strategy
One Successful Approach for Managing Innovation
When I owned a consulting company, we viewed innovation as an imperative. It was the main driver of 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 allowed everyone on the team 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 team member.
We developed the following 10 questions to qualify & quantify the potential of new ideas:
- What will this new thing do?
- Be very detailed, as this was used to create a shared vision of success based on the presented idea.
- What problem(s) does this solve, and how so?
- This seems obvious, but selling this new product will be an uphill challenge if you are not solving a problem (such as “lack of organic expansion”) or addressing an immediate pain point.
- What type of organizations have those problems and why?
- This was fundamental to understanding whether a fix was possible from a practical perspective, what value that fix might have 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 you are the first to attack this problem. Due diligence can help you avoid repeating others’ failures by learning from their lessons and avoiding similar pitfalls.
- Will this expand our existing business, or does it have the potential to open up a new market for us?
- Each answer has upsides and downsides, but breaking into a new market can take more time and be more difficult, time-consuming, and expensive.
- Is this Strategic, Tactical, or Opportunistic?
- An idea may fall into multiple categories. When the Sarbanes-Oxley (SOX) Act became law, we viewed a new service offering as a tactical means to protect our managed services business and an opportunistic means to acquire new customers and grow the business. While this is not true innovation, it was an offering that flowed from this defined process.
- 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 willing to provide a PO committing to purchasing the MVP within a specific timeframe increased our confidence in the idea’s viability.
- What are the specific Critical Success Factors to be used for evaluation purposes?
- This lesson learned over time helped minimize emotional attachment to the idea or project and provided objective milestones for critical go/no-go decision-making.
This process was purposeful, agile, lean, and fairly aggressive. We believed it gave our company a competitive advantage over larger companies that tended to respond more slowly to new opportunities and smaller competitors that did not want to venture outside their wheelhouse.
With each project, we learned, 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 some leading-edge ideas, such as a “Support Robot” in 2003, an interactive program that used a pseudo machine-learning algorithm. It would be trained using historical log files, tested quickly and safely in a representative pre-production environment, refined as needed, and ultimately validated and rolled out.
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, a defined approach to 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 better understand their competitive growth strategies, which are largely based on innovation).
Implementing this approach within a larger organization requires additional steps, such as securing buy-in from a variety of stakeholders and aligning with existing product roadmaps, but it remains key to scalable growth for most businesses.
Creating Customers for Life
The goal for any business, regardless of the products you sell or the services you provide, should be maintaining a satisfied customer base that is loyal to your business. The idea is to create a mutually beneficial relationship that motivates people to keep working with you, even when competitive products or incentives are available (e.g., those pushing for a “Corporate Standard” involving another product).
The best part is that this concept applies to all companies and all Product Life Cycle stages. Whether your company is on a rapid growth trajectory towards ‘Unicorn status,’ or your offerings are mature and viewed as ‘less exciting.’ The approach will also help if your products decline and you seek the ‘longest tail’ possible. At each phase, credible threats from competitors seek to grow by eroding your business.
Several years ago, I was responsible for two product lines in two major geographic regions (Americas and APAC/Japan). Our attrition rate (“churn”) was traditionally slightly below the industry average, and our net revenue rate (NRR), which reflects overall growth by factoring in churn, was around 100, indicating the business was flat. We began seeing an increase in churn and a corresponding decrease in organic growth. Both were indicators that something needed to change.
After discussing tactical approaches, our small leadership team agreed this was a strategic issue we needed to address. The result was an understanding that we needed to create ‘Customers for Life.’
Everyone agreed with the concept, but due to various differences (culture, who our customer was – end customer vs. channel partner, buying patterns, etc.), we agreed to try what was best for each of our regional businesses and share the results and lessons learned.
My approach focused on developing strong relationships that fostered collaboration and ultimately led to growth and success for both parties. The basic premise was simple:
- People tend to buy from people they like, respect, and trust. Become one of those people for your customers.
- Helping companies achieve better business outcomes leads to greater success for our customers and us.
How did we do it? It was a systematic process that my team used that included the following:
- Develop simple profiles for each customer (e.g., products used, date of first purchase, footprint size, usage and payment trends, industry).
- Estimate their overall impact based on product footprint size, annual spend with us, company size, engagement and interactions, and growth potential. Companies and organizations with the most at stake or the most to gain became our Tier 1 priority. These are the customers that we invested even more time and effort with.
- Make contact multiple times yearly, not just when you want money.
