Is Your Organization Capable of Competing in a Data Driven World? – Part 3



Getting Teams Equipped to Share Everything Not Just Some Things.

Technology has been both a cause for the challenges companies experience and the tools for success.  But it is the change in culture in the organization that allow leaders to leverage data driven decisions properly.

At the core of this journey to adaptability lay a yin-and-yang symmetry of shared consciousness, achieved through strict, centralized forums for communication and extreme transparency, and empowered execution, which involves the decentralization of managerial authority.  Together, these power the evolution of a data driven enterprise to use it properly.

Your transformation is reflective of the new generation of mental models we must adopt in order to make sense of the twenty-first century.  If we do manage to embrace this change, we can unlock tremendous potential for human progress.

So here are some of the principles we’ve developed over the years to enable and protect a healthy data driven culture.  I know that when you distill a complex idea into a T-shirt slogan, you risk giving the illusion of understanding – and, in the process, of sapping the idea of its power.  An adage worth repeating is also halfway to being irrelevant.  You end up with something that is easy to say but not connected to behavior.  But while I have been dismissive of reductive truths throughout this series, I do have a point of view, and I thought it might be helpful to share some of the principles that I have found to be most effective in developing a new culture.  

“The trick is to think of each statement as a starting point, as a prompt toward deeper inquiry, and not as a conclusion.”


  • Give a good idea to a mediocre team, and they will screw it up.  Give a mediocre idea to a great team, and they will either fix it or come up with something better.  If you get the team right, chances are that they’ll get the ideas right.


  • If there are people in your organization who feel they are not free to suggest ideas, you lose.  Do not discount that ideas come from anywhere in the organization.


  • It isn’t enough merely to be open to ideas from others.  Engaging the collective brainpower of the people you work with is an active, ongoing process.  As a manager, you must coax your staff and constantly push them to contribute.


  • Do not fall for the illusion that by preventing errors, you won’t have errors to fix.  The truth is, the cost of preventing errors is often far greater than the cost of fixing them.


  • Change and uncertainty are part of life.  Our job is not to resist them but to build the capability to recover when unexpected events occur.  If you don’t alway try to uncover what is unseen and understand its nature, you will be ill prepared to lead.


  • Similarly, it is not the manager’s job to prevent risk.  It is the manager’s job to make it safe to take them.


  • Failure isn’t a necessary evil.  In fact, it isn’t evil at all.  It is a necessary consequence of doing something new.


  • The people ultimately responsible for implementing a plan must be empowered to make decisions when things go wrong, even before getting approval.  Finding and fixing problems is everybody’s job.  Anyone should be able to stop the production line.


  • A company’s communication structure should not mirror its organizational structure.  Everybody should be able to talk to anybody.


  • An organization, as a whole, is more conservative and resistant to change than the individuals who comprise it.  Do not assume that general agreement will lead to change – it take substantial energy to move a group, even when all are on board.


  • Do not confuse the process with the goal.  Working on our processes to make them better, easier, and more efficient is an indispensable activity and something we should continually work on – but it is not the goal.  Making the product great is the goal.


The path to a data driven company is one that is achieved through the balance of technology and culture.  The “dark data” that your organization has accumulated over the years is where we have focused our attention.  Illuminating that data and making it useable for your people to make decisions is the goal that comes from building a culture of trust and shared consciousness.

If you would like to learn more about how InCloud Control has helped other companies on this journey please feel free to send us a note at: 

hello@myincloud.com or call us at (404) 316-0082 

Is Your Organization Capable of Competing In The Data Driven World? Part 2

2015-11-03 09.58.42 am

The Assembly Line of Information Sharing is Broken – There is one main critical flaw in the way companies have been structured and managed over the past 100 years.  What once worked for as a proven methodology to improve efficiencies in American assembly line environments is no longer a viable organizational structure in today’s constantly changing world.

The traditional top down leadership styles are creating two very important gaps in an enterprises ability to adapt:

Information captured at the operator level (point of production) takes too long to get to the leadership that is both analyzing the data and making decisions based on that data.

