Business Intelligence

Profitability through Operational Efficiency

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In my last post, I discussed the importance of proper pricing for profitability and success. As most people know, you increase profitability by increasing revenue and/or decreasing costs. But, cost reduction does not necessarily mean slashing headcount, wages, benefits, or other factors that often negatively affect morale and cascade negatively on quality and customer satisfaction. There is often a better way.

Picture of a hand holding several twenty dollar bills

The best businesses generally focus on repeatability, realizing that the more that you do something – anything, the better you should get at doing it. You develop a compelling selling story based on past successes, develop a solid reference base, and have identified the sweet spot from a pricing perspective. People keep buying what you are selling, and if your pricing is right there is money available at the end of the month to fund organic growth and operational efficiency efforts.

Finding ways to increase operational efficiency is the ideal way to reduce costs, but it does take time and effort to accomplish. Sometimes this is realized through increases in experience and skill. But, often optimization occurs through standardization and automation. Developing a system that works well, consistently applying it, measuring and analyzing the results, and then making changes to improve the process. An added benefit is that this approach increases quality as well, making your offering even more attractive.

Metrics should be collected at a “work package” level or lower (e.g., task level), which means they are related tasks at the lowest level that produce a discrete deliverable. This is a project management concept, and it works whether you are manufacturing something (although Bill of Materials may be a better analogy in this segment), building something, or creating something. This allows you to accurately create and validate cost and time estimates. And, when you are analyzing work at this level of detail it becomes easier to identify ways to simplify or automate the process.

When I had my company we leveraged this approach to win more business with competitive fixed price project bids that provided healthy profit margins for us while minimizing risk for our clients. Bigger profit margins allowed us to invest in our own growth and success by funding ongoing employee training and education, innovation efforts, international expansion, as well as experiment with new things (products, technology, methodology, etc.) that were fun and often taught us something valuable.

Those growth activities were only possible because of our focus on doing everything as efficiently and effectively as possible, learning from everything we did– good and bad, and having a tangible way to measure and prove that we were constantly improving.

Think like a CEO, act like a COO, and measure like a CFO. Do this and make a real difference in your own business!

The Importance of Proper Pricing

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picture showing several bundles of money

Pricing is one of those things that can make or break a company. Doing it right takes an understanding of your business (cost structure and growth / profitability goals), the market, your competition, and more. Doing it wrong can mean the death of your business (fast or slow), the inability to attract and retain the best talent, as well as creating a situation where you will no longer have the opportunity to reach your full potential.

These problems apply to companies of all sizes – although large organizations are often in a better position to absorb the impact of bad pricing decisions or sustain an unprofitable business unit. Understanding all possible outcomes is an important aspect of pricing as it related to risk and risk tolerance.

When I started my consulting company in 1999 the plan was to win business by pricing our services 10%-15% lower than the competition. It was a bad plan that didn’t work. Unfortunately, this approach is something you see all too often in businesses today.

In our case we only began to grow once we increased our prices (about 10% more than the competition) and focused on justifying that with our expertise and the value provided. We were (correctly) perceived as being a premium alternative, and that positioning helped us grow.

Several years ago I had a management consulting engagement with a small software company. The business owner told me that they were, “an overnight success that was 10 years in the making.” His concern was that they might not be able to capitalize on recent success so he was looking for an outside opinion.

I analyzed his business, product, customers, and competition. His largest competitor is the industry leader in this space, and products from both companies were evenly matched from a feature perspective. My client’s product even had a few key features that better for management and compliance in Healthcare and Union environments that his larger and more popular competitor lacked. So, why weren’t they growing faster?

What I found is that competition was priced 400% higher for the base product. When I asked the owner, he told me their goal was to be priced 75% – 80% less than the competition. He could not explain why he did this, other than to state that he believed that his customers would be unwilling to pay any more than that. His lack of confidence with his own product became evident to companies interested in his solution.

In many cases he lost head-to-head competition against that competitor, but almost never on features. Areas of concern were generally on the size and profitability of the company, and the risk created by each for prospects considering his product.

I shared the graph (below) with this person, explaining how proper pricing would increase their profitability and annual revenue, and how both of those items would help provide customers and prospects with confidence. Moreover, this would allow the company to grow, eliminate single points of failure in key areas (Engineering and Customer Support), add features, and even spend money on marketing. Success breeds success!

Graph showing revenue relative to the life cycle stages of a successful business venture
Source: Entrepreneurial Finance by Leach and Melicher (3rd Ed.)

In another example I worked with the Product Manager of a large software company who was responsible for producing quarterly product package distributions. This work was outsourced and each build cost approximately $50K. I asked a simple question, “What is the break-even point for each distribution?” That person replied, “There really isn’t a good way to tell.”

Graph showing cost volume profit analysis
Sample cost-volume-profit (CVP) analysis

By the end of the day I provided a Cost-Volume-Profit (CVP) analysis spreadsheet that showed the break-even point. Even more important, it showed the contribution margin and demonstrated there was very little operating leverage provided these products (i.e., they weren’t very profitable even if you sold a lot of them).

