This guest blog was kindly provided by Smithers Quality Assessments

The clock keeps ticking, and we keep getting closer to that now infamous due date (September 15, 2018, to be exact) for the transition of ISO 9001:2008 certifications to the updated standard of ISO 9001:2015. If you’re already certified to the former, you’re probably going through the process of determining audit dates for transition, or if you’re new to the quality management system, you may be looking at which certification body to select to help you get up to date with the latest standard. In either case, or if you’re unsure of what the best course of action will be for your organization moving forward, highlighting what’s really changed in the latest revision may help to settle uncertainty, solidify expectations, and create a clear direction.

At first glance, the new standard appears different, and may even feel a little different after reviewing it for the first time. However, ISO 9001:2015 is actually very similar to its predecessor ISO 9001:2008.  In fact, if you exclude the more subtle or simple changes, there are four important changes to be found in the latest revision:

1. Processes Emphasis – The goal of this addition is to prompt organizations to really think about their processes, to define them clearly and who’s responsible for what. For example, start by asking yourself these questions: What are your processes specifically? Who will run them? How will you monitor and measure them?

2. Risk Management Concept – Every business owner, operator, or manager must consider the risk involved with many of the decision they make, or the actions they take on a regular basis. For instance: Do you bring on a new supplier? Yes or no? Should you pick up a new customer or job? Do you have the resources or organization bandwidth to provide the necessary services? Can you hire a new employee? These are all examples of risk related issues. As it pertains to the revised ISO 9001:2015 standard, it is now a requirement of the updated quality management system to start thinking about risk and as mentioned in process emphasis, start mapping it out by clearly defining it.

3. No Required Procedures – Unlike in ISO 9001:2008, the revised standard does not contain a structured set of required procedures that you must incorporate into your processes. However, that doesn’t mean that you can have none in place. Instead, the goal of this flexibility is to allow companies the authority to decide which procedures are most applicable to them, which ones to keep or get rid of, and what additional ones should be added to produce the best results.

4. Top Management Must Own its QMS – Another focus for ISO 9001:2015 is the encouragement of top management within organizations to own their quality management system. So, whether it’s the President, VP, or General Manager, the emphasis is on these roles taking a more active role in the development, implementation, measurement, and responsibility of their company’s processes, and not simply delegating it all to quality manager.

As it was mentioned earlier, the above is not an all-encompassing list of the changes or variations between ISO 9001:2015 and ISO 9001:2008, but the rest of the changes are subtler and should not overly influence your transition or audit. To learn more about the benefits of ISO 9001:2015, download Smithers Quality Assessment’s gap analysis sheet.

Manufacturers care most about finding new ways to grow, excel at product quality while still being able to take on short lead-time production runs from customers. New business models often bring the paradox of new product lines that strain existing ERP, CRM and PLM systems by the need always to improve time-to-customer performance. New products are proliferating in manufacturing today, and delivery windows are tightening. Manufacturers are turning to machine learning to improve the end-to-end performance of their operations and find a performance-based solution to this paradox.

The ten ways machine learning is revolutionizing manufacturing in 2018 include the following:

• Improving semiconductor manufacturing yields up to 30%, reducing scrap rates, and optimizing fab operations are is achievable with machine learning. Attaining up to a 30% reduction in yield detraction in semiconductor manufacturing, reducing scrap rates based on machine learning-based root-cause analysis and reducing testing costs using AI optimization are the top three areas where machine learning will improve semiconductor manufacturing. McKinsey also found that AI-enhanced predictive maintenance of industrial equipment will generate a 10% reduction in annual maintenance costs, up to a 20% downtime reduction and 25% reduction in inspection costs. Source: Smartening up with Artificial Intelligence (AI) – What’s in it for Germany and its Industrial Sector?

• Asset Management, Supply Chain Management, and Inventory Management are the hottest areas of artificial intelligence, machine learning and IoT adoption in manufacturing today. The World Economic Forum (WEF) and A.T. Kearney’s recent study of the future of production find that manufacturers are evaluating how combining emerging technologies including IoT, AI, and machine learning can improve asset tracking accuracy, supply chain visibility, and inventory optimization. Source: Technology and Innovation for the Future of Production: Accelerating Value Creation 

• Manufacturer’s adoption of machine learning and analytics to improve predictive maintenance is predicted to increase 38% in the next five years according to PwC. Analytics and MI-driven process and quality optimization are predicted to grow 35% and process visualization and automation, 34%. PwC sees the integration of analytics, APIs and big data contributing to a 31% growth rate for connected factories in the next five years. Source: Digital Factories 2020: Shaping the future of manufacturing

• McKinsey predicts machine learning will reduce supply chain forecasting errors by 50% and reduce lost sales by 65% with better product availability. Supply chains are the lifeblood of any manufacturing business. Machine learning is predicted to reduce costs related to transport and warehousing and supply chain administration by 5 to 10% and 25 to 40%, respectively. Due to machine learning, overall inventory reductions of 20 to 50% are possible. Source: Smartening up with Artificial Intelligence (AI) – What’s in it for Germany and its Industrial Sector?

