Where to Start with IoT

In our post on Four Ways to Create Value with IoT, we discussed at the end the fact that making products better and making better products has a bigger impact on profit. And most companies want the biggest possible impact on profit.

So, – is making better products the place to start? No.

Why? Because it’s a difficult and complicated process. It’s best to start simple and grow into the more complex and impactful benefits of IoT.

It’s easier to wire up equipment with only a few sensors (or use existing sensors) and pull a limited amount of data and to focus on simpler tasks…improving asset utilization and optimization.

You can start with either improving maintenance or operating your equipment better. This requires less data, less analysis, and smaller changes in the product and company processes and culture when compared to the amounts of data and company changes required for innovation and invention.

Let’s take an electric motor as an example. Let’s say you manufacture these motors and sell them to customers. It’d be wonderful to start inventing new types of motors. However, you would need a lot of data about all aspects of how the motor is run, the environment in which it’s used, and the customer’s business. You would also need the capability and team to analyze that data to come up with new ideas. That sounds complicated.

Let’s compare that to adding a vibration sensor to the barring housing and a temperature sensor to the body of the motor. We should start by doing this for a single motor in our test or service shop. By adding “slap and stick” sensors retrofitted onto an existing motor, we’re already making the process simpler because we’re not having to reengineer any aspect of the motor.

Now let’s set up a gateway, pull it into an off-the-shelf IoT software platform to get the data from the motor, collect the data, and monitor the data. Are we able to see what normal conditions look like? Can we run the machine enough such that it starts to exhibit the behaviors we often see in the field such as vibrations from a barring that isn’t lubricated? What do those signals look like? Depending on the IoT software platform and related analytics tools we’re using, we might be able to relatively easily define some algorithms that can identify normal and specific abnormal behaviors. [KP1]  Then, the IoT platform allows us to set alerts to trigger the need for a service event. If we have this working well enough, then we can start to retrofit some motors in the field at a few customers’ sites. We can then continually improve the analytics, business activities, and decisions that come from the analytics, and business value from the whole setup.

Once the value is proven, then it’s time to move forward to execute other projects in this IoT journey which can drive down more costs and generate more revenue. Next might be adding the sensors to the motor during manufacture, providing data to our company and to customers to enable more efficient operations of the equipment. Eventually, the company can move to innovation and invention which require a lot more work and internal capabilities to realize value.

Keep in mind starting with maintenance should be accompanied by a review of your current equipment maintenance records, the performance of your equipment, and maintenance culture and practices. We can put you in contact with people and companies that perform these assessments and provide very valuable recommendations and follow-on services.

If you have any questions on how to start the IoT journey, or on maintenance and reliability best practices please call us, we’ll be happy to chat. We can help evaluate if an IoT journey makes sense. Additionally, we have many contacts in the maintenance and reliability community through our trusted partners and from our heavy participation in SMRP (Society for Maintenance and Reliability, smrp.org).

How to Measure the Value of IoT

 How to Measure the Value of IoT

Are you wondering if you should tackle IoT (Internet of Things), or if you should start developing an Internet of Things product? The answer lies in whether the IoT aspect of the product can be valuable to your company.
Many companies start IoT projects because their competition is doing IoT, and they’re afraid to be left behind. That can be reason enough to consider starting into IoT. However, an IoT project is a complex venture and is a long-term journey, not a short-term project. So, a company should start an IoT project only if it’ll be valuable to the company.
In my next post, I will share the 4 ways that IoT can be valuable to your company so can easily and quickly determine if you should pursue it.
Today, let’s start with what we mean  by creating value with IoT:
Connected devices and smart devices have limited value compared to an IoT device. For example, I use a small Fitbit-like wristband product. It performs its limited function well by tracking and recording my steps, heart rate, and when I ask it to it’ll record my blood pressure. It also connects with a proprietary app on my iPhone which allows me to see that data a few days at a time. However, this device and the phone app don’t connect to other sets of data. Nor does it then combine the various sets of data and present it to me or others where it could be more valuable.
For example, theoretically, it could connect to data from exercise devices like a Peloton (if I used one) to coordinate exercise regimes or set specific exercise goals. It also doesn’t send the data over the internet and combine it with my medical history or my fork and spoon to track food intake or to my debit card to see how many times I go to the local pub to have a couple of tasty beers. The device would be more valuable to me if it were to connect with some or all that data, combine the data in such a way so I can see evidence of my exercise and eating actions and the results I’m getting in a healthy body. It would be even more valuable if the data were available for my physician or exercise trainer, so they can help coach me to live better (accountability would be a big motivator here).
Let’s look at another brief example. Do you have some CNC machines in your shop? Do you need to use TeamViewer or a similar remote computer access tool to see data on that machine? The data might be tool paths, production results, machine status, and machine usage. That data could be automatically pulled from each of the machines, connected with orders and sales orders data from the ERP system, and combined to add a lot more value. The value could come in being able to optimize production schedules and forecasts based on real-time data or get early indicators of when a machine is acting up and may need to be scheduled for maintenance and repairs to prevent unplanned downtime.
These are examples of how simple connected and smart devices aren’t as valuable as an IoT device, a device that pulls data over the internet, connects it with other data, and turns it into very valuable information.