Decisions made at the top trickle down creating old and irrelevant intelligence for the operators.

The shift in organizational structure must move from assembly line mentality to that of a living organism.  Let me explain.

When operators on a plant floor are faced with data that provides them insight into a specific asset failure, the optimal decision for action should be made by the individual closest to the action.  However, in an assembly line organizational structure, the information travels through the chain of command up the food chain.  The result is an operator with the ability to make a decision – but a structure that is not set up in a way that they can impact immediate change.

So the information travels down the conveyor belt to your analysts and managers that look at multiple options and arrive at the best possible solution that creates the lowest amount of impact on the production schedule and outstanding orders in the pipeline.  Oftentimes we see the scenario where by the time a decision is delivered back down the assembly line the machine has already deteriorated into a fail state or a faulty part has been shipped and a costly recall needs to be initiated.

The Solution is Simple but not Easy – In an assembly line organization – leadership looks at each functional station as an independent part of the process that flows with a predictable rhythm and governance.  The problem with this is that the further the information flows away from the operator the less accurate and impactful it becomes.

When we describe the organizational shift to that of a living being our customers are able to understand the disconnect and can now begin taking the proper steps to support that structure.  Think of your enterprise structure as a human body.  The leadership is the head, the maintenance team are the legs, the production team are the arms, and the assembly line operators are the hands.  When we touch a hot surface – immediately our head knows that something is not right – our arms are connected directly to the the hands so they know what’s up immediately – and if it’s a fire and we need to get the heck out of the building our legs are quick to take us away from danger.  We don’t have to wait for each part of our body to analyze the fact that we just touched something hot.  The head doesn’t have to check with the arms or legs to know if they should react and respond to the hand’s discovery.  No – the body is completely connected.  It is interdependent throughout.

The shift from disconnected and long feedback cycles to interdependent shared experiences is where we will focus our next post.  Part 3 is the most difficult part of getting this process started…

Getting Teams Equipped to Share Everything Not Just Some Things.

If you have any questions or would like to engage with us to help your organization execute on the challenges of a massive change in structure give us call (404) 316-0082 or email us at info@myincloud.com

Is Your Organization Capable of Competing in a Data Driven World? – Part 2


The Assembly Line of Information Sharing is Broken – There is one main critical flaw in the way companies have been structured and managed over the past 100 years.  What once worked for as a proven methodology to improve efficiencies in American assembly line environments is no longer a viable organizational structure in today’s constantly changing world.
The traditional top down leadership styles are creating two very important gaps in an enterprises ability to adapt:
  1. Information captured at the operator level (point of production) takes too long to get to the leadership that is both analyzing the data and making decisions based on that data.
  2. Decisions made at the top trickle down creating old and irrelevant intelligence for the operators.
The shift in organizational structure must move from assembly line mentality to that of a living organism.  Let me explain.
When operators on a plant floor are faced with data that provides them insight into a specific asset failure, the optimal decision for action should be made by the individual closest to the action.  However, in an assembly line organizational structure, the information travels through the chain of command up the food chain.  The result is an operator with the ability to make a decision – but a structure that is not set up in a way that they can impact immediate change.
So the information travels down the conveyor belt to your analysts and managers that look at multiple options and arrive at the best possible solution that creates the lowest amount of impact on the production schedule and outstanding orders in the pipeline.  Oftentimes we see the scenario where by the time a decision is delivered back down the assembly line the machine has already deteriorated into a fail state or a faulty part has been shipped and a costly recall needs to be initiated.
The Solution is Simple but not Easy – In an assembly line organization – leadership looks at each functional station as an independent part of the process that flows with a predictable rhythm and governance.  The problem with this is that the further the information flows away from the operator – the less accurate and impactful it becomes.
When we describe the organizational shift to that of a living being our customers are able to understand the disconnect and can now begin taking the proper steps to support that structure.  Think of your enterprise structure as a human body.  The leadership is the head, the maintenance team are the legs, the production team are the arms, and the assembly line operators are the hands.  When we touch a hot surface – immediately our head knows that something is not right – our arms are connected directly to the the hands so they know what’s up immediately – and if it’s a fire and we need to get the heck out of the building our legs are quick to take us away from danger.  We don’t have to wait for each part of our body to analyze the fact that we just touched something hot.  The head doesn’t have to check with the arms or legs to know if they should react and respond to the hand’s discovery.  No – the body is completely connected.  It is interdependent throughout.
The shift from disconnected and long feedback cycles to interdependent shared experiences is where we will focus our next post.  Part 3 is the most difficult part of getting this process started…
Getting Teams Equipped to Share Everything Not Just Some Things.
If you have any questions or would like to engage with us to help your organization execute on the challenges of a massive change in structure give us call (404) 316-0082 or email us at info@myincloud.com

