Outcome-Backed Funding: Productizing Strategy Without Making Bad Guarantees
- RESTRAT Labs
- Oct 13
- 17 min read
Updated: 2 days ago
Outcome-Backed Funding shifts how businesses allocate resources, prioritizing results over rigid plans. This approach funds clear, measurable goals through smaller, iterative investments rather than large, upfront commitments. It helps organizations adapt to market changes and avoid wasted resources. By focusing on learning and measurable outcomes, companies can make smarter financial decisions while reducing risk.
Key Takeaways:
Replace fixed budgets with flexible, goal-driven funding cycles.
Test ideas with smaller investments and scale successful ones.
Use metrics like learning velocity and funding alignment to track progress.
Avoid risky, all-in bets on unproven outcomes.
Adopt frameworks like Lean Portfolio Management and OKRs to connect funding with results.
This method balances financial responsibility with agility, enabling businesses to respond faster to changes while ensuring resources drive meaningful results.
Outcome-Driven Finance - with Marie-Luise Lehmann from Deloitte
Safe Betting vs. Risky Gambles
The step from wise choices to unsure bets can be small, mainly in the way companies plan. This part looks at how some choose to spend with facts and study, while others make big and unsure bets without any proof. Many groups think they are being safe, but in truth, they are tossing their assets away. Knowing what sets these two apart is key to building ways to use money that get good results and skip big money losses.
The main thing here is how they deal with the unknown. Safe Betting uses tests to learn, while Risky Gambles make firm promises on unsure results. One uses careful study, the other hopes on luck.
What is Safe Betting?
Safe betting is about wise choices that come from real proof, not just hoping for set results. It backs systems that learn and get better. Groups that agree to this put money into steps that check and confirm info instead of just chasing a set end.
This way often means rounds of money linked to learning checks. For example, rather than giving $2 million all at once for a huge tech shift, a careful group could use $200,000 for a three-month look to try ideas and check guesses.
Jonathan Smart, big on focusing on results in management, pushes this way. He asks for spending ways that like testing and changing more than strict plans. The question moves from "Did we do what we said?" to "What did we learn, and how does it help us move forward?"
Making choices with proof is core here. Teams get info, check their ideas, and change as they learn. Like if a plan to get more customers isn't working after a month, the team changes it instead of just sticking to a half-year plan because it was first written that way.
Checked learning rounds guide where money goes next. Each step shows what works and what doesn't, leading to the next money choices. This builds a path of smart choices, not just one big unsure play.
Being open works well here. Teams need to show how they used money to find new info, making a style of true care. On the other hand, groups that bet big and stick to it often end up just gambling, risking their means on results not yet proven.
What is Risky Gambles?
Risky gambles happen when money goes to firm promises on unsure results. It might look wise - "We will only pay if it makes X% more money" - but it often brings mess and bad pushes.
This way sees business results like a dice game. Groups bet big from the start on happy guesses and just hope things go well. When things don't go as thought, trouble starts as teams rush to find why it went wrong or who to blame.
Strong promises kill new tries. Teams, scared of not hitting goals, might not take needed chances or switch paths. Like a software group may keep making a tool they know users don’t want, just to stick to their first promise.
This way of thinking often leads to "success theater", where teams change numbers to look good rather than make real worth. They aim for high scores but the true help to the business is lost.
Risky bets build the base of gambling-like money plans. Teams must go after goals that are often out of their hands, causing money trouble when those goals aren't hit. The win-or-lose setup of these bets can lead to money shortfalls or fights over deals, making a loop of ups and downs that hurt plans for the future.
Accountability vs. Gambling: Key Differences
The gap between being responsible and gambling shows up more when you look at how each deals with not knowing, risk, and learning. The table below shows these differences:
Aspect | Outcome Accountability | Outcome Gambling |
Funding Set-up | Step-by-step, goal-driven funding | Big early cash outs with set goals |
Risk Handling | Spread over many tries | All in on one big risk |
Win Markers | Signs of growth and change | Hitting set end goals |
When Failing | Adjust with new ideas | Blame or give fines |
Who Decides | Many make choices, based on proof | Few decide, stick to first plan |
Look Ahead | Short checks and changes | No quick change, stick to the plan |
New Ideas Effect | Push for new tries and shifts | Holds back risky tries and fixes |
The rule changes are big. Funds tied to doing well let groups change with new facts. Teams can adjust their plans with some fixed rules, and bosses help them make smart choices more than just sticking to strict targets.