How to Evaluate Prospective Vendors, Part III – Value as Return on Investment

This is the third post in a 3-part series on how to evaluate prospective vendors.

Evaluating Value as Return on Investment (ROI)

Another way to inform decisions about whether a vendor will be a good one is by quantifying the value the vendor delivers. You can measure this value in a few ways:

1) Ask. Just ask the vendor to tell you about what value they deliver to your company. If they can’t do it, that’s a red flag.
2) Calculate the Return on Investment (ROI). You can figure the ROI of a project before it starts to determine whether it’s worthwhile to invest.
3) Go with your gut. This is a subjective, gut-check measure. Does the vendor add to or alleviate stress and worry for you? Chances are, whatever you’re feeling now, you’ll feel even more in the future.

Companies often decide to move forward with projects based on subjective beliefs. They might ask for the price of the project and then measure that against some unknown and subjective number in their head about what they believe the project should cost. That’s not a great method. Yet business owners, C-suite leaders, and managers who usually make great decisions in other areas using objective reports and KPIs can sometimes decide to do a project such as a software fix without objective information.

Here’s what should be happening instead: they should evaluate the project cost against the expected benefits of the project measured in dollars and then discuss whether that return is appropriate. Calculating the ROI of a project is not difficult. ROI is calculated by dividing the cost of the project by the benefit of the project, with the final value expressed as a percentage (%):

ROI % = (Benefit – Cost of Investment) divided by the Cost of Investment x 100

The calculation does not need to be exact. Using reasonable educated guesses is far better than using no data measures at all. To value the benefits, you can factor in cost savings, Total Cost of Ownership (TCO), and potential revenue or profit growth. The project cost is provided by the vendor.

Let’s run through a quick example:

A high-level manager of a company currently spends 3 hours every morning manually manipulating data in Excel files to arrive at solid project schedules and resource plans. Let’s start by establishing the approximate value of those three hours of management time:

The manager’s annual salary with benefits is $150,000. Using 2,000 working hours per year, we can calculate the value of the manager’s time at $75/hour. Multiply that by 3 hours a day, 5 days per week, 50 weeks per year. The result is roughly $56,000.

This value doesn’t even consider the value of other more valuable tasks not being performed by that same person that could be completed if they were freed up to the work. So that can also be calculated and added to the total. Maybe if the manager captured those 3 hours every day and was able to spend that time creating new enterprise customer relationships, the net of those potential projects could be $100,000. Adding that to the saved time value brings the total project benefit value to $156,000.

The vendor has quoted that the project will cost $50,000.

We can now calculate ROI, using the formula above:
ROI % = (Benefit – Cost of Investment) divided by the Cost of Investment x 100

(($156,000 – $50,000) / $50,000) x 100 = 212%

That’s a solid return on the investment for the first year, which is likely to improve in the following years when costs of the solution should be lower while the benefits continue.

In summary, asking about, quantifying, and getting a feel for the value a vendor delivers on any given project are great ways to evaluate whether it is likely to be a successful client-vendor relationship. Great vendors are already having these discussions with their clients. That’s how they become true “partners”, and that’s the kind of vendor you should look for.