Is Your Organization Capable of Competing In The Data Driven World? Part 1

2015-10-15 02.37.09 pm

 

The impact big and fast data has made on organizations has never been more critical. There is no shortage of data sources or credible insights to help organizations to take action. So the question we asked ourselves at our latest contract with a major manufacturing company was this:

“Why is the compressor that our predictive analytics platform identified as a 90% assurance that complete failure would occur in 6 weeks not on any maintenance team’s list 4 weeks after the first alert was announced?”

 

The answer to this led us on a six-month journey through an introspection of the organizational structure that would change our client and our perspective forever.

Silo Walls Must Come Down
What once was an organizational structure that worked in 1952 when this company first began manufacturing parts for the automotive industry – was no longer viable in an era of fast moving data and changes by competition and customers.

Operations, Maintenance, Reliability, Accounting, Safety, and Sales Teams were all functioning in isolated units. Each had been created in this fashion to derive efficiency and cost cutting measures. In addition the historical relevance of each independent unit had been created as a vertical distribution of information – mostly in the form of specific instruction from the top down. This is no anomaly in the broad overview of American companies. Without exception manufacturing organizations have been functioning under this model for over 100 years.

The reason this model had been adopted throughout the modernization of manufacturing dates back to the inception of the assembly line and the methodology deployed around improving efficiency and cutting costs. By limiting the view of the assembly line worker to a short list of tasks, companies were able to measure specific movements down to the second. This created a hierarchal approach to managing workers, performance, and above all information.

By employing a “Need-To-Know” mentality around information – these units within the organization had become highly competitive around performance, innovation, efficiency, and control. By most accounts during our discovery phase – managers were incentivized by their individual units “efficiency rating” vs. all other units within the organization.

This culture of competition and lack of sharing and collaboration had created very thick and high walls around and more importantly between the other units.

Introducing Data Exposes The Interface Breakdown
When InCloud Control was first contracted to deliver a predictive failure analytics platform to this client we attacked the problem as we always had – as a system integrator with a focus on the IT function. We understood the manufacturing process. Our platform had already been integrated with the historian that was aggregating all of the machine sensor data. We integrated nicely with their maintenance platform. We had established push notifications to the maintenance team when a failure signature was discovered. We had provided everything a company needed to react to the data.

The problem as we soon discovered was not with the data and information we were providing. The problem was in how that data was being acted upon.

Operations was unwilling to take a machine out of production because that would affect the VP over operations bonus. The maintenance team had an ever growing list of repairs that needed to be completed so that the VP of maintenance didn’t miss her bonus. The reliability team didn’t want to disrupt the efficiency of the performance and longevity of the equipment by taking it out of production because… Yep the VP of reliability would take a hit against his bonus. Why would anyone want to work together to fix a very expensive machine when it would be taking money out their collective pockets?

There was the problem and we needed to first understand the problem before we could figure out how to fix it.

In part 2 we will discuss how we transformed this organization into the data driven team they have become today.

