KPIs and OKRs for startups: differences and practical application

How do KPIs and OKRs differ?

According to Atlassian’s documentation, businesses can use both KPIs and OKRs. A KPI can become a measure for a key result. BHKD suggests distinguishing them through their purpose: are you monitoring whether an activity is healthy, or creating a specific change?

For example, the percentage of orders delivered as promised can be an operational KPI. When the quarterly objective is to make delivery more reliable, that percentage, complaint rates and resolution time can become key results. Renaming a metric does not create a good OKR.

Sample OKR for sales and customer service teams

A hypothetical situation: a startup attracts many new customers, but they often purchase only once. The quarterly experiment aims to help suitable customers experience value early and want to return. Targets must reflect baseline data, sample size and resources; illustrative numbers should not be treated as industry benchmarks.

A hypothetical set of results: raise repeat purchases among eligible customers from 18% to 24%; reduce complaints caused by incorrect advice from 12 to 6 cases; maintain gross margin above an agreed threshold. Supporting work might include revising usage instructions or training advisers, but those activities alone do not prove customers received value.

For a long purchase cycle, a quarterly repeat-purchase rate may be unsuitable. An early indicator such as the percentage completing the first usage step may be chosen, but check whether it relates to long-term outcomes or simply looks easy to improve in a report.

A metric-definition template before assigning targets

Two departments may both report conversion rates, but one counts price inquiries while the other counts customers whose needs have been qualified. Figures cannot be compared with different denominators. A short metric dictionary helps prevent disputes after results have been agreed.

Do not reward a metric at any cost

If only call volume is measured, sales teams may increase contacts without increasing quality conversations. If only newly contracted revenue is measured, discounts or sales to unsuitable customers can improve short-term targets while creating refund and receivables pressures.

Pair outcome metrics with a quality condition. For example, track revenue alongside margin and actual cash receipts; track processing speed alongside rework rates. The set should be sufficient to reveal trade-offs without becoming so large that reporting consumes the team’s day.

Does each person on a small team need an OKR?

Not necessarily. Improving the customer experience may require sales, product and operations to work together. Splitting this into many individual objectives can encourage people to optimize their own areas while neglecting the shared result.

BHKD suggests starting with one team objective and a small number of key results, each with a tracking owner. Weekly tasks still need clearly assigned performers. When using results to evaluate employees, consider their control, the data and circumstances; do not automatically turn experimental objectives into a reward-and-penalty formula.

What decisions should metrics support in meetings?

When a metric deviates, ask in sequence: is the data accurate, does the change come from the customer mix or the process, and what should be tested this week? With limited data, add sample conversations, orders or feedback to understand the situation rather than drawing firm conclusions from a small fluctuation.

Meeting notes should record an action, an owner, a review date and the desired measure. If you cannot say what you learned at period-end, improve objective selection before adding another dashboard.

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