- These “out of cycle” contacts became very important for maintaining and growing the relationship.
- When issues or concerns came up, we often learned about them earlier and addressed them before renewal, which helped expedite the process.
- Ask questions about key initiatives, milestones, and concerns.
- We documented the responses, which helped seed following conversations and demonstrate a genuine interest in what they were doing.
- If we noticed changes in their industry or region, we asked about them and probed whether we could help.
- Follow-up!
- Lack of follow-through is the fastest way to lose your customer’s trust and respect. Being reliable and helpful increases your value.
- Request meetings to understand how they use our products and get a brief update on what our company has been doing.
- Face-to-face meetings are always preferred, as you tend to learn much more than in remote meetings.
- Learning more about their business, systems, goals, and challenges creates opportunities to add value and become more of a partner in that customer’s success.
- Ask “What would it look and feel like when you successfully overcame those challenges and achieved your goals?” and “What is a realistic timeframe for making that happen?” to get the customer emotionally focused on that better future state, and then look for ways to “Weave your value proposition into the fabric of their dreams and goals.“
- We looked at how they used our products and offered suggestions to do more, do something better or more efficiently, call out potential problems, and discuss best practices. Often, we had a technical expert follow up and provide an hour or two of free assistance to explore those suggestions. We invested in their ongoing success.
- Look for opportunities to congratulate them.
- It demonstrates that they are important enough that you are paying attention. Google Alerts made this easy.
- Regularly ask our customers if there is anything that we could do to help them.
- They would often reciprocate, leading to increased references and referrals.
- Helping our install base customers, even if it wasn’t directly related to our products, was good business.
- Continuous Improvement – Analyze the results and refine the process as needed.
Before the meeting, we would spend an hour or two researching the company, its history, and significant events for it and within its industry, and identify its top 2-3 competitors. My consulting background came in handy as I “looked between the lines” to better understand the situation as we planned the meeting, focusing on what we wanted to walk away with and what we wanted the customer to walk away with. Preparation matters.
As we met with our Customers and Channel Partners, we would explain what ‘Customer for Life’ meant to us and the potential benefits to them. Before the meeting, we would check whether we had (or they wanted) an NDA so they could speak freely and with confidence. Trust was important. The information disclosed helped us understand their situation, and we mapped it against other customers to identify actionable trends. Showing interest and understanding created credibility. Asking relevant questions helped conversations move to substantive issues faster. From there, we focused on specific points that would positively impact that customer.
Over the course of two years, my team and I helped our customers innovate by providing different perspectives and ideas, modernizing (e.g., moving to spatial analytics to get a more granular understanding of their own business, cloud-enabling their systems to increase responsiveness to their business and control costs), improving their systems and growing their businesses, and more. We became their trusted advisors and advocates within our company.
We also received feedback that helped us improve our products and a variety of processes – something that benefited all customers. Occasionally, we learned about problems they were having. We took ownership of the issue, brought in the right people, and helped the customer find a resolution. Collaboration and success created stronger relationships – especially with the largest customers and companies.
The results: Customer churn decreased by 50%, organic growth increased by slightly more than 20%, and NRR increased by over 5%. This program made a several-million-dollar positive impact with relatively little effort. We had achieved our objectives, improved our bottom line, and shared our lessons learned with the other two teams.
The concepts behind Strategic Account Management, Voice of the Customer, Customer Experience, Customer Loyalty, and Customer Success blended into a manageable, practical approach and delivered strong ROI. My biggest lesson learned was that adopting this mindset and creating a repeatable process should be started sooner rather than later – before problems arise.
Every day you are not creating your own ‘Customers for Life,’ there is a good chance that your competition is. Don’t let that happen to your business.
The Future of Smart Interfaces
Recently, I was helping one of my children research a topic for a school paper. She was doing well, but the results she was getting were overly broad. So I taught her some “Google-Fu,” explaining how to structure queries to get better results. She replied that search engines should be smarter than that. I explained that sometimes the problem is that search engines look at your past searches and customize results as an attempt to appear smarter or to motivate someone to do or believe something.
Unfortunately, those results can be skewed and potentially lead someone in the wrong direction. It was a good reminder that getting the best results from search engines often requires a bit of skill and query planning, as well as occasional third-party validation.