This is the third post in a 3-part series on how to evaluate prospective vendors.

Software Selection, Part I

This is Part I of a two-part post that walks you through a framework for software selection. In this post, we’ll cover the steps you should take before you even start shopping.

If you are planning to select some software to run a certain set of business processes within your company, please be very thoughtful and careful with that decision. Selecting the wrong software can be very, very costly!

Here are a few key issues to think about in the software selection process:

Define a Goal

Start with defining the outcomes that will occur once the software system is in place. How will the business be better? Faster order processing time so you can get orders to customers faster? Reduced errors, which saves money with returns and reorders? There might be multiple outcomes. If so, I’d suggest selecting the top one or two most important outcomes. Then figure out how to measure that outcome. Use dollars, minutes or hours, number of canceled orders, or something else you can specifically and easily measure. Then set a new outcome value as a goal. After the software system is installed, continually measure this value to see if you reach the goal intended with the software system. If you do, then you know the project was a success. You can also use that key performance indicator (KPI) as a way to check whether the potential software system being evaluated will help move the needle on the KPI in the right direction.

Document your Requirements

Write down the requirements for the software system you feel you need. I’d suggest creating the list of features as the first column of a spreadsheet. Then create columns to the right of that for each software system you find, and enter a tick mark or score for whether that system has that feature.

If the type of software system you need is common, such as an accounting and finance or ERP system, you can likely find some template documents on the web which will give you a solid head start.

Document the Differentiating Requirements

It is also a good idea to define what requirements or criteria will make the difference in selecting one software product versus another. For example, if you are a footwear manufacturer and will have a lot of SKUs for your products based on the combination of style, size, width, and another attribute or two, then be sure to add that capability to the list. Other examples might be multi-company capabilities, the budget available to purchase the system, and whether you prefer the solution to be locally installed versus running from the cloud. Be sure your understanding of these requirements is well founded. For example, if you don’t know what it even means for the software product to be on-prem (installed locally, on premises) versus the cloud (on servers in a data center, or using a SaaS system), then your software selection will not be efficient or return good results. This short list of unique attributes of your needs can often be a quick way to eliminate software products from the initial long list.

Next week, we’ll cover how to create your product shopping list and how to choose the right software for your company.

Start Small with Business Intelligence (BI) Projects

If you can use pivot tables, you can do BI. Here’s how.

A BI project doesn’t need to be complex. You can start off small.

Here is an example using a construction company with project managers and schedulers:

Imagine you’re a project manager (PM) and your boss comes to you asking why it takes so long for a lot of small projects to be reviewed, approved, and scheduled after they’re submitted to your team. You know you’ve been under a lot of pressure, wearing several hats in your job, putting out a lot of fires. And you kind of knew this was an issue, but you didn’t know what the real cause of the issue was.

How do you find the answer? Ultimately, you know you need to pull and clean a lot of data, analyze it, and then start fixing the parts of business processes once the analyses point you in the right direction. This can be completely overwhelming, and potentially expensive if you looked at the situation as a whole. And if it were expensive, your boss might not give you the budget approvals to start anyway.

Instead, take it in small bites. Try to narrow the situation to a short statement of the problem, your theory or hypothesis of the cause. Like this:

             Problem: Once we get a project, it takes us a long time to review, approve, and schedule it. We need to do it faster without negatively impacting the quality of our work.

             Theory: I believe it is because Fred doesn’t understand how to review our road-building projects and takes too long, and that’s 70% of the work we do.

Then, get the data for that one specific situation and throw it into Excel PowerPivot (no need to get expensive software tools, keep it lean and affordable).

Pull the related data from your project management software and export it to an Excel file. Include fields that define the date it was received, reviewed, approved, and scheduled. Also pull data on who received it, who reviewed, who approved, who scheduled. Finally, pull the fields that define the various types of projects, sizes of projects and other useful attributes.

Use Microsoft Power Query to clean up the data as needed (dirty data doesn’t give clean results). Power Query has a lot of capabilities.

Sample this post to understand one of many ways to clean and transform your data

Once cleansed, then create some new columns to give you more data to enrich the analysis.

