Written by Cindy Etsell
Today, the manufacturing industry is experiencing significant change, with many companies battling slimmer margins and fierce competition in a saturated market. As competition increases, product differentiation becomes a real challenge. With emerging economies now able to produce goods en masse and more cheaply, for manufacturers to compete on this level and continue to produce goods without sacrificing quality, they must acknowledge the importance of knowing the customer.
Against this backdrop, manufacturers are now looking at new ways to remain competitive, maintain quality and optimise revenue streams by reinventing business models and streamlining operational processes. To do this effectively, many manufacturers are turning to analytics.
As a tool for getting the most out of customer data, analytics can significantly enhance operational excellence – an enviable weapon in today’s competitive environment. It can help manufacturers to gather valuable customer feedback and data that supports the entire value chain – from sourcing to production –right through to marketing to optimise trade and promotions with retailers, across a variety of departments. By using customers and supplier feedback to improve the production process, companies can concentrate on enhancing the quality of products. As an important factor in a customer’s purchasing decision, if manufacturers want consumers to make big investments and part with their cash, they cannot afford to compromise the standard of production they once upheld.
Driving analytics
Big investments are rarely made lightly and a lot of consideration goes into these decisions to ensure value for money. A car is a great example of this. Whether you prefer something fast, sleek and sporty, or a practical family run-around, buying a car is a big deal. Once the cash has changed hands, the colour of the leather interior chosen and the keys released, we all expect our new cars to be perfect.
However, in some instances, despite the many millions spent by manufacturers on R&D and testing cars, problems occur. In the worst of all cases, some products must be recalled, with recall figures often stretching to hundreds of thousands of units, sometimes even into the millions. This can have catastrophic repercussions for a brand’s reputation, with customers turning to other, more reliable brands and manufacturers facing large, unavoidable and unnecessary costs. A bit of smart-thinking by manufacturers could make recalls a thing of the past. In using analytics to predict and prevent future recalls before the cars have even left the assembly line, car manufacturers can minimise the disruption and associated costs, keeping customers happy.
Take American Honda, as an example. By listening closely to its customers and using data gathered on purchases from warranty claims, technical helplines, customer feedback and parts and vehicle sales, Honda has ensured the continued high quality and performance of its vehicles. By comparing customer and technician feedback against manufacturing and other systems data, Honda has been able to develop an early-warning system which searches for recurring patterns and trends that could indicate a problem, halting potential recalls before they even occur. As soon as an area of possible concern is identified, the team can immediately alert engineering, manufacturing or even the dealers’ repair shops. In doing so, Honda is supporting engineering improvements to build better vehicles, meaning less cost to the company and, in turn, less expense and inconvenience to its customers.
The sweet taste of success
It’s not just product recalls that analytics can help to repair. With product differentiation becoming increasingly important in the industry, manufacturers need to use feedback from customers to help improve products and gain a competitive edge.
The food industry is a great example of a sector where customer feedback is invaluable and can be used to improve operational processes and the quality of goods. We eat food every day, and whether we enjoy it or not, we’re always making comments to our friends and family on that burger we really enjoyed or that biscuit that nearly broke our teeth. The food industry is driven by customer perception and the only way food companies can meet the expectations of the public and produce high-quality, delicious food stuffs is to react to positive and negative feedback.
Kraft Foods discovered the value of business analytics when the manufacturer began using analytics solutions to help hone and perfect some of the world’s most recognised food products. To ensure that the taste of each product lives up to its name, Kraft tests its foods throughout the manufacturing process and assigns numerical measurements that quantify the flavour, colour, aroma and other attributes of each product.
Using data and feedback from taste tests, product developers and sensory technologists can evaluate recipe reformulations, product improvements and consumer preferences. Production processes can also be reviewed in order to reduce variation in baking and mixing, allowing for greater planning efficiencies throughout the manufacturing process. Ultimately, using data from customers on the crunchiness, creaminess and chewiness of products, Kraft can ensure that customers continue to choose and enjoy its high quality products that taste great with every bite.
The ingredients of the business analytics mix
Although the benefits of analytics for the manufacturing industry are vast, for it to be successful there are a number of essential ingredients. First and foremost, companies require the buy–in and commitment from senior managers to ensure that they are willing to use the data to make better, more informed decisions about how to make improvements to operations. Secondly, for analytics to give true insight, it must be deployed enterprise-wide and cross-functional teams need to have the skills to ensure that the data inputted into the system is accurate and companies can gain a comprehensive, single customer view. Lastly, there needs to be an ongoing commitment to make improvements and maintain analytical models to ensure they are always delivering new insight. Once these three points have been addressed, manufacturers are then free to enjoy the benefits and competitive edge that comes with business analytics.
