Ghyslain Cadieux
Partner | B.B.A., CPA, CMA | Business Transformation

Use Industry 4.0 technology to boost operational and financial data cross-referencing to determine production costs more quickly and be more competitive.

Production cost and measuring processes

Production costing could be described as cross-referencing operational and financial information that are often in separate systems together into a common structure.

The purpose of operational data is to measure a business’s various processes (speed, quality, satisfaction, etc.) while financial data indicate the cost of resources needed to operate these processes. The two data help determine the cost of the manufacturing process, distribution, sales, client experience, etc.

Individually, operating and financial data do not provide the same informational value or foster quick and efficient decision-making.

The operational data challenge for production costs

The level of corporate informational maturity varies greatly, and data collection methods range from notes on paper to integrated management systems (ERP), and the ubiquitous Excel spreadsheet. Until recently, we were rarely able to access structured, quality data. Instead, data compilation, validation and transformation exercises were required to obtain accurate data that could be used in costing. Today, organizations are facing two major revolutions:

  1. Easy access to digitization
    There has been an abundant supply of products and services in this field in Quebec for several years now, making it possible to quickly obtain accurate, structured operational data;
  2. The enhancement of existing data
    Many companies have an unsuspected information asset in their hands. They accumulate data in ERPs, machine tools or other systems without exploiting them.

With artificial intelligence et advanced analytical techniques, it is now possible to enhance these data and gain an important competitive advantage.

With the data acquired by digitizing processes or using existing data, the company can determine the production cost more quickly and often more accurately. It is also possible to exploit the benefits of costing and to analyse profitability by product, customer, order, etc., based on available information and the company’s objectives.

A practical example

A summary analysis provided the following information: 47% of the costs incurred are operating costs, 53% are selling and administrative costs. An analysis of the 53% production costs revealed that they consist of the following services:

To support its distributors, for several years the company has been hiring more resources to prepare bids and technical drawings with no corresponding rise in sales.

Exploiting data to understanding how costs behave

By analysing six variables over time and adding qualitative data, it was possible to define measurements that characterized each of the distributors:

  • Measurement 1: Success rate (sales $/bid $);
  • Measurement 2: Bid cost per distributor;
  • Measurement 3: Technical drawing cost per distributor;
  • Measurement 4: Sales per distributor.

The above graph indicates that distributors 1 and 2 account for less than 10% of the bids and technical drawing departments’ efforts and 50% of sales. On the other hand, distributor 6 accounts for 50% of the bid department’s efforts and 25% of the technical drawings department’s effort.

Return on investment

On the basis of this analysis, the company drew up a clear portrait of each distributor’s contribution. Using this information and an analysis of the six underlying variables, the company:

  • Discussed potential improvements with distributors;
  • Targeted training efforts;
  • Identified the efficient distributors’ good practices and passed them on to the others;
  • Introduced fees for certain services;
  • Eventually, dropped the distributors that did not show any improvements, despite the measures taken.

Whether data come from an ERP, artificial intelligence or elsewhere, if they are not used, there is no return on investment.

Our consultants are available to help you initiate or continue your 4.0 transformation and support your projects, from the smallest to the most ambitious. Go for it!

Did you know?

PME en action program offers subsidies to support the implementation of projects to boost productivity, including industry 4.0 initiatives. You could qualify for a non-refundable contribution of up to 40% of eligible project expenses.

30 Apr 2018  |  Written by :

Ghyslain Cadieux is expert in Business Transformation consulting at Raymond Chabot Grant Thornton....

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Pierre Laberge
Manager | Tax

Digital technologies such as artificial intelligence can help boost your business’s productivity. Join the 4.0 revolution and find out what financial assistance is available.

Industry 4.0 is not science fiction

When presented with examples of the results of shifting to industry 4.0, many people believe that the transition can only be accomplished with major technological infrastructure investments, a perception that, unfortunately, may lead to delaying the digital transition of processes.

Not only is the technology to achieve this transformation available, it’s also easy to access and integrate. For example, adding artificial intelligence solutions to better exploit your application data is no longer in the realm of science fiction. However, few businesses have the necessary knowledge to undertake such a project on their own.

One step at a time

As innovation financing and technological development experts, we have extensive knowledge of the manufacturing sector and we know that the initiative can build on existing technology infrastructures. Enterprise resource planning systems, production management software and automation service providers’ software packages are sources of information that can be exploited. The company can then test the new technologies by undertaking one project in order to become familiar with the process.

By initiating the transformation with minimal infrastructure investments, it’s possible to get an idea of the positive impact of the 4.0 transformation on a company’s activities. Projects could involve, for example, the client experience, energy efficiency, improved production cost calculations, reducing losses, improving security or employee engagement or efficiency.