Add columns that calculate the number of hours or days between the various events of receiving, reviewing, approving, and scheduling projects.

Then create a few simple pivot tables using Power Pivot to understand the data.

Create a simple pivot table of the average time from receiving and reviewing by project type. Then a similar table by the person doing the reviewing and by project type. Maybe another table by another attribute of the project like the location of the project or size of the project. Where is most of the time spent reviewing projects? Anything look odd there? Are small projects taking longer to review than larger projects? Is Fred taking longer than everyone else on the road-building projects? You can also easily insert a simple chart too if seeing bars help you more easily identify unusual situations in the data. If you can narrow in on definitive causes you can now start coming up with solutions within the business.

Once you have discovered the root cause(s) of the issue, you can come up with a solution, and implement it. Then, it’s a good idea to keep an eye on the situation over time. Did the solution work? Or not?

Maybe once a month follow the same process as before to prepare the data and run the pivot tables and charts. How is Fred doing now on the projects he’s more comfortable with? Is his mean time to review a project faster? Are the road projects which were given to someone else being reviewed faster? Then start looking for the next low-hanging fruit problem to solve.

Up to this point, you don’t even need to use Power Pivot if you don’t want to. You could use Excel and pivot tables. Though you will eventually be limited to the extent you can analyze and visualize the data.

If you haven’t used Power BI up to this point but want to continue using it to analyze the data, here are some examples of how you could use it:

  • Use Power Query to set up data sources to pull from your database or Excel files that are used to track projects. Then you can pull and cleanse the data at the click of a button.
  • Create a dates/calendar table and add it to the Power Pivot data model to make it easier to analyze data with various types of dates and date calculations.
  • Add data from tables of a SQL Server database (assuming that’s where the software’s data lives) to the Power Pivot data model to provide more useful data for the analysis.
  • Read and learn more about the capabilities of these tools. They are incredibly powerful. A great place to start is the blog and training courses (online and in-person) of our good friends at P3 Adaptive.

Ectobox is helping a company through this process right now. They have a department that is really busy and constantly changing how it does its work as a result of rapid growth within the company. This department is finding out how difficult growth can be. Their old business processes are causing bottlenecks, but they’re not exactly sure why or where those bottlenecks exist.

We’re starting off simple by using Excel PowerPivot, pulling data from a single SQL Server database, creating a small data model for only the tables needed for this specific situation, creating only a few charts, giving the whole Excel PowerPivot file, and connecting it to the SQL Server database. So, we’re building the fishing net, so to speak, and then we’ll teach them how to fish.

If this process takes hold and our client finds value in analyzing this data, they may start to realize the power and value of the data they have. This could lead eventually to the development of a truly data-driven culture, giving them unlimited opportunities for increasing profitability.

Do the Basics First in Reports and Business Intelligence

It’s like baseball. You want to focus on the fundamentals before you try the expert moves.

Let’s say you’re watching your local team slide in the standings, as we have unfortunately seen with the Pittsburgh Pirates. You’ll hear the sportscasters and managers and coaches talk about getting back to the basics before they get fancy.

It’s a solid piece of advice. If you have complex systems, and not everything is working, it’s best to keep it simple, and focus on these basics first:

1) Know your desired outcomes. What do you want to know from your software and reporting systems? How will the business benefit from tracking this data? What insights do the higher-ups need to make important business decisions?

2) Identify only the data you need to gather to get those reports. Don’t add an extra field or two because you think you might use it in 10 years. Focus on what you need now and only in the near term. There is always room for improvement LATER.

3) Create a list of issues that need to be fixed. Add details to each item such as specifically how to reproduce the issue or where it is, what is the result you’re seeing now, and what result should you see.

4) Tackle each item one by one. Make a concerted effort to not jump ahead, not to tackle only the easy ones, and not to allow yourself (or whomever is implementing) to get distracted and go off and do other things.

If you’re able to execute these basics, then you will surely climb up in the rankings and have great success.

