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Top 6 business intelligence mistakes

Top 6 business intelligence mistakes

These days, companies large and small have an insane amount of data to help with decision making.

A small mom and pop restaurant with a cloud based reservation system can forecast how much ingredients to order for the week. Yet we all still make bad decisions. Why?

First of all, let’s not blame the data. By itself, data can’t do anything.

If there’s anyone to blame, it’s us. That’s right: the human beings behind the data.

We are the ones that decide what data to record, how to record it, how to analyze it, and how to look at it. Between the moment we have a question and the moment we make a decision, there are numerous chances of misusing data and arriving at the wrong conclusion. It’s like walking through a minefield.

Working in the analytics field, I’ve seen hundreds of data analyses go nowhere, wasting thousands of hours of effort. So I’m going to share five of the most prevalent mistakes I’ve seen.

“What’s the actual problem?”

I once helped an e-commerce company analyze their top 10 sources of new visitors. After seeing the results, they were ecstatic to find that both their paid campaigns and their blog were top sources of new visitors. These were channels that they could actively control and scale. So they did just that: They invested more money in their paid campaigns and kept their blog active.

Yet a few weeks in, they started to complain that their effort didn’t translate into higher revenue. A lot of new people were visiting the site, but not buying. Why is that?

The simple answer is that the analysis they wanted answered a specific question: Which sources brought the highest number of new visitors? It did not answer which sources brought the highest number of new paying customers, or high lifetime revenue customers, which would both have been more helpful to their actual problem of growing new revenue. So to avoid wasting time, effort, and money, let’s ask the right questions to begin with.

“Is the sample statistically significant?”

I once observed a sales team cancel a process change after 10 prospects failed to convert under a new process (they handled on average 200 prospects a month). By no means was that sample size significant enough to draw any conclusions yet, scientifically speaking. It was not a data-driven decision. It was an emotional decision.

I’ve also witnessed a case where a company made product decisions based on half-a-dozen phone interviews with select clients that they had good relationships with. This particular company had 500+ clients. Half-a-dozen people among a population of 500+ clients does not represent an accurate view of growth opportunities. In addition, the quality of the sample was also questionable. All clients interviewed had good relationships with the company, which indicates that the opinion of unhappy customers and churned customers were not acknowledged.

Sampling problems, including selection bias and lower than optimal sample size, abound in business intelligence. Startups are especially prone to taking shortcuts and use poor samples. Sometimes, it’s because there is simply not enough data… If a company just started acquiring customers, there may not be enough customers to make the analysis statistically significant. Other times, it’s because of pure impatience… Teams want to take decisions now, not in two weeks, so they often fail to wait for their experiments to fully complete.

The result is a decision based on poor data.

“Are the numbers relevant?

I’ve also witnessed many companies set future sales goals based on historical trends, but then change their entire sales process and expect the same goals to be hit. How can one expect the the same forecast when all input variables have changed?

It’s like expecting to fly from New York to Los Angeles in 6 hours, but then change our plane for a car and still expect to get there in 6 hours.

Let’s recognize that the analysis or forecast that we do is only good for the scenario that we considered. Should we decide to tweak or change our scenario, a new analysis needs to be performed.

“Are you sure the numbers are right?”

NASA once lost a $328 million satellite in space because one of its components failed to use the same measurement units as the rest of the machine. Target lost $5.4 billion in Canada partially because its inventory system had incorrect data.

Time and again, huge mistakes were made because the underlying data fueling these projects was bad to begin with.

So to make sure that my analysis is accurate, I often ask a second party to check the numbers. One should never review their own essay. The rule applies to analyses as well.

“What does this mean?”

Having access to information doesn’t mean that we know what to do with it. I’ve seen many people confused by data reports and unsure of what decision to take.

I once helped a B2B company evaluate which customer group to target for an advertising campaign. Their product was used by customers from three different industries, but they didn’t have the resources to tailor their sales processes and marketing content to all three groups yet.

So they began by looking at revenue generated by the three industries. Then they looked at revenue growth over time, profitability, and lifetime revenue. The results showed that 50% of their revenue came consistently from one industry, but that another industry was the fastest growing, going from 10% to 35% of their revenue over the past year. Both were potentially good choices to target and they didn’t know which one to pick.

