Analytical approach to transforming product quality

Analytical approach to transforming product quality

Philips DAP Hastings decided to engage with the University of Brighton as part of the Teaching Company Scheme. Originally the project aim was to reduce the rate of product returns for fan heaters and develop design rules for later models.

I joined the scheme and took on the project almost straight from University. However, fan heaters are seasonal products. So I recommended that I work on kettles instead. The factory made over a million kettles a year and its returns rates were among the highest in the group. As the project would use significant amounts of data, my university mentor engaged a statistical researcher and we adopted the, then, infant tool of six sigma to provide a framework.

Define

My goal was to reduce the number of designed and manufactured defects in kettles as measured by product returns. Each product return was estimated to cost the company the same as the cost of manufacture of that product. [Now I would add many other elements into this cost such as the cost of running the returns department, reputational costs and disposal costs.]

Measure

At the time of my project, Philips assessed 20% of all product returns in each major market. The UK returns centre was in Croydon. However, the Quality Manager in Hastings (my industrial mentor and project sponsor) had set up a returns department that inspected every other returned kettle (and fan heater). These two departments were my primary sources of data. Analysis of their investigations showed some technical issues but over 50% of all returns were classed as ‘no fault found’. My first action was to ask that the teams record the stated reason for return in each of these cases. To get to the heart of these non-technical returns I also set up other data sources:

  • Secondary inspection of life test kettles
  • Home trials
  • Retailer visits – both to headquarters and individual stores
  • Consumer conversations – sometimes using warranty data and sometimes by meeting consumers in-store and talking. I even visited two consumers at home to see how they used their kettles

Analyse

I employed statistical techniques to analyse the quantifiable data and determined several reasons for return among the technical faults. Working with the product owner (Design Engineer) and Production Engineering I built a business case for several of the returns. I also worked closely with purchasing to address issues with the switch and elements. I developed a breakdown of reasons for return among the ‘no fault found’ products.

Pareto of technical and non-technical faults
Pareto of technical and non-technical faults

Improve

The design team addressed the technical modifications both in design and production.

However, most of my analysis was around subjective subjects and in those situations, I learned to employ influencing skills to build a consensus for change. My suggestion to change colour was adopted for the current product. I also recommended re-introducing a water level indicator (introduced on the next model) and shortening the rolling boil – Marketing declined to change this attribute.

Control

To assess the impact of the improvement and to collect better data moving forward I agreed several changes in data collection and reporting with the returns teams. These data showed changes with the introduction of modifications and continued to reflect improved customer satisfaction. Based on the same data, I estimated the cost savings for future models.

Achievements

I was awarded an MSc by Credit Accumulation and Transfer for my work

In my first week I observed a repeated failure in life test and persuaded the Design Engineer to make a minor modification. The design change probably prevented ~40% returns and irrevocable damage to our relationship with key retailers

Using consumer and retailer feedback I recognised that many ‘no fault found’ returns were driven by the shade of white used in the product – a recolour across the entire brought forward

Pursuing one technical issue, I worked with our element manufacturer to pinpoint a manufacturing process failure – opening the door for purchasing to negotiate a price reduction

Changes applied to the existing product reduced returns by over 30%

Changes applied to next product reduced returns by 60-80%, equating to £600,000 per year

I was asked to coach design and product teams – providing the ‘Voice of the Customer’

I introduced the ethos that “we are not selling a kettle, we are selling a cup of tea”

I applied learning to fan heaters, assessed returns and drove improvements in product marking and instructions

Offered a permanent role, first as Supply Chain Quality Engineer and then as Design Quality Manager

(not really related but fun) as a permanent member of staff I assessed products returned as part of legal claims for compensation

Key skills

Business analysis – in addition to using statistical techniques, I assessed qualitative data and provided business insight

Project management – from defining requirements and setting up governance to planning and delivering a range of cross-functional requirements

Stakeholder engagement – working with major UK retailers at all levels, consumers in person and through home trails and across the Philips organisation to learn and understand perspectives and to influence change in the current and future products

Do you have low customer satisfaction scores for a product or service? Are you struggling to see the wood for the trees? Contact us today to discuss your requirements and learn how Delta Swan can help you.