My recommendations included increasing prices (which could negatively impact sales), invest in fewer releases per year, or find a more cost-effective way of releasing those products. Without this analysis their “business as usual” approach would have likely continued for several years.

Companies are in business to make money – pure and simple. Everything you do as a business owner or leader needs to be focused on growth. Growth is the result of a combination of factors, such as uniqueness of product or services provided, quality, reputation, efficiency and repeatability. Many of these are the same factors that also drive profitability. Proper pricing can help drive profitability, and having excess profits to invest can significantly impact growth.

Some customers and prospects will do everything possible to whittle your profit margins down to nothing. They are focused on their own short-term gain, and not on the long-term risk created for their suppliers. Those same “frugal” companies expect to make a profit on their own business, so it is unreasonable to expect anything less from own suppliers.

My feeling is that, “Not all business is good business” so it is better to walk away from bad business in order to focus on the business that helps your company grow and be successful.

One of the best books on pricing that I’ve ever found is, “The Strategy and Tactics of Pricing: A Guide to Profitable Decision Making” by Thomas T. Nagle and Reed K. Holden. This is an extremely comprehensive and practical book that I recommend to anyone responsible for pricing or who has P&L responsibility within an organization. It addresses the many complexities of pricing and is truly an invaluable reference.

In a future posts I will write about the metrics that I use to understand efficiency and profitability. Metrics can be your best friend when it comes to finding ways to optimize pricing and maximizing profitability. This can help you create a systematic approach to business that increases efficiency, consistency, and quality.

At my company we developed a system where we know how long common tasks would take to complete, and had efficiency factors for each consultant. This allowed us to create estimates based on the type of work and the people most likely to work on the task, and fix bid the work. Our bids were competitive, and even when we were the highest priced bid we often won because we would be the only (or one of the few) companies to guarantee prices and results. Our level of effort estimates were +/- 4%, and that helped us maintain a 40%+ minimum gross margin for every project. This analytical approach helped our business double in revenue without doubling in size.

There are many causes of poor pricing, including: Lack of understanding of cost structure; Lack of understanding of the value provided by a product or service; Lack of understanding of the level of effort to create, maintain, deliver, and improve a product or service; and Lack of concern for profitability (e.g., salespeople who are paid on the size of the deal, and not on margins or profitability).

But, with a little understanding and effort you can make small adjustments to your pricing approach and models that can have a huge impact to the bottom line of your business.

To Measure is to Know

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Lord William Thomson Kelvin was a pretty smart guy in the 1800’s. He didn’t get everything right (e.g., he supposedly stated, “X-rays will prove to be a hoax.”), but his success ratio was far better than most so he did have useful insight. I’m personally a fan of his quote, “If you can not measure it, you can not improve it.”

Business Intelligence (BI) systems can be very powerful, but only when they are embraced as a catalyst for change. What you often find in practice is that the systems are not actively used, or do not track the “right” metrics (i.e., those that provide insight into something important that you have the ability to adjust and impact the results), or provide the right information – only too late to make a difference.

The goal of any business is developing a profitable business model and then executing extremely well. So, you need to have something that people want, then need to be able to deliver high quality goods and/or services, and finally need to make sure that you can do that profitably (it’s amazing how many businesses fail to understand this last part).  Developing a systematic approach that allows for repeatable success is important. Pricing at a level that is competitive and provides a healthy profit margin provides the means for growth and sustainability.

Every business is systemic in nature. Outputs from one area (such as a steady flow of qualified leads from Marketing) become inputs to another (Sales). Closed deals feed project teams, development teams, support teams, etc. Great jobs by those teams will generate referrals, expansion, and other growth – and the cycle continues. This is an important concept to understand because problems or deficiencies in one area can manifest themselves in other areas.

Next, understanding of cause and effect is important. For example, if your website is not getting traffic is it because of poor search engine optimization, or is it bad messaging and/or presentation? If people come to your website but don’t stay long do you know what they are doing? Some formatting is better for printing than reading on a screen (such as multi-column pages), so people tend to print and go. And, external links that do not open in a new window can hurt the “stickiness” of a website.  Cause and effect is not always as simple as it would seem, but having data on as many areas as possible will help you understand which ones are really important.

When I had my company we gathered metrics on everything. We even had “efficiency factors” for every Consultant. That helped with estimating, pricing, and scheduling. We would break work down into repeatable components for estimating purposes. Over time we found that our estimates ranged between 4% under and 5% over the actual time required for nearly every work package within a project. This allowed us to fix bid projects to create confidence, and price at a level that was lean (we usually came-in about the middle of the pack from a price perspective, but the difference was that we could guarantee delivery for that price). More importantly, it allowed us to maintain a healthy profit margin that let us hire the best people, treat them well, invest in our business, and take some profit as well.

There are many standard metrics for all aspects of a business. Getting started can be as simple as creating some sample data based on estimates, “working the model” with that data, and seeing if this provides additional insight into business processes. Then ask, “When and where could I have made a change to positively impact the results?” Keep working and when you have something that seems to work gather some real data and re-work the model. You don’t need fancy dashboards (yet).