I thus asked them to divide the total revenue by the number of clients/companies in each industry, effectively giving us the average revenue per client. My logic was that their sales and marketing efforts were going to be spent on a select number of prospects, so targeting prospects with higher individual revenue may yield a better ROI (e.g. between a $500/year client and a $5,000/year client, I’d advise to choose the $5,000/year client assuming that cost of support is similar). Based on the analysis, we saw that the fastest growing industry was also the one with the highest paying clients. This thus made the decision easier.

The point is that looking at the right information is important, not just information. This requires people that can interpret data, explain caveats, and tell a story. I thus highly recommend for all managers, data analysts, and data scientists to read Cole Nussbaumer’s Storytelling with Data book.

“We deleted what?

I once tried to help a SaaS company understand their user churn trends, only to discover that they delete customer account information 3 months after a user deactivates their account. This meant that there was only data on recently churned clients. The sample proved to be too small and biased to draw any useful conclusions.

Developers may delete data because they are running out of room on their hard disk, or because they think that a certain piece of data is unimportant. Regardless of what developers think, from an analytical perspective, we should never ever ever delete data.

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Need better insights? Stop surveying and start observing

Need better insights? Stop surveying and start observing

The number of surveys and feedback requests I receive from companies is insane.

Buying a plant at Home Depot prompts a 15-min experience survey. Getting out of an Uber ride prompts for immediate rating. Every software tool I’ve used has asked me “How likely I am to refer a friend…” It has become too easy for people to design and launch surveys, leading to too little planning around what to ask, why, and how often.

Our team has certainly been guilty of this behavior as well. We conduct a couple email surveys a year, ask for feedback during account calls, and actively track our NPS score.

While I support this customer-centric culture, I also believe that we’re asking many unnecessary questions.

As result, customers are becoming inundated with annoying requests for feedback. I can’t help but think of a future where people block surveys like they block online ads. In a way, they already are: Response rate of our customer surveys are around 5%. To boost this, we often have to resort to contests, prizes, and bribes that bias the sample population. In the end, we can’t even trust the data from our surveys.

Therefore, I’m advocating for a less intrusive and more accurate method of gathering customer insights, by observing customer behavior. To illustrate this approach, I’m going to analyze three common questions found in customer surveys, and how we can answer them without talking to customers.

“How likely are you to recommend us to a friend?”

I understand the need to know how much users love our tool via NPS. It helps us evaluate progress on customer satisfaction, and even compare against other companies.

What I don’t understand is why we need to ask people this question when we can simply track referral rates. Besides, if someone answers 9 or 10, but never actually referred anyone… are they playing nice or lying out loud? Either way, knowing how likely someone is to refer us doesn’t help our business. Actually referring people to our business does.

So instead of surveying NPS, what I’d advocate for is a referral system that allows customers to actually refer their friends directly in-app. We can then gauge how likely customers are to refer us based on actual data. There’s a clear difference here: NPS measures a person’s likelihood to refer someone (mere words), whereas the referral rate measures the ratio of people actually doing it (an action). If I remember right, action speaks louder than words.

With this data, we can even take the analysis a step further, and calculate the referral rate over time by registration cohorts (i.e. % of people that registered in a specific month and referred friends in month X after registration). It would show us when people are most likely to refer after registering themselves, and when numbers plateau, indicating an opportunity to remind them of our referral program. Taking actions to increase this metric is much more impactful than trying to increase NPS – it directly drives customer acquisition, not just a sentimental score. 

But wait, don’t we already have referral systems? Yeah, so why do we keep asking that NPS question?

“What would you like to see improved?”

I recently took a flight to Florida, which was delayed and overbooked, after which I got an email asking me for feedback. Boy did I have lot of feedback to share… But did I answer the survey? No.

Why? Because I had already spoken to a customer service agent before the flight to make sure my wife and I would be on the flight, along with a flight attendant about some other issues in flight. I didn’t feel like repeating myself.

In my opinion, no company that cares about customer happiness should survey customers about how they can improve. Most customers, at least in the USA, proactively complain to customer service. To ask for it again via a second channel is like saying: “Hey, I don’t remember what feedback you gave our team. In fact, I don’t trust that customer service recorded anything at all. May I ask you to refamiliarize yourself with your frustrations and repeat them to me again?”