SR&ED tax incentives to go further

Having worked with many businesses on technology projects, we know that, in the past few years, many of them have used such an approach to initiate a process digitization. Building on this experience, they are now ready to go further. They believe industry 4.0 is an opportunity to use more advanced technologies and to benefit from smart installations. However, some aspects of their projects could raise a number of issues.

Some innovative or larger-scope projects may come up against difficulties and technological challenges, such as having to work with technologies that are not at the same level of maturity, maintaining legacy systems or integrating components that were developed for another field. It is specifically for such situations that programs like the SR&ED tax credit, for example, have been developed with the objective of sharing the financial risks and helping to overcome obstacles. This requires maximizing the financial support and strategically planning each step to achieve strategic, financial, operational and employee objectives. Our team specializing in SR&ED and technological innovation tax incentives is familiar with such situations and has the requisite expertise to support your efforts and address the issues.

Did you know?

There are scientific research and experimental development investment tax credits available. The scope of these programs may have been curtailed in recent budgets, but they are still one of the most generous sources of financial assistance in the country. In some cases, combined Canada/Quebec credits can be as much as 70% of expenses.

20 Apr 2018  |  Written by :

Pierre Laberge is a manager at Raymond Chabot Grant Thornton. He is your expert in taxation for the...

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Nancy Jalbert
Partner | CPA, CA | Business Transformation

With the digital shift, now more than ever, clients are in the driver’s seat. In order to evolve with their needs, a business must be able to innovate.

Clients can access an almost limitless product and service offering, with fierce competition leading to lower prices. The ever-changing business landscape and innumerable uncertainties underscore the need for businesses of all sizes to position themselves to ensure their longevity and development.

  • Do you find that your value proposal isn’t sufficiently distinctive for you to stand out from the competition?
  • Do you feel that your customers’ expectations have changed in recent years and they want to do business differently?
  • Does your business no longer bring in enough income to meet your growth needs?
  • Is technology transforming how your industry does things?

If the answer to any of these questions is “yes”, it’s time for your business to take a close look at its business model to stay competitive.

Adapt or die: How your business model can impact your growth

The fast pace of technological innovations forces businesses to position themselves to deal with the changes, which may have significant short- or medium-term impacts on their industry. It’s clear that the key to success today is no longer a guarantee of success tomorrow. Businesses increasingly need to question their business model.

An Economist Intelligence Unit (EIU) study indicates that 54% of entrepreneurs consider innovation through new business models rather than new products or services as the way to gain a competitive advantage in the future. Why? Because it’s more difficult for competitors to imitate an entire innovation system than just a product or process.

It’s obvious that business sectors are transforming their business models. Examples abound:

  • Airbnb in the hotel industry;
  • Spotify in the music industry;
  • Alibaba in distribution;
  • PayPal with financial transactions, etc.

Even more traditional industries, such as professional services, must review their business models, as we have seen with Raymond Chabot Grant Thornton. The firm recently deployed its e-accounting platform Operiō to meet the needs of its new-generation clientele.

Competition may not necessarily be found where it was expected in the past. The intermediaries have changed, bringing new opportunities to reach customers. You have to ask yourself: how can your business model help you maintain or even find new sources of income in a constantly changing marketplace?

Changing your business model

Let’s start by defining a business model. There are various definitions, but most agree that it describes how a business will create, deliver and capture added value for its customer base and generate income.

The first question to ask is how you can create value for your customers and then, how you can organize your business to deliver that value, whether it’s through your business processes, resources, value chain, business partners, etc. There are multiple possibilities for business model innovation: expanding your service offering with new upstream or downstream activities, adding a complementary product to your offering, creating value to ensure loyalty, etc.

A number of factors must be considered for a successful, innovative transformation of your business model.

Know your customer
Business model innovation is based, first and foremost, on your knowledge of your customers, their needs, their expectations and, especially, the value they are looking for in a product or service like yours.

Your model should not be based on what you think. You may have a biased view because of your industry perceptions or history. Take the time to consult your customers to get an accurate and up-to-date picture. Plan and conduct customer surveys or hold discussion groups.

Ensure strategic monitoring
New ideas are not the only source for new business models, you can often draw inspiration from models in other industries that could be applied to yours.

Take the time to analyze similar sectors to understand business model best practices and validate their relevance for your business. Consider benchmarking your market to identify the most appropriate business models for your business, or analyze your competition to evaluate positioning opportunities or business models that could set you apart.

Work in synergy
A new business model has repercussions throughout your business’s ecosystem. All functions (human resources, operations, marketing, finance, etc.) will be called upon and will have to evolve at various levels to ensure the new model’s value creation.