Then the other day I saw this commercial from Motel 6 (“GasStation Trouble”) where a man has problems getting good results from his smartphone. That reminded me of seeing someone speak to their phone and get frustrated by the responses. His questions went something like this:
“Siri, I want to take my wife to dinner tonight, someplace that is not too far away, and not too late. And she likes to have a view while eating, so please look for something with a nice view. Oh, and we don’t want Italian food because we just had that last night.”
Just as amazing as the question being asked was watching him ask it over and over again in the exact same way, each time becoming even more frustrated. I asked myself, “Are smartphones making us dumber?” Instead of contemplating that question, I began to think about what future smart interfaces would or could be like.
I grew up watching Sci-Fi computer interfaces like “Computer” on Star Trek (1966), “HAL” on 2001: A Space Odyssey (1968), “KITT” from Knight Rider (1982), and “Samantha” from Her (2013). These interfaces had a few things in common:
- They responded to verbal commands.
- They were interactive – not just providing answers, but also asking qualifying questions and allowing for interrupts to drill down or enhance the search (e.g., with pictures or questions that resembled verbal Venn diagrams).
- They often suggested alternative queries based on intuition. That would have been helpful for the gentleman trying to find a restaurant.
Despite having 50 years of science fiction examples, we are still a long way off from realizing the goal of a truly intelligent interface. Like many new technologies, they were originally envisioned by science fiction writers long before they appeared in science.
A spectrum of common beliefs about modern interfaces seems to exist. On one end, some products make visualization easy, facilitating understanding, refinement, and drill-down of data sets. Tableau is an excellent example of this type of easy-to-use interface. At the other end of the spectrum, the emphasis is on back-end systems – robust computer systems that digest huge volumes of data and return the results to complex queries within seconds. Several other vendors offer powerful analytics platforms. In reality, you need a strong front end and back end to achieve the full potential of either.
But there is so much more potential…
I predict that within the next 3 – 5 years, we will see business and consumer interface examples (powered by AI and Natural Language Processing, or NLP) that are closer to the verbal interfaces from those familiar Sci-Fi shows (albeit with limited capabilities and no flashing lights).
Within the next 10 years, I believe we will have computer interfaces that understand the request (not just the string of words), intuit our needs, and quickly and easily generate correct answers. While this is unlikely to be at the level of “The world’s first intelligent Operating System” envisioned in the movie “Her,” and probably won’t even be able to read lips like “HAL,” it should be much more like HAL and KITT than like Siri (from Apple) or Cortana (from Microsoft).
Siri was groundbreaking consumer technology when it was introduced. Cortana seems to have taken a small leap ahead. While I have not mentioned Google Now, it is somewhat of a latecomer to this consumer smart interface party, and in my opinion, it is behind both Siri and Cortana.
So, what will this future smart interface do? It will need to be very powerful, harnessing a natural language interface on the front end with an extremely flexible and robust analytics interface on the back end. The language interface will need to take a standard question (in multiple languages and dialects) – just as if you were asking a person – deconstruct it using Natural Language Processing, and develop the proper query based on the available data. That is important, but it only gets you so far.
Data will come from many sources – things that we consider today with relational, object, graph, and NoSQL databases. Structured and unstructured data with inconsistent formats must be joined and filtered quickly and accurately. In addition, context will be more important than ever. Pictures and videos could be scanned for facial recognition, location (via geotagging and image searches), and, in the case of videos, analyze speech and background noises. Relationships will be identified and inferred based on a variety of sources, using both data and metadata. Sensors will collect data from almost everything we do and (someday) wear, providing both content and context.
Stylometry will identify outside content likely related to the people involved in the query and provide further context about interests, activities, and even biases. This is how future interfaces will truly understand (not just interpret), intuit (so it can determine what you really want to know), and then present results that may be far more accurate than we are used to today. Because the interface is interactive, it will allow you to organize and analyze subsets of data quickly and easily.
So, where do I think that this technology will originate? I believe that it will be adapted from video game technology. Video games have consistently pushed the envelope over the years, driving the need for higher-bandwidth I/O capabilities in devices and networks, better and faster graphics capabilities, and larger and faster storage (which ultimately led to flash memory and even Hadoop). Animation has become very lifelike and will someday be created with a few simple commands. Games are becoming more responsive to input from multiple sources, and may someday use things like eye movement for guidance. It is not a stretch to believe that the next generation of smart interfaces will come from this direction or something similar, like leading-edge defense technology (rather than from the evolution of current smart interfaces).