Do we really want people to think about what frustrates them once more?

I didn’t feel like repeating myself.

In my opinion, surveying customers on how we can improve means that we either don’t have a help desk, or don’t use our help desk data intelligently.

So to gain ideas on how to improve our business, let’s analyze our customer complaints and help desk data first.

“What features would you like to see?”

I’ve helped many product managers set up conversations with clients to get ideas on new features. Clients are usually excited to share their thoughts, and most have very specific features in mind. To help put their ideas into context, we often resort to further probing: Asking customers why they need XYZ feature, how they plan to use it, and how they’d prioritize their wishlist. This usually leads to hour long conversations where the client isn’t doing work they’re paid to do. While we only gain a tiny window into the challenges of our users. Hearing a story is simply not the same as being there. It lacks context.

Instead of all this questioning, I’ve found visiting clients and observing them using our tool, without disturbing them, is much more insightful. Shadowing users provides critical context around how they’re using the tool, as part of what process, in combination with what else, when, etc. This allows me to clearly understand the core challenge that a client is facing. And more importantly, it helps me gain ideas that can improve how our software is used in combination with other tools, and in different situations.

If engineers and product managers simply took the time to observe the users they serve in their environment (not some ideal lab setting), or maybe even do what their customers do for a day, the world would function much more effectively.

Allow me to share another example: I recently visited a grocery store where they had just installed a new cash register / payment system at all checkout lanes. Register clerks had a frustrating time using them, leading to long lines. We could blame the issue on improper training, or we could ask ourselves how a cash register could be so hard to operate… I’m willing to bet that the machine had no issues in the lab setting that it was designed in, but that engineers never even tried to use it in a real grocery store by themselves. They likely designed the whole thing based on indirect customer feedback, which rarely provides enough context to a problem.

I don’t doubt that we can find exceptions to what I’m advocating above. The point stands however that we should first see if we can answer our questions through observations rather than surveys. It yields much more comprehensive and accurate insights, and doesn’t waste our customers’ time. Action speaks louder than words.


Recommended exercise

Let’s look at all the questions that we’re asking on our customer surveys and ask ourselves: “Can this be replaced with insights from their actual behavior?”


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Why does one problem always lead to another?

Why does one problem always lead to another?

I can’t remember the number of times that clients re-opened a case or issue after we thought that it was resolved. Take the example of how we tried to help a client get relevant email reports:

Our software has a feature that allows users to schedule customized email reports to themselves.

A customer one day asked if the email report could include more data points, as some of their reports exceeded a set limit on how much data can be included. So we doubled the amount of data each report could include.

The same customer asked a few weeks later if the tool could send graphical email reports (email reports were shown in table formats up until now), which would make things easier to read. So we began work on that feature as well.

A few months later, the customer reached back out to our product team and asked whether we could automatically send email alerts when certain events happen, rather than wait for the data in a scheduled email the next morning.

That’s when something clicked in our minds. We realized that all their requests pointed to one single problem. They needed a way to receive actionable information at the right time. It took us months to finally realize it. Pre-scheduled email reports helped with that goal, but didn’t completely solve the problem. Only when the customer asked for automated alerts did it click that we were solving symptoms to their problem rather than addressing the problem.

If I had the opportunity to re-tackle this client’s request from the beginning, I would identify the client’s true pain first rather than do what they asked each time. I’d then follow up with an idealized design process to think of potential solutions. It would have saved a lot of time.

It has become clear to me over the years that a problem will rarely be solved if we fail to identify its root cause. To this effect, I’ve designed a framework to help vet problems. I’ll be exploring it in detail below and walk through a personal example together.

What’s the problem with dishes?

Let’s explore our framework by working through a typical conflict among roommates, where one person doesn’t want to wash their dishes, while another person needs to use clean dishes.

What is the problem / pain / frustration? One roommate doesn’t want to wash their dishes, while another needs clean dishes to eat.

Who are the players involved and how do they perceive the situation?

Person A: Person having to wash the dishes

What does this person desire? Clean dishes without having to spend time washing dishes.

How does this person perceive the situation? Spending too much time washing dishes.