If you would like to learn more about InCloud Control and how we can help your company integrate our great predictive analytics solutions into your organization give us a call at:

(404) 316-0082 or email us at hello@myincloud.com

Is Your Organization Capable of Competing In The Data Driven World? Part 1



The impact big and fast data has made on organizations has never been more critical.  There is no shortage of data sources or credible insights to help organizations to take action.  So the question we asked ourselves at our latest contract with a major manufacturing company was this:


“Why is the compressor that our predictive analytics platform identified as a 90% assurance that complete failure would occur in 6 weeks not on any maintenance team’s list 4 weeks after the first alert was announced?”


The answer to this led us on a six-month journey through an introspection of the organizational structure that would change our client and our perspective forever.

Silo Walls Must Come Down
What once was an organizational structure that worked in 1952 when this company first began manufacturing parts for the automotive industry – was no longer viable in an era of fast moving data and changes by competition and customers.

Operations, Maintenance, Reliability, Accounting, Safety, and Sales Teams were all functioning in isolated units.  Each had been created in this fashion to derive efficiency and cost cutting measures.  In addition the historical relevance of each independent unit had been created as a vertical distribution of information – mostly in the form of specific instruction from the top down.  This is no anomaly in the broad overview of American companies.  Without exception manufacturing organizations have been functioning under this model for over 100 years.

The reason this model had been adopted throughout the modernization of manufacturing dates back to the inception of the assembly line and the methodology deployed around improving efficiency and cutting costs.  By limiting the view of the assembly line worker to a short list of tasks, companies were able to measure specific movements down to the second.  This created a hierarchal approach to managing workers, performance, and above all information.

By employing a “Need-To-Know” mentality around information – these units within the organization had become highly competitive around performance, innovation, efficiency, and control.  By most accounts during our discovery phase – managers were incentivized by their individual units “efficiency rating” vs. all other units within the organization.

This culture of competition and lack of sharing and collaboration had created very thick and high walls around and more importantly between the other units.

Introducing Data Exposes The Interface Breakdown
When InCloud Control was first contracted to deliver a predictive failure analytics platform to this client we attacked the problem as we always had – as a system integrator with a focus on the IT function.  We understood the manufacturing process.  Our platform had already been integrated with the historian that was aggregating all of the machine sensor data.  We integrated nicely with their maintenance platform.  We had established push notifications to the maintenance team when a failure signature was discovered.  We had provided everything a company needed to react to the data.

The problem as we soon discovered was not with the data and information we were providing.  The problem was in how that data was being acted upon.

Operations was unwilling to take a machine out of production because that would affect the VP over operations bonus.  The maintenance team had an ever growing list of repairs that needed to be completed so that the VP of maintenance didn’t miss her bonus.  The reliability team didn’t want to disrupt the efficiency of the performance and longevity of the equipment by taking it out of production because…  Yep the VP of reliability would take a hit against his bonus.  Why would anyone want to work together to fix a very expensive machine when it would be taking money out their collective pockets?

There was the problem and we needed to first understand the problem before we could figure out how to fix it.

In part 2 we will discuss how we transformed this organization into the data driven team they have become today.

If you would like to learn more about InCloud Control and how we can help your company integrate our great predictive analytics solutions into your organization give us a call at 

(404) 316-0082 or email us at hello@myincloud.com


How Machine Learning Saved Thanksgiving

Thanksgiving is next week already and the plans have been set for family, turkey, and kicking back watching my Detroit Lions disappoint me in the 4th quarter.

Managing a manufacturing company with a backlog of work always meant to me that we would be running at least two shifts on Thanksgiving day.  And without hesitation – I would get the phone call from the plant that one of our key production machines was down and needed repair.

Now if your wife is anything like mine she would give me that look that said, “Don’t you dare leave this table right now. ”  And like every other year, I would have to step away from the family and start scrambling to contact our maintenance team, manufacturer rep of the machine for parts, and try to find a way to get the production team back online.

Then I discovered Mtell.  They educated me on the fact that my machines were already “smart machines” and were trying to communicate with me, but I just hadn’t taken the time to listen.

You see, all of the key production equipment we have on the shop floor was already sensored and the data produced from those sensors was just sitting in our historian.  Yes we had implemented a CMMS and an EAM to help us schedule routine maintenance, but frankly the repairs sometimes were the cause of the machine breaking down shortly thereafter.