Case in point: We are working with large manufacturing company that was acquired and is experiencing similar issues. There are some legacy software, database, and reporting systems left behind, not all of which work. We are starting our work by helping them get back to what they’re calling “ground zero”. We are identifying what business outcomes they want from the system, defining the details of what needs to be fixed, and cranking through the issues one by one until they are all fixed. Once done they’ll be really happy and will be able to have the data needed to make important business decisions. They will also be in a much better position to define and pull out new sets of data for data analysis and reporting to take the business to the next level.

The Biggest Software Mistake Your Company is Probably Making

error-blog 1 picMost companies spend a lot of time thinking about IT — information technology – which refers to computer hardware, computing capabilities, storage, transmission, security, etc. Virtually everyone works on or with a computer or electronic device of some kind. Evolving technology is “in our face” all the time. You can’t help but see colleagues with the newest gadget, smartphone, or laptop, or read headlines about what Apple is up to next, or the latest security breach. Our awareness of changing technology and the associated risks is high. So most companies, whether or not they have a CTO, have a strategy for keeping their tech up to date. For example, a company may have a policy that desktops are replaced every 5 years, laptops every two years, and smartphones are BYO. IT is often what CIOs and IT directors/managers think of first. They certainly think about and focus most of their time on IT, keeping the servers up and running.

But what often gets lost in the focus on the latest and greatest tech is the information that all that tech is managing. A company’s information is worth much more than their hardware: it represents the company’s assets, including customer lists, product information, intellectual property, and historic documentation. And it’s the information that represents the company’s growth potential for the future. So an information systems (IS) strategy – one that addresses which software a company uses and how to manage data and data transmission— is a critical part of a company’s planning. Many CIOs neglect to consider how information systems could and should support business growth.

What happens then is the tools selected, the data stored, where and how the data is stored, the quality of the data, how the software works, the functions the software performs, the reports and data analysis it provides, etc. eventually becomes cumbersome, gets in the way of business growth. People in operations as well as in IT spend more time supporting the systems than using them.

So what is an IS strategy?

An IS strategy is an approach to managing your company’s information assets with software that reflects your company’s values and best helps your reach your goals, regardless of what other companies or the rest of the market is doing. It gives you a framework for making decisions so you can be confident about what software to buy (or NOT buy), where the software should be hosted, what types of technical people you need and whether they are on staff, contracted, or brought in as vendors.

Why do I need one?

The reason you need an IS strategy one is closely related to the reason you have a corporate strategy, or a market strategy, where you make business decisions based on corporate values and goals. Only you know best what those values and goals are. There will always people advising you to choose the newest, best, or most robust software, but there really is no “one size fits all” software. Think of it like a vacation destination: say you are going to the beach, and you check GPS for directions. The “best” directions depend on your personal goals for the trip: do you want to get there as fast as possible? Or would you rather avoid congested highways? Or make a side trip to visit a friend on the way? There are many roads you can take to reach your destination, and each has pros and cons.

The same applies to an IS strategy. Is your company taking a slow, organic growth model, or aggressively pursuing growth that will result in significant changes for the company (hiring many new employees, increasing leads, transactions, production, shipments, etc.)? In a small company, operations are more straightforward and manageable. But if your company is approaching or passing the 50-employee mark, the increased size and complexity of your structure and operations necessarily leads to complexity in your IS setup and needs. The same is true and more so if your company is passing the 1,000-employee mark. That increased size underlines the need for a formal IS strategy since it becomes increasingly difficult to track and share information.

Without a clear sense of what software you need to run the organization now and in the future, you don’t have a way to know what software is and is not appropriate to acquire and implement. Without an IS strategy, CIOs may select products or allow departments to select products to address specific needs, and eventually end up with overlapping or incompatible systems, a hodgepodge of tools that don’t work well together and hold the company back by wasting valuable employee time in process and data inefficiencies. Additionally, unplanned decisions on data storage, software design architecture, locally or remotely hosted software applications, etc. can have a serious impact on the success of a business when an IS strategy is not in place.

To summarize, an IS strategy enables a business’s future plans and helps them succeed by selecting the best data storage, software, and reporting/analysis systems to achieve their business goals, and making the best software functional decisions that work in concert with a company’s overall business plan for future success.

Next Up: Find out what a winning IS strategy looks like and how to build one for your company.