Why is this painful (starting a root cause analysis)? Perception that time can be better spent elsewhere.

Why is dish washing not a good use of time? Washing dishes isn’t as enjoyable as other activities. It’s boring.

Why is it boring? Perception that washing dishes is a chore, and we don’t enjoy doing chores in our society.

Why don’t we enjoy doing chores? There is a perception that chores should be performed by people whose time is less valuable than ours.

Why are dishes not worth my time? We want to feel proud about what we spend our time doing, and there’s nothing prideful about washing dishes.

Why do I want to be proud of what I do? Want to be happy.

Person B: Person that needs to use clean dishes

What does this person desire? Clean dishes without having to spend time washing dishes, and without having to spend time convincing someone else to wash the dishes.

How does this person perceive the situation? Dishes are not washed and I am not responsible for doing them.

Why is this painful? I feel a lack of respect as my roommate is failing to wash dishes that he used.

Why is the roommate responsible for it? There’s the perception that an agreement exists on who should wash dishes, and it’s not honored.

Why isn’t it honored? The roommate doesn’t care about the agreement.

Why doesn’t the roommate care about the agreement? There hasn’t been a verbal or written agreement around the expectation that has been agreed upon by the roommate.

Why hasn’t there been a formal agreement? There exists a perception that cleaning up after oneself is a social norm.

Why isn’t the roommate abiding by the social norm? They’re not aware of it.

So what are the actual problems experienced? Person A doesn’t find happiness washing dishes, while person B feels that Person A isn’t respecting a social norm on who’s responsible to wash dishes.

The simple framework above helped us evaluate a problem from different perspectives, and identify the root cause of each player’s pain. It’s not simply that person A doesn’t want to do dishes, it’s that they don’t enjoy doing it. There’s a difference. And it’s not just that person B needs clean dishes, it’s also that they feel a social norm isn’t being respected. Now that we have full clarity and context around our problem, we can go ahead to identify solutions and innovate, responsibly. Solving either root causes will likely also solve other problems beyond just dishes.

Before ending this blog post, I’d like to recommend “Are your lights on” for further insights on problem definition. It’s in my opinion one of the best books on problem definition.


Recommended exercise

Next time that someone identifies a problem, let’s break it down and identify the root cause using the framework above.


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Where forecasting fails, scenario planning succeeds

Where forecasting fails, scenario planning succeeds

Most of us carry a flat tire in our car. Not because we forecast having a flat tire, but because it’s a potential scenario. While we use scenario planning to avoid being stuck on the road, we often fail to do so when planning our business’s future.

Most startups have yet to find a scalable business model. So in the face of changing customer needs and new competitors, we are prone to change our business processes, organizational structures, and product offerings much more frequently than established businesses do.

Under this constant need to adapt, I’ve often found myself lacking the time to plan and vet a decision. The only question I resort to asking my team is: “What’s the best solution to this problem and what do we foresee happening?”

With time, I’ve discovered that my question is limiting in two aspects: 1) It inadvertently forces people to only think about one choice, one “best” option, rather than many; and 2) It misleads people into thinking that there is only one possible outcome as result of our choice.

In reality, there are always multiple options, each with a multitude of potential outcomes.

Why is this important to recognize? Because I’ve often realized that there’s a better solution, but only after a decision has been made, after a change has been implemented. When it’s too late.  I also find that we could have identified that better option beforehand, if we simply took a minute to consider all our choices.

My team and I once faced with the common problem of having too much work, too many clients to support (a good thing), and not enough time. And as we just landed a series B investment, leadership had even faster growth in mind.

So I sat everyone down and asked “What’s the best solution to our large queue of work and what do we foresee happening?”

Immediately, everyone jumped right to the solution of hiring additional team members that could focus on a specific type of request. In other words, increase staffing and specialize. In the moment, it sounded like a good plan, so I advocated for additional team members. And we got them.

A few months following the hire of two additional team members, the same problem resurfaced. The number of clients didn’t proportionally grow, but we had more requests from the same pool of clients. Since we weren’t making additional revenue from these clients, hiring additional people was not a great solution. We all agreed that we couldn’t just throw money at the problem. So we sat down and asked ourselves: “What options do we have?” Everyone got surprisingly creative thought of ideas such as:

  • Set a quota to how much service time each client can access per month;
  • Stop doing certain type of work for clients and train them on doing it instead; and
  • Charge extra for access to our service team.