On the other hand, betting-like ways make tight rules that care more about following them than being able to change. Choices get slow and all come from the top, as any change might break the first promises. Bosses often use more time on handling fees and deals than on helping with new ideas.
John Doerr's ideas on OKRs (Objectives and Key Results) show this well. His way mixes big goals with clear results but points out that OKRs are there to guide focus and learning, not to push strict targets. It does best when it lets groups find out what works instead of making them follow set plans.
The way this changes culture is also big. Groups that focus on doing well grow learning cultures where teams can talk about tough times and change if they need to. Groups that act like they're betting often get blame cultures, where teams hide issues and keep on with bad plans to dodge fees.
Smart money knows that results rely on many things, none can control all. The aim is not to remove risk - it's to make setups that can handle it well while keeping money in mind.
"Fund learning, not luck."
This rule means caring about the results. When groups put work into learning step-by-step, they get better in time. But if they just hope for good luck, it won't last and a lot gets thrown away.
Plans for Smart Funding that Builds to Results
Moving from an old idea of chancing with funds to a clever, tighter control way needs plans that add up learn while caring for the money. These plans work to link wise choices with real results, avoiding unsure promises but keeping room to change. Among the best ways are Lean Portfolio Management (LPM) from SAFe 6.0, outcome-more-than-output rules, and using OKRs (Objectives and Key Results) as money checks.
What holds these ways as one? They put learning from what really happens first over hard promises, letting money plans change with new facts. Let's look into how each plan helps make funding easy to change and true to good use.
Lean Portfolio Management (LPM) in SAFe 6.0
Lean Portfolio Management shifts how groups hand out money by changing set yearly budgets with ongoing, bendy money checks based on how well it works. This method pays for value streams - work flows that bring worth to customers - more than just single projects.
For instance, a store could give money to bring in customers and check it every three months, changing it by looking at costs to get customers and how much they bring over time. This makes sure that what's put into the work fits with real results and market happenings.
A key part of LPM is participative budgeting, which brings finance people, leaders, and work teams together to share fresh data. This joins the gap between those with the money and those who do the work, getting better matching.
SAFe 6.0 also starts money checks to keep order without too much control. These might be:
Limits on how much to spend for trials
Checkpoints to ask customers or see money effects
Changes based on key show numbers
Quick changes in where money goes is another main bit. If a flow of work does really well or gets good results, money can be moved to use that push - sometimes in days. Usual money checks turn into group meet-ups for money, where teams show what they've learned, results, and plans for new tests. This open sharing helps even when things don't go as hoped, making it easier to tell what to do with the money.
Outcomes Rather Than Outputs in Rules
Jonathan Smart's thinking in Sooner Safer Happier moves watching past just seeing if jobs are done. It checks if what was made does what was wanted. This move from "Did we make it?" to "Did it work?" changes how money choices are made.
For example, a software group might deliver every item on time, but if customers are less happy or main numbers don't get better, it's not a win. With a focus on results, money goes to making worth, not just finishing jobs. Teams that show true results - like a marketing group lowering how much it costs to get a customer by trying new things - are more likely to get more resources.
This style stresses quick react circles over set long plans. Instead of detailed steps ahead, teams work on short-term learn goals with clear win signs. This lets quick fixes when market happenings or customer needs shift.
Smart's plan skips the dangers of just hoping for good results by looking at the quality of choices, not just expecting things to be right. They keep checking and fixing things often, which means money choices rely on solid info, like what customers do or how the market reacts. This makes a system that can move fast when new chances show up and keep everything in check.
OKRs as Money Safe Lines
John Doerr's book, Measure What Matters, shows how OKRs link big goals to careful money use. When used right, OKRs are like safe lines, guiding how money is spent and letting teams find the best ways to reach their goals.
OKRs don't force strict goals; they push for learning. For example, a goal to "Keep more customers" might have key results based on things like how many leave each month, how much customers like the service, or the value of a customer over time. These points show if success happens without forcing one way to do things, giving teams room to try and find great ways to work.
Money goes with OKR times, not old budget times. Teams get money to start their plans, with more coming as they get closer to their key results. Like, a team working to make users more active might only get more money after they show real steps in important points.
Doerr's way pushes big goals that boost new ideas while making sure money is spent based on real results. Clear tracking lets everyone keep an eye on progress, showing when it makes sense to put in more money. Also, OKRs make clear points to change direction - if results aren't happening, teams can think again and move money to better plans.
