Bay Blueberries Case Study

We are a boutique blueberry business, dealing locally, but also in domestic and export. We are a family business that has grown ‘organically’—with our people and our values. In spite of our growth, we are still a family business. We are located in a stunning part of the world, with very mild weather… it’s quite Mediterranean. People just love working and living here.

The fact that we are a family business that has grown in a carefully managed and deliberate way. That we, as a whole, have grown with our people and our skills. Our climate is wonderful, and we’re passionate about what we do because we love growing berries in the Bay.

We are members of the Blueberries New Zealand Organisation. The organisation holds grower discussions and field days, plus bigger events where suppliers can have demonstrations and information. It was at an industry field day that I saw Dataphyll.

Dataphyll was being used by a lot of growers. It seemed to fill a need I saw developing. We were small, but the solutions they were proposing and offering filled a couple of our needs. We wanted to show traceability from the plant to the customer at the end. To do that efficiently it took a lot of work to monitor every stage of the fruit’s path.

Dataphyll makes that traceability simple. We know who picked that fruit, on what day, what variety, what row, where it was packed, where it has gone, and to which customer. Previously we did all of that manually which took a lot of time.

I stopped to look at them because they built the software from an understanding of fruit growing and our needs. They were insiders in the growing industry. They knew the challenges and are open to feedback. We were early adopters and appreciated the fact that they understand our needs as opposed to a lot of more generic systems, where no growers are actually involved in development.

We need to monitor productivity as people are paid hourly. If we are not picking enough to cover the cost of hourly work, we are losing money because we have to top up wages to meet minimum wage.

Many pickers want to work on pick rates and contract rates because they can make great money. We have a lot of different types of pickers picking crops, and Dataphyll allows us to see how that is going on across the team. You can check why they are doing well. Can gauge whether picking volume is down due to an issue with the crop or if it’s an issue of skill. Slow pickers can then be singled out for work in the packhouse instead, so everyone is happy.

One picker absolutely shines on piece work rates (hourly rate). She picks in a beautiful way, and there’s actually an elegance about her technique. Since we’ve discovered her, we will be filming her technique to use as training material. Without Dataphyll, we’d never have figured out that she was doing something special.

As I said previously, we want to show traceability from beginning to end. Tracking staff productivity has now become important, and the traceability that Dataphyll offered was attractive.
Unfortunately, labour costs and compliance around labour costs took a lot of time and energy to manage. This system allows us to do it all in an efficient way. It’s great for our employees to be able to see their productivity against their payroll, and for us to identify somebody who may need more support or training.

Efficiency is critical in a business that hinges more and more upon margins as it grows. For my key team, Dataphyll is doing something to lighten their workload. It also makes pickers’ jobs easier. It’s an easy tool to use and cost-effective.

We adopted it carefully, because we are light on staff, and it allows pickers to take more responsibility for production. They can see their day’s work. They can easily see their pay slip and outcome each day. It almost gamefies work for them and makes them a part of the team.

It’s really boosted our ability to manage the packhouse. This allows us to shift the product quicker, giving us a lot more time to focus efforts elsewhere, or just speed up.