We then proceeded to plan around contingencies, asking ourselves what could happen if we implemented these solutions. For example, if we were to set a quota to how much time each client could use per month, our team foresaw that:

  • High demand clients could complain;
  • Low demand clients that don’t hit the quota could file requests just to fill their quota; and
  • Client could be frustrated if they exceeded their quota, and yet needed a critical service necessary to the functioning of their account.

The exercise was successful all around. People were creative, open-minded, and honest in their assessment of potential outcomes.

Fact is, all options identified were possible and better than hiring additional team members, both in terms of efficiency and scalability. And the fact that we analyzed potential outcomes, we were in a position to plan ahead or readily react with counter-measures. For example, we could have reached out to high demand clients and set new Service Level Agreements during a renewal conversation, and gradually roll out the concept of quotas.

Yet we only identified these solutions once we faced the same problem again, without an easy way out. The question thus begs: Could we have identified them in the first place? I think so. If we stopped and analyzed all our options.

It goes without saying that I’m now a huge fan of scenario planning. So for the rest of this blog post, I’m going to share my take on this crucial decision making tool.

What is scenario planning?

In the context of tactical decision making, scenario planning involves a process by which we first identify a series of potential solutions to our problem, including doing nothing. Next, we identify and analyze all plausibles outcomes of each solution identified, our scenarios, and plan around contingencies.

Based on an analysis or even experimentation of how effective each solution can be, we can then take our decision. From there, we’ll have our contingency plans available should any of the plausible outcomes identified during scenario planning materialize. We effectively stand ready to react.

Success translates into no surprises and readiness to respond.

What’s the difference between scenario planning and forecasting?

Technically, forecasts envision a probable future (how likely is it to occur?), whereas a scenario planning identifies plausible futures (can the event occur?). The relevancy of the two methods thus depends on how we want to plan for the future and what resources we have available. For example…

  • A prominent application for forecasting is weather. If we forecast rain today, we’re likely to plan on having an umbrella when commuting. If we were to perform scenario planning for weather, where rain is always a plausible future, we’d be walking around with an umbrella independent of the probability of rain – it’s simply a plausible outcome.
  • Scenario planning on the other hand is often used for trip planning. We can’t always forecast exactly what we will do, what we will visit, or what the weather will be like when traveling, so we plan for all plausible scenarios. We bring all kinds of clothes for comfort, medications for health, and even books for potentially boring moments.

Scenario planning is thus very much linked to contingency planning. Again, our goal is to simply stand ready to react.

For a more strategic application of scenario planning, I highly recommend Idealized Design by Dr. Ackoff.

When should I use scenario planning?

In my opinion, scenario planning needs to be applied anytime a decision is needed. This allows us to fully acknowledge the potential impacts of our decision, and plan around plausible risks and threats.

For further reading, I highly recommend HBR’s article on how Shell performs strategic scenario planning and what they gain from it.


Recommended exercise

Let’s pick a decision that we’re actively assessing right now and pull the team together to brainstorm on: “What do you think would happen if we decided to go ahead with___?” Is the team ready to face these consequences?


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Do I care about my team more than my company?

Do I care about my team more than my company?

When a start-up company scales from a core team of 10-20 team members to 100+ people, I’ve witnessed a tendency for departments to lose touch with one another. Thats when we become hyper-focused on scaling our own individual team.

This often results in the loss of cross-team communication, break-downs in collaboration, along with other inter-department conflicts.

In this blog post, I’m going to share one exercise that will help our teams avoid conflicts and stay cohesive. It starts by seeing the organization as one entity, rather than a group of separate teams.

Do I see the company as one?

Adopting this perception is critical to the success of an organization, because the alternative, to see the company as parts that work separately, will never grow the company as a whole. Allow me to elaborate:

In our day-to-day, we often view ourselves as part of one specific team, one group. In turn, we subconsciously view the organization as a group of separate entities such as marketing, sales, customer success, product management, engineering, R&D, finance, etc.

The danger of this perception is that it can create inter-team conflicts: e.g. when goals are missed, we tend to blame it on other teams; when budgets are planned, we tend to fight each other for a bigger piece of the pie.

