If you could make one change to the technology in your business, what would it be?
What would your customers or employees find the most use for, today? A new way to pay? Easily accessible data? A more pleasing and easier to use design for the most used service?
Perhaps you don’t know, but you think your competitors might.
Introducing the Razor Sprint
The Razor Sprint is designed for people who believe that technology can enhance their business. If you want to make a change and take action, rather than just think and talk about it, Razor can help.
We get the right people in the room, without distractions, and produce meaningful prototypes, tested on real data to help you decide what to do next.
This is a sprint through a single project. A proof of concept, developed in isolation, where you can remove the shackles and take risks. The Razor Sprint is quick, and has a clear and singular focus.
- The Razor Sprint is designed for people, who believe that technology can enhance their business.
- We will focus on people who want to make a change and take action, rather than just think and talk about it or watch others do it from the sidelines.
- We promise that engaging with what we do, will help you gain clarity on what is possible and make progress, faster.
How do we do it?
The Razor Sprint will get your organisation up, and moving forward. Today's digital economy is all about speed. Moving forward with technology has its risks, risks to security, risks of compatibility, risks of making the wrong choice, but sitting still is the greatest risk of all. We will create a safe space for innovation, where together, we can challenge the status quo, make quick decisions and take action.
At the end of the process, there is something you can see working. This might be a working machine learning model that predicts potential fraud or pricing, a bot that can answer common customer service queries via multiple channels or a mobile app that can be used by customers to identify your products.
The process provides clarity on the possible, the return on investment and ultimately the confidence to take a leap with technology.
You are probably asking, how we can do this? The answer is, that its possible due to a number of factors.
Firstly, Razor invests heavily in R&D and because of this, the team are always on the cutting edge of technology. We bring this knowledge from the whole team to each Razor Sprint, to accelerate the delivery.
Secondly, we use commoditised cloud technologies to accelerate our delivery. There is no reason to build everything from scratch, when you can leverage the existing platforms and technology, it’s how you combine them, where the real magic happens.
If you're ready to take a step out of your comfort zone and ahead of your competition, spare some time to sprint with Razor and see what we can create together.
Phase 1: Understand
In phase 1, we build a shared understanding. This is where we ask where, why, who and what? We also ask, why not? This is where we bring a level of ignorance, to deeply understand the root cause of the challenge and to provoke different thinking.
The greatest strength of a consultant is to be ignorant and ask a few probing questions.
Many companies assume that they know their customers and internal staff. They also assume that what they are doing currently is the best way of doing it. Biases are in full play and can sometimes plague progress.
There is also a blindness to what is technically possible. What may have been impossible or very difficult only months ago is now more attainable. The most dangerous phrase in business springs to mind; “We’ve always done it this way”.
- What are the business strategies, principles, challenges and objectives?
- Who are the users?
- What are these users currently doing?
- What are the problems?
- What can we measure and what information do we currently have?
Activities & outputs;
- Spend time observing how things are done and conduct contextual enquiries. Do this without drawing specific attention if possible.
- Document the current process using tools such as User Story Mapping and Value Stream Mapping and challenge each step.
- Frame the problems that need to be solved. Define success criteria and measurements.
Phase 2: Explore, Refine & Plan
In this phase, we explore the problems and potential solutions. We ask which problems pose the largest gains if resolved and how much effort each problem would take to be resolved. Elements that support each of the solutions, such as the existing systems, ease of integration, security and data concerns, location, access and speed are assessed.
Any intelligent fool can make things bigger and more complex… It takes a touch of genius – and a lot of courage to move in the opposite direction.
The problems are then refined, prioritised and selected. Potential solutions are explored and formed with more clarity and examined against their ability to produce the most appropriate results. A single solution is selected to be taken into the next phase, based on these factors and discussion. The Occam’s Razor principle is used in this phase, where simpler solutions are more likely to be correct, than complex ones.
A plan is then developed that clearly defines what is to be achieved, the metrics that will be measured and steps on how it will be achieved. When you don’t know where you are going, every road leads where you want to go and so the plan is vital to the efficiency of the final product.
It is common for solutions to become highly complex, as this is the easier route and it is very hard to create simplicity, simplicity is hard to achieve! Razor help the team from falling into the trap of settling for the easy option.
There can be an assumption that data, services or underlying systems are present and accessible. Without taking the time to find out, the build stage could be hindered or even blocked. This is where the exploring phase adds the real value, by left shifting the thinking.
