When I owned a consulting company we viewed innovation as an imperative. It was the main thing that created differentiation, credibility, and opportunity. We had an innovation budget, solicited ideas from the team, and evaluated those ideas quarterly.
Almost as important to me was that this was fun. It gave everyone on the team the chance to suggest ideas and participate in the process. That was meaningful and supported the collaborative, high-performance culture that had developed. The team was inspired and empowered to make a difference, and that led to an ever-increasing sense of ownership for each employee.
The team also had a vested interest in having the process work, as quarterly bonuses were paid based on their contributions to the company’s profitability. There was a direct cause and effect correlation with tangible benefits for every member of the team.
We developed the following 10 questions qualify & quantify the potential of new ideas:
- What will this new thing do?
- It is important to be very detailed as this was used to create a common vision of success based on the idea being presented.
- What problem(s) does this solve and how so?
- This seems obvious, but if you are not solving a problem (which could be something like “lack of organic expansion”) or addressing a pain point then selling this new product will be an uphill challenge.
- What type of organizations have those problems and why?
- This was fundamental to understanding if a fix was possible from a practical perspective, what the value of that fix might be for the target buyer, and how much market potential existed to scale this new offering.
- What other companies have created solutions or are working on solutions to this problem?
- The lack of competition today does not mean that you are the first one to attack this problem. Due diligence can help avoid repeating the failure of others, and potentially provide lessons learned by others and help you avoid similar pitfalls.
- Will this expand our existing business, or does it have the potential to open up a new market for us?
- There are upsides and downsides to each answer, but breaking into a new market can take more time and be more difficult, time-consuming, and expensive to achieve.
- Is this Strategic, Tactical, or Opportunistic?
- An idea may fall into multiple categories. When Sarbanes-Oxley (SOX) Act became law we viewed a new service offering as both a tactical means to protect our managed services business as well as an opportunistic means to acquire new customers and grow the business.
- What are the Cost, Time, and Skill estimates for developing a Minimally Viable Product (MVP) or Service?
- What are the Financial Projections for the first year?
- Cost to develop and go-to-market.
- Target selling price, factoring-in early adopter discounts.
- Estimated Contribution Margin Ratio (for comparison with other ideas being considered).
- Break-even point.
- Would we be able to get an existing customer to pre-purchase this?
- A company that is willing to provide a PO that commits to making a purchase of that MVP within a specific timeframe increased our confidence in the viability of the idea.
- What are the specific Critical Success Factors to be used for evaluation purposes?
- This was an important lesson learned over time that helped minimize emotional attachment to the idea or project, as well as providing objective milestones for critical go / no-go decision making.
This process was purposeful, agile, lean, and somewhat aggressive. We believed it gave our company a competitive advantage over larger companies that tended to respond slower to new opportunities and smaller competitors that did not want to venture outside their wheelhouse.
With each project, we learned and became more efficient and effective, and made better investment decisions that positively impacted our success. We monitored progress on an ongoing basis relative to our defined success criteria, and adjusted or sunset an offering if it stopped providing the required value.
The process was not perfect…
For example, we passed on a couple of leading-edge ideas such as a “Support Robot” in 2003 that was essentially an interactive program that used a machine-learning algorithm. It was to be trained using historical log files, could quickly and safely be tested in a production environment, refined as needed and ultimately validated.
This automation could have been used with our existing managed services and Remote DBA customers to further mitigate the risk of unplanned outages. Most importantly, it would have provided leverage to take-on new business without jeopardizing quality or adding staff – thereby increasing revenue and profit margin.
At the time we believed this would be too difficult to sell to prospective customers (“pipe dream” and “snake oil” were some of the adjectives we envisioned), so it appeared to lack a few items required by the process. Live and learn.
In summary, having a defined approach for something as important as business needs innovation to grow and prosper, as best demonstrated by market leaders like Amazon and Google (read the 10-K Annual Reports to gain a better understanding of their competitive growth strategies that are largely based on innovation).
Implementing this type of approach within a larger organization requires additional steps, such as getting the buy-in from a variety of stakeholders and aligning with existing product roadmaps, but is still the key to scalable growth for most businesses.