In Doerr's words:
"Lead for finding out, not for being sure."
These ways together give groups tools to handle money in a style that's flexible, based on data, and aimed at truly making something valuable.
How to Lead for Fast Change and Good Money Care
Moving from old ways of money plans to ones that focus on results calls for a way of leading that blends being strict with money and being able to move funds fast. This way lines up with a strong eye on results, making sure money goes to chances proven by learning on the go. The aim? To cut waste and boost effects.
New ways of leading stress making choices on the spot, leaving behind stiff plans that last a whole year. Rather than just controlling, leading becomes a way to help quick and good work get done.
Fast Money Moves and Who Decides
Fast moves with money set up rules on who can decide, letting teams move resources based on good proof. By setting limits, teams can jump on market chances without too many okays needed, making choices faster.
Fast money moves set in motion based on how well things are doing. For instance, if a team does better than its goals, it gets more money right away. But if it's doing poorly, its funds are cut until it gets better.
At the higher level, strict project budgets turn into money pools. These pools help bigger plans or linked projects, letting funds flow to parts that learn and prove value best. Like, a fund for digital change could support many plans to better customer experiences, with more money going to ones that do well, while cutting off ones that don't.
The way of leading also has steps for big decisions that are too much for just one team. These paths sort things out fast with clear needs and times, avoiding delays while still watching over big money choices.
With these active parts together, groups can sync their plans for even faster money choices.
Syncing Plans and Shared Budgeting
Old budget checks turn into plan syncs, where money chiefs, plan guides, and work teams come together. They share new learnings, talk about needs for funds, and make choices about where to put money based on fresh info, not old plans.
These meets happen often, maybe each month or every three months. Here, teams show what they've learned, key numbers, and ask for money in a way that's easy to see and decide fast.
Shared budgeting goes a step more by letting work teams help decide on money matters. Teams talk about what they need, what holds them back, and chances they see, while money teams bring info on the market and big aims. This way connects how much money there is with the real work needs.
The syncs also have chance shows, where teams share wins and losses. Being open like this builds a way of work where money goes to real learning and not just who talks the loudest or past mistakes.
Also, syncing plans can create chances for teams to fund each other, letting good ways from one team spread to others. For instance, if a way to get more customers works in one place, funds can be shifted fast to try it in other areas or on other products.
Guessing vs. Seeing in Leading
These rule models show a change from old, set ways to new, test-based ones. The main change is in how choices are made and checked.
Aspect | Predictive Governance | Empirical Governance |
Decision Base | Past data and expert views | Real-time feedback and test results |
Time Frame | Yearly money plans with checks every three months | Non-stop money flow with changes each month/quarter |
Winning | Set goals and sticking to plans | Meeting goals by changing and learning |
Risk Game | Plan every detail early and keep extra funds just in case | Try small things quickly and learn fast from them |
Change Answer | Strict steps to handle changes | Easy changes with set rules for making decisions |
Money Flow | Set money shares with small changes | Moving money groups based on what works |
Predictive governance fits well in calm spots where issues and fixes are clear. It does well for jobs and big builds that need a lot of planning and sure results.
Empirical governance, is good in unsure spots where what people want or how the market is, is not clear. It helps quick tests and changes, making it right for new ideas, new things made, and big tech changes.
Many groups use a mix of both ways, using predictive governance for calm work and empirical governance for spots that need fast moves and new learning. This lets them keep good work daily but also build new things and move well in fast-changing spots.
Moving from predictive to empirical governance needs a big culture change. Leaders must take on doubt and put learning first over set plans. Teams need skills in trying things out, checking them, and moving fast. Groups must prize smart risks and fast fixes over sticking to first plans.
RESTRAT gives the tools, teaching, and help firms need to make this change. By mixing careful money managing with being able to change plans, groups can build spending plans that push value fast while still meeting the money needs of bosses and others with a say.
Key Metrics for Measuring Funding Success
When it comes to outcome-based funding, success isn't just about traditional financial metrics. It’s about looking deeper - measuring how well capital aligns with validated outcomes, how quickly teams adapt, and how effectively organizations balance financial responsibility with a drive for innovation. Below are some key performance indicators (KPIs) that help guide this approach to agile financial governance.
KPIs for Outcome-Based Funding
Funding Alignment: This measures the percentage of funding tied to initiatives that have demonstrated measurable progress toward strategic goals. In simple terms, it shows how much of the budget is going to projects with proven results.