Someday, it may no longer be possible to “tweak” results through the use or omission of keywords, quotation marks, and flags. Additionally, it may no longer be necessary to understand special query languages (SQL, NoSQL, SPARQL, etc.) and syntax. We won’t have to worry as much about incorrect joins, spurious correlations, and biased result sets. Instead, we will be given the answers we need – even if we don’t realize that this was what we needed in the first place – which will likely be driven by AI. At that point, computer systems may appear nearly omniscient.
When this happens, parents will no longer need to teach their children “Google-Fu.” Those are going to be interesting times indeed.
Genetics, Genomics, Nanotechnology, and more
Science has interested me for most of my life, but it wasn’t until my first child was born that I shifted from “interested” to “involved.” My eldest daughter was diagnosed with Systemic Onset Juvenile Idiopathic Arthritis (SoJIA – originally called Juvenile Rheumatoid Arthritis, or JRA) when she was 15 months old, which also happened to be about six months into the start of my Consulting company, all while we were in the middle of a very critical Y2K ERP system upgrade and rehosting project. It was definitely a challenging time in my life.
At the time, there was very little research on JRA because it was estimated that only 30,000 children were affected by the disease, and the implication was that funding research would not have a positive ROI. The economics of medical research were eye-opening to me. This was also a few years before major breakthroughs like Enbrel for children.
One of the things that I learned was that this disease could be horribly debilitating. Children often had physical deformities as a result of this disease. Even worse, the systemic type that my daughter has could result in premature death. As a first-time parent, imagining that type of life for your child was extremely difficult.
Luckily, the company I had just started was taking off, so I decided to find ways to make a tangible difference for all children with this disease. We decided to donate 50% of our net profits to fund medical research. Our goal was to fund $1 million in research and find a cure for Juvenile Arthritis within the next 5-7 years.
As someone new to “major gifts” and philanthropy, I quickly learned that some gifting vehicles were more beneficial than others. While most organizations wanted you to start a fund (which we did), the impact tended to be more long-term, supportive, and much less immediate. Later, I met someone passionate, knowledgeable, and successful in her field who showed me a different, better approach (here’s a post that describes it in more detail).
I no longer wanted to blindly give money and hope it was used quickly and properly. Rather, I wanted to treat these donations like investments in a near-term cure. To be successful, I needed to understand research from both medical and scientific perspectives in these areas. That began a new phase in medical research and an independent learning journey in areas where I had limited understanding and expertise.
A lot was happening in Genetics and Genomics at the time (here’s a good explanation of the difference between the two). My interest and efforts in this area led to a position on the Medical and Scientific Advisory Committee with the Arthritis Foundation. Except for me, the other members were talented, successful physicians who were also involved in medical research. We met quarterly, and I asked questions and made suggestions that made a difference. But unlike everyone else on the committee, I needed to study 40+ hours for each call to ensure I understood enough to add value and not be a distraction. Every quarter, I earned my seat at that table, and soon, most of the other members respected me for that (i.e., “not a typical donor”).
A few years later, we did work for a Nanotechnology company (more info here). The Chief Scientist wasn’t interested in explaining what they did until I described some of our research projects on gene expression. He then went into great detail about what they were doing and how he believed it would change what we do in the future. I saw that and agreed. That started my thinking about the potential of leveraging advanced nanotechnology in medicine.
While driving today, I was listening to the “TED Radio Hour” and heard a segment about entrepreneur Richard Resnick. It was exciting because it got me thinking about this again – a topic I haven’t thought about for the past few years (the last time, I was contemplating how new analytics products could be useful in this space).
There are efforts today with custom, personalized medicines that target only specific genes for a specific outcome. The genetic modifications being performed on plants today will likely be performed on humans in the near future (I would guess within 10-15 years as gene editing becomes more mainstream), possibly even performed by some type of robots. Because the body is an incredibly adaptive organism, it may be very challenging to implement anything consequential that is consistently safe and effective long-term. But that day will come.
It’s not a huge leap from genetically modified “treatment cells” to true nanotechnology (not just extremely small particles). Just think, machines that can be designed to work independently within us to do what they are programmed to do and, more importantly, identify and understand adaptations (i.e., artificial intelligence) as they occur and alter their approach and treatment plan accordingly based on findings and changes. This is extremely exciting. From my perspective, being able to do things that positively impact the quality of life for children and their families is a worthy goal.
My advice is to keep learning, stay open-minded, and do what you can to make a difference. You will never know what is possible unless you try. It will also be interesting to see how technologies evolve and work together to create an even greater impact.