Business model innovation requires working with multidisciplinary teams, representing all of the business’s stakeholders. Consider organizing brainstorming workshops led by experts to build consensus. This will foster a common vision of the project and define individual roles in the initiative.

Manage change appropriately
As mentioned, implementing a new business model can lead to extensive changes due to the numerous operational projects to be implemented (IT, artificial intelligence, process optimization, etc.). It’s important to be committed and to manage the change to ensure employee, customer and business partner buy-in. The operational projects must be properly structured in order to implement them efficiently.

Are You Ready to Innovate? Our Experts Can Help!

A business model innovation initiative must be supported by knowledgeable, experienced experts who can help you undertake a strategic reflection of your business’s fundamental makeup to offer a distinctive value proposal that provides a unique and durable competitive edge … until the next transformation!

Our business strategy and organizational performance teams can help you structure your transformation project and provide support to properly manage the change underlying the new business model.

Contact us!

Did you know?

There are scientific research and experimental development investment tax credits available. The scope of these programs may have been curtailed in recent budgets, but they are still one of the most generous sources of financial assistance in the country. In some cases, combined Canada/Quebec credits can be as much as 70% of expenses.

19 Apr 2018  |  Written by :

Nancy Jalbert is a partner at Raymond Chabot Grant Thornton.

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Technological development makes it possible to collect a wide range of useful data. Thanks to artificial intelligence (AI), businesses can capitalize on a focussed and relevant analysis of this information.

The answer to tangible and complex business issues can be found in corporate data. Analytical solutions to problems are a means of optimizing both finances and productivity.

Improved productivity

The productivity of onsite resources can be increased by including algorithms in the decision-making processes. In the manufacturing sector, for example, algorithms make the advanced detection of breakdowns in the production chain possible or can be used for the automated sorting of compliant products.

These solutions rely on data provided by industrial sensors that are currently in place or by low-cost devices, such as cameras or specific sensors that can be installed after the fact. Other applications, such as predictive maintenance, make it possible to boost the efficiency of physical and financial resources used in a manufacturing environment.

Clients in the financial and professional services sectors use algorithms to automate low added-value processes. For example, character recognition can be used to automate data entry.

Algorithmic analyses of financial market results, news and annual reports make it possible for a portfolio management team to prioritize its research work. In the logistics and distribution sector, analysing changes in inventory levels and client demands helps organizations use their storage space more efficiently to reduce inventory shortages and customer dissatisfaction.

Income growth

The data produced can be used to develop solutions that assist departments making strategic and tactical decisions to generate new income. Improved knowledge about clients and their behaviour can be used, for example, to develop initiatives to get their attention and thus meet their needs.

Our AI expertise is leveraged by manufacturing entities to improve their knowledge of clients and detect business opportunities by analyzing past activities and the history of interactions with clients. Analytics are then used to pinpoint where irritants are generated in the client experience or to detect opportunities for cross-sales or supplementary services.

Additionally, thanks to transaction histories and external data cross-checking, clients can be targeted individually during their life cycle. Predictive models can then be used to increase the conversion rate for acquisitions and cross-sales, foster client engagement and reduce attrition rates.

Depending on the available data, these models will identify clients who require special attention. If you know which clients have a high risk of leaving the organizations in the coming weeks, what could be better than preparing a retention offer and acting before they make their final decision?

With this income protection initiative, supported by the analytical component, retention efforts can be invested in the most strategic areas. Similarly, predictive models for product and service cross-sales can be developed to target clients with a strong propensity to convert and thus increase revenues.

Improved client experience

AI can also be applied to improve the client experience. In recent years, the digitized client relationship has significantly changed client expectations in terms of service time, quality and accessibility. Clients want products and services more quickly, they want businesses to be attentive to their needs at all times and they want quality at a lower cost.

In the manufacturing sector, an optimized production line can then reduce production times by anticipating equipment or resource issues, reduce client wait times by anticipating demand and optimizing procurement and improve quality by automating parts of the quality assurance process and controlling input factors. Naturally, similar applications can be implemented in other industries.

AI allows a business to exploit the quantity of data it generates in order to optimize and meet specific business needs. Although it can be used in various situations, it’s important to use it, first and foremost, to support the entity’s mission and bottom line, that is, increase revenues, reduce costs and improve the client experience. Integrating it into a business strategy calls for vigilance.

Our artificial intelligence experts can help!

Did you know?

There are scientific research and experimental development investment tax credits available. The scope of these programs may have been curtailed in recent budgets, but they are still one of the most generous sources of financial assistance in the country. In some cases, combined Canada/Quebec credits can be as much as 70% of expenses.

PME Innovation and technologie - RCGT