It is also common for people to want to shortcut the planning phase and just get stuck in with doing something. Again, this temptation has to be resisted, to ensure that the best solution at the time is selected, with a clear plan of what needs to be done. Seldom does the “just start doing something” approach, produce results.
Selecting what to do can be hard when there are so many things to choose from. Just like saying yes to one thing, you have to remember that you are saying no to everything else. Biases have to be left behind and rational thinking needs to be the priority. Start small and think big is the mantra.
It is also important to have a balance and not spend too much time thinking and planning. It is common for people to try and involve everyone and cover everything. Clarity is all that is required at this stage and not certainty.
- What technology, new and old would be relevant to solve these problems? Discuss how others have deployed this technology and question how technology may be used in this case? Can technologies be combined to solve this problem?
- How will users interact and engage with the technology? Where are the potential challenges for adoption? Where similar technologies have been implemented, what have others found to be problematic?
- Who is affected by the problem and involve them, to help design the new world and mould the technology around them?
Activities & outputs;
- Brainstorm what the new solutions could look like and challenge the status quo.
- Sketch any interfaces and journeys.
- If the problem is a data related one, clearly articulate the questions that need to be answered, so that a definition of what data is needed can be defined.
Phase 3: Build a Prototype
In this phase, we get to work on creating something. When creating the prototype, there aren’t any distractions with the intricacies of how the integration would work or how it would be completely secured; the focus is on building something that proves at a conceptual level, that it is conceptually possible. The explore phase will have clearly identified that integration etc would be possible and where necessary, static datasets will have been extracted for the prototype build.
It is a Minimal Viable Prototype. The prototype is a vehicle for learning, opening minds to what is possible and causing positive action that can be the ignition to a shift towards a positive innovation culture.
We are able to accelerate the build process by leveraging our vast experience, an extensive catalogue of highly technical and cutting edge projects supported by our R&D function.
Companies often try and do too much and not deliver something of value. This is where the exploring, refining and planning in phase 2 come into their own, to ensure that there is a clear vision, the supporting materials and focus.
- Is the team clear on what needs to be created based on the outputs from phase 2?
- Does each team member know what their role is?
If phase 2 has been completed appropriately, then these questions should be answered.
Activities & outputs;
The team create something tangible based on all of the direction from the previous phases. There may be a number of technical deviations and discoveries that help arrive at the destination. An agile approach to development is taken, where tasks are timeboxed to ensure that something is delivered, as quickly as possible.
The end result will be a minimal viable prototype. It may be a simple interface to a machine learning model or a console app that processes data. Whatever it is, it will be focused on solving the problem defined. The key here is focus. Solving that one small thing that might make a huge difference and start a revolution.
Phase 4: Validate
In this phase, the minimal viable prototype is tested with its target users. This could be anything from a demo of what the process does, or even running it alongside any existing systems. The results from the prototype are reflected against the success criteria defined in the first phase.
This is also a prime opportunity to show the leadership, to gain their feedback and guidance, buy in and direction, on the next steps to take.
The most common pitfall is the adversity to accepting that something didn’t work and that the learning from the project is still highly valuable. This pitfall may be more difficult to avoid as it can be an inherent cultural challenge, however, if when starting the process, it is understood that this is how innovation works, then it is less likely to be a problem.
Another common pitfall is the mismatch in expectations of the results. This is most common with machine learning and data prototypes. There is a false expectation that machine learning or natural language processing models are near perfect straight but in fact, need a lot more training and data for them to even start becoming useful. This is especially common with natural language processing and bots.
- Does the minimal viable prototype solve the original problem?
- How did the prototype stack up against its success criteria?
- Will the prototype scale?
- What would be needed to enhance the quality of the prototype?
- What challenges would there be to integrating this into the current processes?
- What would be changed if the planning and build phases could be started again?
- What are the key learnings from the prototype?
Activities & outputs;
- Define assumptions to test.
- Share with the wider team and specifically the people who have first hand experience of the problem area.
- Capture results and report back.
- Run next to existing day to day activities, if relevant and possible.
- Define clear next steps, to take the prototype onto the next stage.
Let’s get started
The Razor Sprint can feel a little challenging at first but once the process gets started, the feeling soon changes into excitement, as the fog is lifted and there is clarity on the direction. That first little step in the right direction makes all the difference.
Are you ready to step ahead of your competition or are you going to wait until you have no choice and are playing catch up?
The only thing we know about the future is that it will be different.