• Improving demand forecast accuracy to reduce energy costs and negative price variances using machine learning uncovers price elasticity and price sensitivity as well. Honeywell is integrating AI and machine-learning algorithms into procurement, strategic sourcing and cost management. Source: Honeywell Connected Plant: Analytics and Beyond

• Automating inventory optimization using machine learning has improved service levels by 16% while simultaneously increasing inventory turns by 25%.AI and machine learning constraint-based algorithms and modeling are making it possible scale inventory optimization across all distribution locations, taking into account external, independent variables that affect demand and time-to-customer delivery performance. Source: Transform the manufacturing supply chain with Multi-Echelon inventory optimization

• Combining real-time monitoring and machine learning is optimizing shop floor operations, providing insights into machine-level loads and production schedule performance. Knowing in real-time how each machine’s load level impacts overall production schedule performance leads to better decisions managing each production run. Optimizing the best possible set of machines for a given production run is now possible using machine learning algorithms. Source: Factories of the Future: How Symbiotic Production Systems, Real-Time Production Monitoring, Edge Analytics and AI Are Making Factories Intelligent and Agile

• Improving the accuracy of detecting costs of performance degradation across multiple manufacturing scenarios reduces costs by 50% or more. Using real-time monitoring technologies to create accurate data sets that capture pricing, inventory velocity, and related variables gives machine learning apps what they need to determine cost behaviors across multiple manufacturing scenarios. Source: Leveraging AI for Industrial IoT

• A manufacturer was able to achieve a 35% reduction in test and calibration time via accurate prediction of calibration and test results using machine learning. The project’s goal was to reduce test and calibration time in the production of mobile hydraulic pumps. The methodology focused on using a series of machine learning models that would predict test outcomes and learn over time. The process workflow below was able to isolate the bottlenecks, streamlining test and calibration time in the process. Source: The Value Of Data Science Standards In Manufacturing Analytics

• Improving yield rates, preventative maintenance accuracy and workloads by the asset is now possible by combining machine learning and Overall Equipment Effectiveness (OEE). OEE is a pervasively used metric in manufacturing as it combines availability, performance, and quality, defining production effectiveness. Combined with other metrics, it’s possible to find the factors that impact manufacturing performance the most and least. Integrating OEE and other datasets in machine learning models that learn quickly through iteration are one of the fastest growing areas of manufacturing intelligence and analytics today. Source: TIBCO Manufacturing Solutions

March 2^nd, 2018 was a chaotic winter workday that all Northeast Ohioans know too well.   Our city’s school district was on a 2-hour delay with heavy snow on the roads, the dog wanted to go out and play, and the driveway needed to be cleared. I quickly accepted that getting to the office that morning would also be delayed.

Once I finished my “snow day” tasks and my teen drivers were off to school, I felt like everything was falling back into place. I ran my 10 am video call from my kitchen and afterward, took a much-appreciated shower The plan was to dress quickly and drive to the office. But as we all know, in business and life, sometimes things don’t go according to plan and you have to be prepared to adapt.  I came out to find three text messages and an urgent call for help from our client, Grand River Rubber and Plastics.

The Client Crisis:

Apparently, our client further north of us got slammed with heavy snow, sleet, and ice so bad that all power and phones were knocked out for 24 hours with no relief in sight for another day. Customers’ orders were not being received or acknowledged and they had lost several shifts of production.

Despite the unfortunate act of fate and the chaos that came with it, Grand River Rubber & Plastics wanted to notify customers and colleagues of the situation as quickly as possible. Flashback one year prior to today’s snowmageddon, the company had hired us to impact lead generation via inbound marketing as well as utilizing public relations and social media. Customers were increasingly using new forms to communicate and marketing activities were generating new leads – – all being recorded and documented in their new customer relationship manager (CRM), and you guessed it, in the cloud.

The Communication Solution: The cloud came to their rescue that day. With my laptop still warmed up from my video call, I quickly accessed their HubSpot CRM online, drafted an email with pertinent information and sent to their 750+ registered contacts. Simply the urgent message and what was being done. Within the same HubSpot portal, the message was immediately posted to their company LinkedIn, Facebook and Twitter accounts.

The Aftermath:

Fortunately, power was restored over the weekend. I updated the Grand River Rubber & Plastics social channels. The company was now able to once again access their server, the internet and update their customers directly.

Grand River Rubber & Plastics’ HubSpot platform, a CRM and inbound marketing platform in one portal, allowed our team to share the urgent message with customers quickly and efficiently across email, social media and web. Snow, sleet, and ice may have started the fight but the cloud (and inbound marketing) came to the rescue.