Average Pivot Cycle Time: This tracks how quickly teams can shift resources in response to new insights. Agile organizations often pivot in weeks, while traditional setups might take months.
ROI Delta Versus Baseline: By comparing the return on investment (ROI) from outcome-based funding to traditional approaches, this metric highlights the financial advantages of reallocating resources based on real, validated outcomes rather than sticking to rigid plans.
Learning Velocity: This reflects how fast teams are generating and applying new insights. It’s measured by the number of meaningful experiments or learning cycles completed in a given timeframe. A higher learning velocity indicates a strong ability to adapt and improve.
Funding Flow Efficiency: This calculates the time it takes to secure resources for scaling a validated opportunity. Faster reallocation means less friction and more time spent on innovation.
Portfolio Rebalancing Frequency: Organizations with advanced outcome-based funding strategies typically adjust their portfolios quarterly instead of waiting for annual reviews. This ensures resources are continually directed to the highest-performing initiatives.
Linking Metrics to Decision-Making
These KPIs do more than just track performance - they actively inform decisions. Real-time dashboards that combine financial data with learning metrics allow leaders to make quick, evidence-based funding choices during regular reviews. By setting funding thresholds tied to specific performance ranges, organizations can ensure decisions remain grounded in data, not gut feelings.
When teams request additional funding, they back up their cases with metrics such as learning velocity, funding alignment, and ROI trends. This approach minimizes subjective decision-making and political considerations, fostering accountability across the board.
Predictive indicators also play a crucial role. For example, teams with high learning velocity might need more resources to scale successful initiatives quickly, while projects struggling with outcome validation might require early intervention. This proactive approach helps organizations stay ahead of potential challenges.
Funding Agility as a Competitive Advantage
The ability to quickly redirect capital toward validated opportunities gives organizations a major edge. Agile funding systems allow businesses to seize unexpected opportunities, adapt to market shifts, and stay ahead of emerging technologies. This flexibility enables faster innovation while reducing risk.
Instead of making large, infrequent bets on untested ideas, agile funding focuses on smaller, evidence-backed decisions made more frequently. This balance between financial discipline and adaptability leads to better ROI and a stronger ability to respond to market demands.
At the heart of this approach is the integration of fiscal responsibility with the agility needed for long-term innovation. Tools like AI-powered dashboards, such as those offered by RESTRAT, help organizations merge outcome-based funding metrics with portfolio management systems. This gives leaders the clarity and speed they need to allocate resources effectively and keep their organizations competitive.
Future Outlook: Board-Level Focus on Funding Agility
Boardrooms are undergoing a transformation. Where directors once concentrated on annual budgets and quarterly earnings, their focus is now shifting toward capital velocity and adaptive funding decisions. The ability to quickly redirect resources toward validated opportunities has become a key differentiator in maintaining a competitive edge. This shift ties directly to the agile funding practices discussed earlier.
How Boards Are Changing Their Approach to Funding
The old "set it and forget it" approach to capital allocation is being left behind. Instead of approving large, multi-year budgets based on static business cases, today’s boards are demanding real-time insights into how capital is being used. They want to see measurable outcomes tied to metrics like pivot cycle times, learning velocity, and funding alignment.
Boards are placing greater emphasis on funding agility metrics, which measure how effectively organizations can reallocate resources in response to new insights. This marks a shift from treating funding decisions as annual milestones to making them part of a continuous, strategic dialogue.
Additionally, board members are recognizing that empirical governance - making decisions based on validated evidence - works better than relying on long-term forecasts in uncertain environments. Instead of demanding detailed five-year plans, they are implementing governance frameworks that reward teams for generating actionable insights and penalize reliance on outdated assumptions. To navigate this shift, boards are adopting new competencies, such as lean portfolio management principles and outcome-based measurement systems.
This new approach has far-reaching effects. Teams are empowered to test ideas, pivot when data suggests better options, and scale successful initiatives quickly. Such an environment not only accelerates innovation but also attracts top talent, creating a culture where adaptability and initiative thrive.
RESTRAT's Role in Driving Funding Agility
As organizations adapt to these new board-level expectations, tools like RESTRAT are emerging as essential partners. To implement funding agility, companies need systems that connect strategic goals with operational execution. RESTRAT’s platform combines AI-powered portfolio alignment with lean portfolio management principles to create funding models that balance adaptability with financial accountability.
RESTRAT offers AI-driven diagnostics to help organizations identify obstacles in their current funding processes. These diagnostics highlight inefficiencies, such as bottlenecks caused by traditional budgeting, and propose targeted solutions to improve capital velocity.