Within a few days it is often possible to identify the Key Performance Indicators (KPIs) that are most relevant for your business. Then, start consistently gathering data, systematically analyzing it, and present it in a way that is easy to understand and drill-into in a timely manner.  To measure the right things really is to know.

 

Spurious Correlations – What they are and Why they Matter

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In an earlier post I mentioned that one of the big benefits of geospatial technology is its ability to show connections between complex and often disparate data sets. As you work with Big Data you tend to see the value of these multi-layered and often multi-dimensional perspectives of a trend or event. While that can lead to incredible results, it can also lead to spurious correlations of data.

First, let me state that I am not a Data Scientist or Statistician, and there are definitely people far more expert on this topic than myself.  But, if you are like the majority of companies out there experimenting with geospatial and big data it is likely that your company doesn’t have these experts on-staff. So, a little awareness, understanding, and caution can go a long way in this type of scenario.

Before we dig into that more, let’s think about what your goal is:

  • Do you want to be able to identify and understand a particular trend – reinforcing actions and/or behavior? –OR–
  • Do you want to understand what triggers a specific event – initiating a specific behavior?

Both are important, but they are both different. My personal focus has been on identification of trends so that you can leverage or exploit them for commercial gain. While that may sound a big ominous, it is really what business is all about.

There is a popular saying that goes, “Correlation does not imply causation.”  A common example is that for a large fire you may see a large number of fire trucks.  There is a correlation, but it does not imply that fire trucks cause fires. Now, extending this analogy, let’s assume that in a major city the probability of multi-tenant buildings starting on fire is relatively high. Since they are a big city, it is likely that most of those apartments or condos have WiFi hotspots. A spurious correlation would be to imply that WiFi hotspots cause fires.

As you can see, there is definitely potential to misunderstand the results of correlated data. More logical analysis would lead you to see the relationships between the type of building (multi-tenant residential housing) and technology (WiFi) or income (middle-class or higher). Taking the next step to understand the findings, rather than accepting them at face value, is very important.

Once you have what looks to be an interesting correlation there are many fun and interesting things you can do to validate, refine, or refute your hypothesis. It is likely that even without high-caliber data experts and specialists you will be able to identify correlations and trends that can provide you and your company with a competitive advantage.  Don’t let the potential complexity become an excuse for not getting started, because as you can see above it is possible to gain insight and create value with a little effort and simple analysis.

Getting Started with Big Data

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Being in Sales I have the opportunity to speak to a lot of customers and prospects about many things. Most are interested in Cloud Computing and Big Data, but often they don’t fully understand how they will leverage the technology to maximize the benefit.

Here is a simple three-step process that I use:

1. For Big Data I explain that there is no single correct definition. Because of this I recommend that companies focus on what they need rather than on what to call it. Results are more important than definitions for these purposes.

2. Relate the technology to something people are likely already familiar with (extending those concepts). For example: Cloud computing is similar to virtualization and has many of the same benefits; Big Data is similar to data warehousing. This helps make new concepts more tangible in any context.

3. Provide a high-level explanation of how “new and old” are different, and why new is better using specific examples that they should relate to. For example: Cloud computing often occurs in an external data center – possibly one that you may not even know where it is, so security can be even more complex than with in-house systems and applications. It is possible to have both Public and Private Clouds, and a public cloud from a major vendor may be more secure and easier to implement than a similar system using your own hardware;

Big Data is a little bit like my first house. I was newly married, anticipated having children and also anticipated moving into a larger house in the future. My wife and I started buying things that fit into our vision of the future and storing it in our basement. We were planning for a future that was not 100% known.

But, our vision changed over time and we did not know exactly what we needed until the very end. After 7 years our basement was very full and it was difficult to find things.  When we moved to a bigger house we did have a lot of what we needed. But, we also had many things that we no longer wanted or needed. And, there were a few things we wished that we had purchased earlier. We did our best, and most of what we did was beneficial, but those purchases were speculative and in the end there was some waste.

How many of you would have thought that Social Media Sentiment Analysis would be important 5 years ago? How many would have thought that hashtag usage would have become so pervasive in all forms of media? How many understood the importance of location information (and even the time stamp for that location)? My guess is that it would be less than 50% of all companies.

This ambiguity is both the good and bad thing about big data. In the old data warehouse days you knew what was important because this was your data about your business, systems, and customers.  While IT may have seemed tough before, it can be much more challenging now. But, the payoff can also be much larger so it is worth the effort. Many times you don’t know what you don’t know – and you just need to accept that.

Now we care about unstructured data (website information, blog posts, press releases, tweets, etc.), streaming data (stock ticker data is a common example), sensor data (temperature, altitude, humidity, location, lateral and horizontal forces), temporal data, etc.  Data arrives from multiple sources and likely will have multiple time frame references (e.g., constant streaming versus updates with varying granularity), often in unknown or inconsistent formats.

Robust and flexible data integration, data protection, and data privacy will all become far more important in the near future! This is just the beginning for Big Data.