applying a tighter, more accurate qualification standard. This means she's using her time more efficiently, and the AE's time downstream more efficiently too.

None of this makes a BDR's output fully predictable, and it isn't meant to. What it does is turn a single vague number — QSL (qualified sales leads) — into four separate signals, each one pointing at a different part of the process. That's the entire value of separating different metric layers. Rather than a scoreboard for the BDR, the telemetry creates a map of where to look first when the top-line number disappoints.