What I discovered through implementing Mtell Advance was that the cost of getting started was directly related to how long I had waited to purchase the software solution in the first place.

Installation took just a couple days to get everything talking to the smart machine learning engine.  Within 8 days Mtell had consumed 2 years of sensor data and connected the failure relationship to my Maximo system.  The maintenance dates, along with the repair records was now a part of the body of data Mtell was comparing the real time feed to.

Normal operating conditions, failure signatures, and outlier anomalies became the “new language” of the plant.  When something was out of the normal operating condition – a text message was automatically sent to myself and the maintenance team to go investigate.  The more we learned about what our machines were saying – the smarter our team and our machines got.

It’s now been two years of running Mtell within the plant and we have avoid over 30 machine failures because of advanced warning from the top ten list of sensor signature contributors.

I have to admit – I’m actually looking forward to sitting down to the table this year knowing that my turkey and mashed potatoes will be warm and delicious – and that I won’t be getting that look from my wife.

Happy Thanksgiving everyone!

Introducing Your Next Favorite Company


INCLOUD is first-and-foremost a cloud-based advanced analytics company.  

 
What that means to our customers is zero spend on the infrastructure that makes analytics possible.  Every other company that tries to sell you on analytics is going to convince you to spend an enormous amount of money on tools, databases, hardware, visualization tools, and the expert talent required to make it all work and develop the algorithms to model the insights.
We are unique because in our world – your data is all that’s required.  We provide everything you need, including the data scientists and visualization specialists to deliver meaningful business insights in just 4-6 weeks.  Why would you want to wait months for intelligent insights when they are available to you right now?  It would take you longer to process the paperwork from one of the big data analytics vendors, than it will for InCloud to deliver meaningful results to your dashboard.
INCLOUD has developed a bunch of kick ass apps that make processing your data fast and easy.  And the best part about developing apps for different use cases is that they can be reused, which makes keeping your data fresh and up-to-date simple and inexpensive.
So why did we decide to build an advanced analytics company in the cloud – deliver ROI focused results really-really-really-fast – oh, and do it at a remarkably low price?  Because as soon as we figured out that the incumbent hardware and professional services companies were pushing product for millions of dollars and in the end, customers had nothing to show for except a huge invoice and an annual support contract…we decided someone needed to kick their ass.
And so here we are, kicking their ass everyday.  And our customers love it and they love us.
Let me tell you a little bit about what we do that’s unique for our customers.  Where most product companies start by talking about what they can sell you, INCLOUD begins with the problem you’re trying to solve.  Digital assets are ready to be harvested to provide new opportunities and insight into the future. 
The problem I stated above – is that the financial investment is only compounded by complexity of trying to find the expertise in-house to make sense of the data – and only after you finally have a functioning analytics platform up and running. 
INCLOUD works with you to first define your problem statement…
”The what if scenario that starts with a question you just haven’t been able to answer – the what if scenario that if you could answer it would give you a competitive advantage.”
We define that “what if scenario” as a use case.  The use case is represented by one of our apps that can ingest your data and then model the results you need to impact your operational decisions.  We then help you integrate the results back into your business so that you can measure ROI on each insight.
Because we are constantly creating reusable apps for each unique customer use case – the catalog continues to grow – creating more opportunities for other use cases performed by your established analytics platform we’ve built exclusively for you.
The visualization and delivery of your results are presented in a beautiful and graphical dashboard display that allows you to actually see the data come to life on your screen.  Visualization also allows you to simulate “what if” scenarios like – what if I spend more money on this thing, or what if I only look at these doctors for this referral, or what if I shorten this campaign from 6 months to 2 weeks.
Powerful insights begin to drive your decision-making because those insights optimize your ROI.  Now you have the capability to not only know what you should do today, but also predict what will happen 6 months from now.  That’s taking your digital assets from simple reporting on what happened last quarter to knowing what decisions will impact your profitability, risk exposure, customer sentiment, security spend…whatever is important to you.
So now that you have captured the data you need to make decisions, on a platform you only pay for when you use it – what more could you do with more intelligence and fresh data?
Well we thought of that too.  INCLOUD has a SaaS model, which means you consume the platform for a low monthly subscription fee.  You can push your fresh data once a quarter, every month, every day or even in real time.  We reuse the apps we created on the unique and secure platform that isn’t shared with any other company – and deliver insights back to your desktop whenever you want to figure out how you did on last month’s pivot or figure out if you should spend more or less money on maintenance this winter.
So there you have it.  Answers to your most important questions, faster, and less expensive than anyone in the market. 