The platform also includes embedded AI tools that provide real-time insights, such as automated backlog prioritization and scenario planning for resource allocation. These features enable organizations to make agile funding decisions at every level, ensuring alignment with their strategic objectives.
For large enterprises, RESTRAT’s expertise in frameworks like SAFe 6.0 is particularly valuable. Their consultants guide organizations in configuring lean portfolio management practices that integrate seamlessly with existing governance structures. This approach reduces risks during implementation while enabling the flexibility needed for adaptive funding.
Custom workshops offered by RESTRAT equip leadership teams with actionable skills for managing outcome-based funding. These sessions cover everything from setting learning thresholds to designing governance models that maintain adaptability while ensuring fiscal discipline. The result is a framework that supports sustained funding agility over the long term.
Key Takeaways for Executives
Transitioning to outcome-based funding requires balancing financial discipline with adaptive learning. This isn’t just about adopting new metrics - it’s about rethinking how organizations allocate resources to foster both innovation and accountability. Executives who embrace this approach understand that funding agility doesn’t mean abandoning fiscal responsibility. Instead, it applies financial rigor to validated learning cycles rather than static projections.
A guiding principle for this shift is:
"Governance for discovery, not certainty."
This means creating decision frameworks that reward evidence-based pivots while holding teams accountable for results. It’s not about avoiding risk but ensuring that risks are informed by data rather than speculation.
Measurement systems must evolve to combine traditional financial metrics with indicators like learning velocity, pivot cycle time, and funding alignment. This integration supports confident, agile decision-making.
Ultimately, funding agility requires a cultural shift. Teams need to feel safe reporting negative outcomes if those outcomes lead to valuable insights. Leaders must avoid penalizing pivots that are backed by solid evidence, and boards must embrace the iterative nature of validated learning while maintaining high standards for the process.
Organizations that master this approach will gain a significant advantage. They’ll be able to respond faster to unexpected opportunities, avoid wasting resources on unproductive initiatives, and build capabilities that strengthen over time. In markets where change is constant, this adaptability will set them apart from competitors locked into rigid funding cycles.
FAQs
How is outcome-backed funding more adaptable and less risky compared to traditional budgeting?
Outcome-backed funding takes a different path from traditional budgeting by linking financial support to proven results instead of relying on fixed forecasts. This method lowers risk by prioritizing measurable outcomes, giving organizations the ability to adjust based on fresh data and insights. Unlike conventional budgets that lock in spending upfront, this approach allows for quick reallocation of funds to initiatives that show clear value.
By focusing on ongoing learning and improvement, outcome-backed funding encourages a mindset of exploration and responsibility. It reduces the risks tied to flawed predictions while encouraging innovative approaches, ensuring resources go toward efforts with demonstrated success. This mix of adaptability and fiscal discipline makes it a smart choice for driving strategic growth.
What steps can organizations take to shift from predictive governance to empirical governance?
Organizations aiming to transition from predictive to empirical governance should emphasize validated learning cycles over rigid planning. This approach starts with identifying key decision points that depend on real-world data and promoting ongoing experimentation. Regular performance reviews through iterative cycles can provide actionable insights to guide decision-making.
To support this shift, it's essential to establish processes that focus on evidence-based decision-making. For example, reallocating resources based on proven outcomes and maintaining flexibility in operations can make a significant difference. Governance roles must evolve to encourage agility while upholding accountability, ensuring that decisions stay aligned with strategic objectives and financial discipline. By cultivating a mindset of adaptability, organizations can strike a balance between innovation and responsibility, setting the stage for sustainable growth.
What are the best ways to measure the success of outcome-based funding, and which KPIs should organizations prioritize?
Organizations can gauge the effectiveness of outcome-based funding by tracking key performance indicators (KPIs) that emphasize learning, accountability, and flexibility. Here are a few examples:
Percentage of funding tied to validated outcomes: This tracks the portion of investments linked directly to measurable results rather than speculative efforts.
Average pivot cycle: Indicates how quickly teams can adjust and reallocate resources based on emerging insights or changing circumstances.
ROI delta vs. baseline: Evaluates financial performance improvements compared to initial benchmarks or expectations.
These KPIs highlight the importance of focusing on results and adaptability. By prioritizing data-backed outcomes over rigid, predefined goals, organizations can encourage innovation while maintaining fiscal discipline. This approach supports a culture of continuous improvement and smarter decision-making.