It’s not Rocket Science – What you Measure Defines how People Behave
I previously wrote a post titled “To Measure is to Know.”
The other side of the coin is that what you measure defines how people behave. This is an often forgotten aspect of Business Intelligence, Compensation Plans, Performance reviews, and other key areas in business. While many people view this topic as “common sense,” based on the numerous incentive plans you run across as a consultant and compensation plans you submit as a Manager, that is not the case.
Is it wrong to have people respond by focusing on specific aspects of their job that they are being measured on? That is a tricky question. This simple answer is “sometimes.” This is ultimately the desired outcome of implementing specific KPIs (key performance indicators), OKRs (objectives and key results), MBOs (Management by Objectives), and CSAT (Customer Satisfaction), but it doesn’t always work. Let’s dig into this a bit deeper.
One prime example is something seemingly easy, yet often anything but: compensation plans. When properly implemented, these plans drive organic business growth through increased sales, revenue, and profits (three related items that should be measured). This can also drive steady cash flow by closing deals faster and within specific periods (usually months or quarters) and focusing on models that create the desired revenue stream (e.g., perpetual license sales versus subscription license sales versus SaaS subscription sales). What could be better than that?
Successful salespeople focus on the areas of their comp plan where they have the greatest opportunity to make money. Presumably, they are selling the products or services that you want them to based on that plan. MBO and OKR goals can be incorporated into plans to drive positive outcomes that matter to the business, such as bringing on new reference accounts. Those are forward-looking goals that increase future (as opposed to immediate) revenue. In a perfect world, with perfect comp plans, these business goals are codified and supported by motivational financial incentives.
Some of the most successful salespeople are the ones who primarily care only about themselves (although not at the expense of their company or customers). They are in the game for one reason—to make money. Give them a well-constructed plan that lets them win, and they will do so predictably. Paying large commission checks should be a goal for every business because properly constructed compensation plans mean their own business is prospering. It needs to be a win-win design.
However, suppose a salesperson has a poorly constructed plan. In that case, they will likely find ways to personally win with deals that don’t align with company growth goals (e.g., paying a commission based on deal size but not factoring in profitability and discounts). Even worse, give them a plan that doesn’t provide a chance to win, and the results will be uncertain at best.
Just as most tasks tend to expand to use all the time available, salespeople tend to book most of their deals at the end of whatever period is used. With quarterly payment cycles, most of the business tends to book in the final week or two of the quarter, which is not ideal for cash flow. Using shorter monthly periods may increase business overhead. Still, the potential to level out the flow of booked deals (and associated cash flow) from salespeople working harder for that immediate benefit will likely be a worthwhile tradeoff. I pushed for this change while running a business unit, and we began seeing positive results within the first two months.
What about motivating Services teams? What I did with my company was to provide quarterly bonuses based on overall company profitability and each individual’s contribution to our success that quarter. Most of our projects used task-oriented billing, where we billed 50% up-front and 50% at the time of the final deliverables. You needed to both start and complete a task within a quarter to maximize your personal financial contribution, so there was plenty of incentive to deliver and quickly move to the next task. As long as quality remains high, this is a good thing.
We also factored in salary costs (i.e., if you make more than you should, you’re bringing more value to the company), the cost of rework, and non-financial items that benefited the company. For example, writing a white paper, giving a presentation, helping others, or even providing formal documentation on lessons learned added business value and would be rewarded. Everyone was motivated to deliver quality work products on time, help each other, and do things that promoted the company’s growth. My company prospered, and my team made good money to make that happen. Another win-win scenario.
This approach worked very well for me and was continually validated over several years. It also fostered innovation because the team was always looking for ways to increase their value and earn more money. Many tools, processes, and procedures emerged from what would otherwise be routine engagements. Those tools and procedures increased efficiency, consistency, and quality. They also made it easier to onboard new employees and incorporate an outsourced team for larger projects.
Mistakes with comp plans can be costly – due to excessive payouts and/or because they are not generating the expected results. Backtesting is one form of validation as you build a plan. Short-term incentive programs are another. Remember, without some risk, there is usually little reward, so accept that some risk must be taken to find the point where optimal behavior is fostered, and then adjust the plan accordingly.
It can be challenging and time-consuming to identify the right things to measure, the right number of things (measuring too many or too few will likely fall short of goals), and the incentives that motivate people to do what you want and need. Anything worth doing is worth doing well. Hopefully this post provided ideas on how to make that happen.
Where Ideas, Experiences, and Lessons Learned Intersect 