We are InCloud…are you in?

How Well Do You See Through A Dirty Windshield?

A Clear View Is Best


A customer was sharing a challenge she faces each day at her company.  She is one of three managers at a packaging manufacturer that plans and schedules production runs.  Here is the problem as she sees it:

“My schedule is based off order data that comes from our accounting system.  We transfer new orders to our planning software each day by manually keying in the data that helps us track the important information we need to schedule people, machines, and materials.  As soon as I commit the schedule to the system it is incorrect.  I know it’s incorrect and so does everyone else.  If I could somehow get the schedule visualized in a way that could make sense to the rest of my team I think we could improve our process.”

Wrong Wrong Wrong
If you visualize incorrect data then really all you’ve done is just beautified the lie.

My question to her was why is the data lying to you?  Here is what we discovered.

Treating everything as a task is the simplest way to explain the problem.  Yes you have orders.  Yes you have quantities.  Yes you schedule people and machines and materials.  But when everything is scheduled what really matters most and how do you track the changes that occur?

Proving Theories
We experimented with our theory for one week.  Simple tasks assigned to a specific person.  Each person assigned to a machine.  Tasks, person, and machine connected to an order.  Order was connected to the delivery date.

Here is what we found to be true – (1.) The closer you can get to the point of production (meaning the individual person responsible for the task) the more accurate the data.  (2.) The closest you can get to near real time feedback the more accurate the data.

So what happened during our experiment that impacted my friend?

3 tasks were assigned to one of her shop floor workers – Start order #320014, Make 150,000 things, Finish order #320014, and she assigned the worker to a specific machine #13.  

The worker started the first task, then the second task.  Two times during the day machine #13 broke down because of a jammed head.  Once the worker was able to fix it in 20 minutes, but the other time maintenance needed to be called to fix the head.  The second time the machine was down for 2 hours.

The minute the machine went down the worker changed the status of his task from active to stopped.  Entered in a reason for the stoppage and an alert was sent to my friend letting her know that the schedule was creeping.  20 minutes the first time.  2 hours the second time.

What did that provide her?
She knew that there was no way that order #320014 was going to be ready the next day for shipping so she was able to call two other plants to see if they had any extra inventory to complete the order on time.  One plant had enough to fill the balance of the order and put the product on a truck that was leaving at 4:00pm that day.

Before our experiment my friend wouldn’t have found out the order wasn’t going to be late until the next day’s production meeting.  Simply put, progressing the tasks and communicating change to the schedule provided her the clear view of the truth she needed to make a smart business decision and make the delivery date promised to the customer.

If you want to learn how we can help you see the truth in your data clearly give us a call or send us a note at hello@myincloud.com

Is Your Schedule Always Wrong?

The Black Hole of Scheduling


Our research team has spoken with over 100 companies this year to understand what are the biggest challenges US Manufacturers face.  What we found I’m sure will not shock or astound you.

Number one and two by a mile is that “our schedule is wrong the second we press commit” and “communicating change to those impacted”.

Following phone interviews, we visited 40 sites that were trying to solve these problems with either off-the-shelf or home grown solutions.  Here’s what we saw with our own eyes.

The software solutions ya’ll are using require so much detail that any change that occurs requires you to make so many updates to the data that your only option is to throw your hands up and accept the chaos.  The systems you buy and the systems you create are too complex for your users to adopt and interact with on a regular basis.