As we don’t emotionally relate to other teams as much as we do with our own team, we focus on improving only one team: Our team. This can be detrimental. Improving only one segment of the company will not result in a better company: e.g. Hitting our sales goals may not result in higher revenue if the sales team is not collaborating with customer success on retention goals.

A company thus needs all teams to be aligned on a single strategy for it to grow. It becomes clear that improving how teams interact and work with each other is more important than improving the team itself.

In one case, I was helping a clothing retailer’s merchandising team identify product trends. The goal was to find characteristics of clothing items that people would buy as part of repeat purchases, then advertise them as part of newsletters. However, because the marketing team had differing priorities, the products we identified as leading to a higher chance of repeat purchases failed to be advertised. Instead, newsletters featured customer stories in an effort to connect emotionally with users. This is not to say that the marketing team’s tactic wasn’t effective, but because both teams failed to coordinate, time and resources were wasted. The merchandising team’s effort was in vain.

The good news is that everyone is capable of seeing the company as one. We do this every day when we look at other companies.

For example, we don’t react to news on Google’s self-driving cars and say: “Wow, the marketing team on Google’s self-driving car project is really effective at …” Instead, we say: “Wow, Google is really catching a lot of eyeballs with their cars.”

Now we only have to see our own company as a unit.

Does my team see the company as one?

team

To help our team members see the company as one entity, we can perform a diagnosis of the company’s traits. This translates into the creation of a profile that defines our organization and exposes our group dynamics.

Having team members evaluate the organization as one re-enforces the mindset that we are all on the same boat, regardless of what teams we work with.

One approach is to survey all team members’ perception of the organization, asking the following questions:

  • What is your perception of our company’s current vision and strategy? How do we hope to impact the world, why, and how do we plan to achieve that?
  • What are natural tendencies and behaviors that you notice of your team, other teams, and the company as a whole? What are some biases that you observe, what do we enjoy/don’t enjoy doing, what mistakes do we repeat, and what do we prioritize and de-prioritize?
  • What frustrations do you experience that gets in the way of our company achieving its strategic goals? What are you repeatedly frustrated by?
  • What do you feel are our company’s strengths and weaknesses? What helps us achieve our goals and what drags the team back?
  • What values do we live by? Based actions and behavior observed, what values do you think we stand by?

Assembling a company profile based on every team member’s perception allows for the entire company to actively reflect on what type of animal it has become. This awareness alone will make team members more empathetic to other teams. Should we take it a step further and incentivize changes while praising improvements, teams will also implement changes to eliminate behaviors they perceive as negative or unproductive.

How often should we do this and why?

I recommend for this exercise to be performed at least twice a year for a couple reasons:

  1. Start-up companies tend to get distracted by new ideas that pull teams off alignment from the company strategy, so regular assessment helps to diagnose whether any team is going off-course, and to actively re-align them;
  2. Similarly, as a company evolves, its traits change. It’s thus important to regularly assess whether the company’s behavior is evolving in the direction that we want, creating the culture that we desire.

Let’s explore these two points in more detail.

1- Aligning teams to the company strategy

one team

In my opinion, it is easier for top leadership to set a competitive strategy than it is for them to keep all teams aligned to the strategy.

Especially at start-ups, individual teams tend to get distracted by new ideas and initiatives that fall outside of the company strategy. This is caused by a combination of factors including:

  • Ambitions and smart team members that want to change the world, but are easily distracted;
  • Ineffective communication from senior leadership about the actual strategy; and
  • Lackluster enforcement of the strategic plan.

The result is that actions across teams and individuals are misaligned and the company is pulled in all directions.

For example, a payment solution provider’s competitive strategy may be to focus on providing payment systems for large hotel management businesses, offering industry-specific solutions.

If that strategy is ineffectively communicated and ill-enforced, teams may take actions and decisions that are counter-productive. Marketing may run campaigns that attract all hotel operators, large and small, to get as many leads as possible. On the other hand, customer success may adopt a low cost strategy to boost profit margin rather than offering enterprise level support for clients.

The result will be that marketing money is wasted on attracting the attention of small and medium hotel companies we don’t want. And down the line, customer success will have a hard time retaining large clients without proper resources to create deep relationships.