Manufacturing salespeople, I’m going to tell you something that may shock you. It’s time to take a more hands-off approach to prospect nurturing. I know, I know, that goes against everything you’ve been taught. However, just like you cannot expect to get married on a first date, you cannot expect to meet a prospect and close a deal immediately. The biggest mistake I see salespeople making is not customizing the sales approach based on where the prospect is in the buyer’s journey.

Not everyone is ready to buy, especially when you are approaching your quota deadline and fielding update requests from your sales manager. So, what are manufacturing salespeople to do to stay top of mind to their prospect and develop a relationship that ends in a sale? Also, what about all the TIME it takes to follow up with key prospects? Use the 3 key steps below to streamline your sales cycle and customize your approach to each prospect’s stage in the buyer’s journey more efficiently.

3 Key Steps to Streamline Prospect Nurturing Quicker and More Efficiently

• Targeted a specific type of buyer (prospect persona)

Need help? Why Developing Buyer Personas is Invaluable for Manufacturers

• Developed relevant and interesting content

Need help? Why Manufacturers Need a Content Map for Inbound Marketing Success

• Setup an automated way to personally communicate while you do another task

I know, the 3^rd point is daunting to most manufacturing salespeople.  Have you not found a way to clone yourself? Would be nice, right? Read on to hear how you can essentially “clone” yourself and multi-manage your prospect nurturing.

“I Like Pizza” Watch the movie Multiplicity. Not all clones are created equal!

Well, it is possible to save time and clone yourself, if executed correctly! Automated email sequences are the closest thing to cloning in the sales world and it works amazingly for us and our clients.

What Are Automated Email Sequences?

Email sequences are a pre-written, customizable series of emails and task reminders. Turn repetitive tasks, such as follow up reminders into simple, easy-to-launch messages. We utilize sequences to following up with prospects when they do the following: download an eBook, we see them at a trade show and think they can benefit from our media interview services, we identify a prospect that should parlay company announcements into published industry news stories, or even when we are trying to reconnect with a lead we have not spoken to in months or even years.

At any time, our agency may have multiple, buyer’s journey staged sequences with 4 or more emails, timed to send over a series of days. We can set reminders to call or even remind us to send a LinkedIn invite to prospects once emails have been automatically sent. Sometimes we get a response from a prospect on the very first email, which prompts an immediate conversation. Other times, the entire series plays out and we get nothing (which is good!)

Why You Should ‘Go For the No’

What’s good about hearing nothing back from a prospect you may wonder? Ever heard of ‘going for the no’? Not everyone who you meet in a target industry or who views your website is a prospect. The technology we use allows us to see if a prospect has opened an email and if they have clicked a link we provided. This inside knowledge of the prospect’s behavior, such as a download or reading of an eBook makes the follow-up call so much easier and more focused on their behavior.

Now sit back, use data to help you identify the best-performing sequences and bam, a successful use of your time and the perfect appearance of professionalism from your new cloned self.

Related Articles You May Enjoy:

• The 5 Biggest Inbound Marketing Mistakes Manufacturers Make
• Why Developing Buyer Personas is Invaluable for Manufacturers
• Inbound Marketing for Manufacturers

Manufacturing sales reps can compare the sales of the manufacturing sales process to a retail experience. From fast food to retail clothing, the phrase “How may I help you” is uttered repeatedly, almost unconsciously by armies of clerks, waiters and yes, sales representatives. In retail, the assumption is you are searching for something, otherwise, why would you be in the store, a brick and mortar store no less (read on).

Free Inbound Marketing for Manufacturers Assessment

In manufacturing sales, especially with high-ticket equipment, the sales cycle might be 12 or even 18 months. A consultative approach almost always requires in-depth questioning, audits, assessments and maybe even sample projects. Are you there to help? Of course you are.  If your prospect feels more like you are selling then consulting, a natural distrust creeps into your relationship. No one wants to, let alone admit to, being sold.

In our eBook, The Industrial Manufacturer’s Guide to Inbound Marketing we explain how building trust, converting visitors to leads and retaining customers is all about your prospect’s self-discovery of just how you can help.  And, here lies the success for manufacturing sales companies, focus on how and IF you can help. We find prospects more willing to discuss goals, challenges, and plans if they understand that your questions are just trying to determine if you and your company can help. How you can help, why, with what tools and tactics are best received if the prospect discovers this fact for themselves. See the inbound sales funnel here.

There is plenty of time, later in the process, to show your fancy presentation. I often repeat the phrase:
‘I am just trying to determine if I can help.’ Your questioning, unlike an inquisition, should be bolstered with tips and tactics that not only provide value to your prospect but position you as a caring expert in your field.

Can you help? Perhaps. You still need to gather information from your prospect to not only move them through the buying cycle but to discover for yourself if your services are a match. Also, do you like this prospect and can you do something spectacular together? This part of the process is most similar to dating. You’re not proposing marriage, talking about future kids and picking out china patterns on the first date. Dating is questioning. Keep asking and keep stating, you’re just trying to see if you can help. And, through mutual self-discovery you and the prospect both determine there is a way you can help, now your sale is closed.