What We Discovered During Our Research

You told us that visualizing your schedule is very difficult.  Many of you try to solve this problem by transferring the necessary detail to a whiteboard.  Which is better than nothing but is difficult to make quantum changes that impact many people, departments, and processes.

You told us that when a change occurs to any aspect of the schedule, the ripple affect is felt by everyone.  That impact is difficult to communicate in near real time because of the way you are currently assigning tasks and job packages to your staff.

Those two paragraphs alone were enough to make us ask – 

“What if we could design and build an easy-to-use scheduling application that was alway accurate?”

So We Made It Just For You

We have developed an entirely new application that focuses on execution of tasks assigned to either people and/or machines.  We only care about the delivery date, what you’re making, and how many things your customer ordered.  We do the rest of the automation behind the scenes.

Simulation and optimization functionality allows you to stop being a babysitting-data entry-clerk and start using your brain to innovate and find ways to make your company better.



Because we only require a few points of data, your job just got easier.  Because we extend task assignments to actual people, those people are responsible for progressing tasks and alerting you and your team when something changes that may impact the schedule.  Like a machine goes down, or you run out of packaging materials in shipping, or that guy doesn’t show up for work today.

Because we automate the scheduling creep in both directions, the moment a task is stopped because a worker can’t complete it, a timer starts on the machine he is assigned to, and the duration of the downtime moves the schedule until the task is resumed.  The Plant View Display shows the schedule and all the dependancies creep a matched duration.

And if any collisions occurred during that stoppage, you will see visual indicators showing those problem areas in red.  Now you know exactly what happened, why, how long, and what was impacted by the creep.

Don’t Even Ask…of course we made it Drag and Drop capable

If you have to go into a box and retype something, a scheduling application is dead-on-arrival.  So we made the things that need to move around easy for you to drag them onto the schedule, or onto a different machine, or onto a different person.  We handle the time and date sequencing on the back side.  Oh and all of dependancies are still there so no need to worry about breaking the original connection.



So You’re Probably Wondering 

“How Is My Workforce Going To Use The Software?”  I’m so glad you asked.

If you are reading this article, I assume you can get to the web.  InCloud InTime Scheduling Application can be accessed from your pc, mobile device, a terminal on the shop floor, or your workers can access the application with our Smart SafetyGlass Wearables.

We just want you to get the task assignments and progression of those tasks as close to the worker and as close to near real time as possible.  That could be a layer above a team that manages the group tasks on an iPad.   A worker that progresses his tasks at a nearby terminal on the shop floor.  A worker could get a printed task assignment for the day, but progress his tasks on break, lunch, and at the end of the day on his smartphone.  Or a worker could be wearing our Smart SafetyGlass Wearables that are voice activated, barcode scannable, and yes our app runs directly on them so they are always updated with the latest data.



So what do you think?  

Did we hit the nail on the head?

If you want to learn more send us a note at hello@myincloud.com and we can give you a quick 5 minute demo that will show you everything described above.

Talk to you soon.


Creating A Generative Organizational Culture

What If You Could Change Your Company’s Culture?



In a generative environment, it is understood that continuous improvement leads to ever-higher levels of throughput and stability. Planning, scheduling and operations work together throughout the delivery process, and collaborate on ways to reduce the cost and risk of making changes. 

Everybody is encouraged to run experiments to learn how to improve both processes and the products and services they build. Failure is treated as a learning opportunity. The flow of information and feedback is fast, because it’s built into the system, from continuous integration to automated tests to monitoring of production environments. 

The result is a business that can pull ahead of the competition because it can quickly detect and respond to new market opportunities, unburdened by an external decision-making process. Just as important, generative workplaces have more engaged employees who can express their intelligence and creativity, lending the company an important competitive advantage.

What if you had the power to make changes like described above to your company?  InCloud Control tests every new feature our customers request by thinking about how it’s going to impact you.  How is this new feature going to impact your company?  We hope you love our new product.  It’s created a lot of fan mail for our researchers and product development team so far.  It’s real.  Use the right tools to change your world.