Misaligned goals across an organization will thus slow down the company’s growth, if not reverse it.

To avoid such a fate, it’s critical to first decide and agree on a competitive strategy among the senior leadership team. Each department head should have a clear idea of their role as part of the strategy and who they need to collaborate with. Afterward, leaders will need to design and communicate the strategic plan to all their team members.

Results from the company profile survey will reveal whether everyone understands the strategy. Should there be confusion, misalignment, or lack of information on what team members believe the company strategy to be, we’ll need to clarify the strategy (i.e. highlight decisions and initiatives that are aligned or misaligned), actively refuse resources to misaligned initiatives, and review team goals for strategic alignment.

With limited resource, there’s no time to waste on misaligned initiatives.

Following up on our example above, the payment solution provider’s marketing goal should be to attract as many large hotel operators as leads as possible, and to neglect any small and medium size operators. On the other hand, customer success needs to provide enterprise level support with an appropriate budget.

2- Is the company maturing as desired?

evolution

Keeping an eye on the company’s behavioral tendencies, strengths, and weaknesses helps leaders acknowledge the company position, and whether we need to change course to stay relevant.

As teams gain experience tackling their problem, and as new individuals join the team, a company’s strengths will evolve and new skills will be added. On the other hand, a larger team will also bring new organizational challenges (e.g. bureaucracy, processes, politics) that may add to the company’s weaknesses and frustrations. Externally, competition and changing customer expectations will often redefine whether a company trait has become a new strength or a new weakness.

Blockbuster‘s rise and fall is a great example of a company that failed to understand itself, and its position within a rapidly changing market. With the introduction of Netflix type services and changing customer expectations, Blockbuster’s competitive advantage evaporated. What were once strengths (e.g. a lot of physical stores and access to customers) became weaknesses (e.g. too much overhead cost), while existing weaknesses grew in impact (e.g. limited stock and selection). Should they have acknowledged these market changes early, there was certainly a chance to stay relevant.

Since a start-up’s operating environment can change month-to-month, it’s critical that we regularly evaluate its evolution and position within the market.

Are we too optimistic?

optimism

It takes a healthy dose of self-belief, courage, and optimism to found a start-up company. This positive outlook on the future is foundational to the culture of most start-up companies, shared by almost all team members that decide to join a start-up and forego a safe job.

I, for one, certainly believe in my company’s eventual success, even though we’ve yet to make $1 of profit.

Fact is, a positive mindset is necessary to pursue dreams and work on unproven solutions. If we had any doubt in our success, we wouldn’t be pursuing this venture. We know that the odds are stacked against us, and yet, we decide to put up a good fight.

The upside of having an optimistic mindset is clear: We always have the energy to get back up after experiencing failure, and keep moving forward.

Yet, there is also a danger to our optimism: It can make us blind to our weaknesses. At start-ups, we have a tendency to turn a blind eye to our company’s structural problems, strategic threats, and other long-term issues. These issues tend to be ones that we can’t solve right away and necessitate company-wide collaboration. And because there’s always more urgent short-term issues to solve at a start-up, we tend to ignore our long-term challenges. With time, the team learns to turn a blind eye to structural problems and let their optimism take over.

What’s the result? Blind optimism can cloud the evaluation of a company’s true situation. And slowly, it can become culturally unacceptable to voice negative thoughts. Team members may not raise or report their frustrations and challenges, for fear of being perceived as pessimists or even worse, not believing in the company’s future success. Complaints and frustrations will often follow with someone saying “Yeah, but we work with really smart people. We’ll figure it out.” Like that adds any value to the conversation…

The leadership team is certainly not immune to blind optimism (they need it most!), so they may become unreceptive to team members’ concerns, shielded by ego and by the fear that there’s nothing they can do about the issue.

At that point, the entire company is no longer capable of objectively assessing itself. Everyone drank the cool-aid. As it is no longer looking to improve itself, the company will slowly become unable to face changing market forces, to resolve internal challenges, and ultimately, to hit its goals.

So allow me to share a word of advice: When assessing the company’s profile, ask team members to be brutally honest. In the wise words of my yoga teacher: “Observe differences, don’t judge.”

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