As a young boy, I was “that kid” who would take everything apart, often leaving a formerly functional alarm clock in a hundred pieces in a shoe box. I loved figuring out how things worked, and how components worked together as a system. When I was 10 I spent one winter completely disassembling and reassembling my Suzuki TM75 motorcycle in my bedroom (my parents must have had so much more patience and understanding than I do as a parent). It was rebuilt by spring and ran like a champ.
By then I was hooked – I enjoyed working with my hands and fixing things. That was a great skill to have while growing up as it provided income and led to the first company I started at age 18. There was always a fair degree of trial and error involved with learning, but experience and experimentation led to simplification and standardization. That became the hallmark to the programs I wrote and later the application systems that I designed and developed. It is a trait that has served me well over the years.
Today I still enjoy doing many things myself, especially if I can spend a little bit of time and save hundreds of dollars (which I usually invest in more tools). Finding examples and tutorials on YouTube is usually pretty easy, and after watching a few videos for reference the task is generally easy. There is also a sense of satisfaction to a job well done. And most of all, it is a great distraction to everything else going on that keeps your mind racing at 100 mph.
My wife’s 2011 Nissan Maxima needed a Cabin Air Filter, and instead of paying $80 again to have this done I decided to do it myself. I purchased the filter for $15 and was ready to go. This shouldn’t take more than 5 or 10 minutes. I went to YouTube to find a video but no luck. Then, I started searching various forums for guidance. There were a lot of posts complaining about the cost of replacement, but not much about how to do the work. I finally found a post that showed where the filter door was. I could already feel that sense of accomplishment that I was expecting to have in the next few minutes.
But fate, and apparently a few sadistic Nissan Engineers had other ideas. First, you needed to be a contortionist in order to reach the filter once the door was removed. Then, the old filter was nearly impossible to remove. And then once the old filter was removed I realized that the length of the filter entry slot was approximately 50% of the length of the filter. Man, what a horrible design! A few fruitless Google searches later I was more intent than ever on making this work. I tried several things and ultimately found a way to fold the filter where it was small enough to get through the door and would fully open once released. A few minutes later I was finally savoring my victory over that hellish filter.
This experience made me recall “the old days.” Back in 1989 I was working for a marketing company as a Systems Analyst and was given the project to create the “Mitsubishi Bucks” salesperson incentive program. People would earn points for sales, and could later redeem those points on Mitsubishi electronics products. It was a very popular and successful incentive program.
Creating the forms and reports was straight forward enough, but tracking the points presented a problem. I finally thought about how a banking system would work (remember, no Internet and few books on the topic, so this was reinventing the wheel) and designed my own. It was very exciting and rock solid. Statements could be reproduced at any point in time, and there was an audit trail for all activity.
Next, I needed to create a fraud detection system for incoming data. That was rock solid as well, but instead of being a good thing it turned out to be a real headache and cause of frustration. Salespeople would not always provide complete information, might have sloppy penmanship, or would do other things that were odd but legitimate. So, I was instructed to turn the dial way back. I let everyone know that while this would minimize rejections it would also increase the potential for fraud, and created a few reports to identify potentially fraudulent activity. It was amazing how creative people could be when trying to cheat the system. By the third month the system was trouble free. It was a great learning experience. Best of all, it ran for several years once I left – something I know because every month I was still receiving the sample mailing with the new sales promotions and “Spiffs” (sales incentives).
This reflection made me wonder how many things are not being created or improved today because it is too easy to follow an existing template. We used to align fields and columns in byte order to minimize record size, overload operators, etc. in order to maximize space utilization and performance. Code was optimized for maximum efficiency because memory was scarce and processors slow. Profiling and benchmarking programs brought you to the next level of performance. In a nutshell, you were forced to really understand and become proficient with technology out of necessity. Today those concepts have become somewhat of a lost art.
There are many upsides to easy. My team sells more and closes deals faster because we make it easy for our customers to buy, implement, and start receiving value on the software we sell. Hobbyists like myself are able to accomplish many tasks after watching a short video or two. But, there may also be downsides relative to innovation and continual improvement simply because easy is often good enough.
What will the impact be to human behavior once Artificial Intelligence (AI) becomes a reality and is in everyday use? It would be great to look ahead 50 to 100 years and see the full impact, but my guess is that I will see some of the effects in my lifetime.