The modern e-commerce and retail scene is an interconnected world of myriad service providers and vendors adding value across a complex supply chain ecosystem. The collaborative nature of many operations mean that any change in performance of one player within the value chain could also affect others in the chain. Photo studios are a critical part of e-commerce and retail operations, and it is common for large studios to work closely with external partners offering photo editing services. Given the significant role post-production plays, and the growing volume of visual content creation, any change in photo editing productivity can have broad internal and external impacts, affecting quality, costs, turnaround time, shipment and revenue.
Traditional challenges to measuring photo studio productivity
The unique nature of photo studios, mixing “right brain” creative insight and “left brain” operational rigor, makes it difficult to implement a robust productivity model common in other commercial companies. Both organizational and personnel structure will affect how productivity is measured and reported at a photo studio, which is run by creative, business and operations executives. Due to the nature of the job, managers overseeing core studio operations, i.e. taking and processing photos, can be more invested in the creative and image-specific aspects of photography like aesthetics, art direction, photography techniques, lighting and quality of samples. C-level executives, on the other hand, who oversee business development and operations at the studio, need access to data on multiple key performance indicators (KPIs) in the entire photography process chain to make business and finance decisions in real-time. This approach is much more efficient than traditional predictive approaches which rely on historical data that may not be relevant to the radical changes within the content creation process.
In this scenario, a communication gap can be created where people driving the core photography operations struggle to speak ‘the same language’ with colleagues making data-driven management decisions at the top. This lost opportunity to measure and use data to boost overall productivity can have wide ranging implications: from quality, processing and efficiency at the photography level to studio profit and loss, staff salaries and increments, and turnaround time and pricing in the image processing supply chain.
Accurate measurement is tailoring for success
Measuring productivity and content performance requires the right data. The generation and interpretation of this critical element of productivity can become difficult to carry out or be easily overlooked in a typical photo studio environment. Measuring relevant data provides great insights to make studio operations more efficient, reveal cost reduction opportunities where there were none before, and boost revenues including employee perks and salaries. A strong and well implemented productivity model factors in all the studio’s critical ‘stakeholders’. It collects, reports and interprets different data sets for each stakeholder to help senior management make more efficient decisions backed up by data. A photo studio’s stakeholders can include, among others: Customers; photographers; photo stylists; image processors; outsource partners (e.g. image retouching services); studio staff (management, marketing, operations, etc.); vendors; technology equipment; and shipping partners.
Data that counts
When all data from all stakeholders are put on a central ‘dashboard’ and analyzed, a trained growth manager or data analyst can easily identify trends and areas of improvement in each segment. More importantly, all the data can collectively give a broad picture of the photo studio’s overall performance, identifying the strong and weak points of the business and its relationship to the larger e-commerce chain. Here’s a simple example of using data to measure productivity: A growing photo studio had the theoretical capacity to produce 1000 finished images per day, but the team could only process 800 images. An investigation by collecting data on employee feedback, equipment allocation, and turnaround times revealed a simple reason for the difference in expected and actual output. It turned out that many of the digital retouching staff had recently been given new, larger mice at their workstations which were slightly harder to grasp and control, thus increasing retouching time for each image. Stay tuned for our next blog which talks about stakeholder data and decision making.
Photo studio productivity: Stakeholder data and decision making
To this point we have conferred about the significant role of the photo studio in the entire e-commerce supply chain and why measuring productivity is important for everybody involved (including external partners offering photo editing services). Now we dive right into the types of data needed from the different stakeholders, and the insights obtained from interpreting this data.
To make the most effective data-driven decisions, photo studio management needs to ask the right questions. Here are some examples around the important stakeholders in a photo studio, suggested questions that a manager should ask, and the subsequent data that needs to be collected to inform decision makers. Once a sufficient amount of data has been collected (e.g. over 100 days or a year), trends can be identified to inform future predictions and improvement areas.
Full-time staff photographers
- How much time do full-time staff photographers spend on Set shooting, vs. other activities?
- Are they making proper use of equipment and support resources?
- How many shots do they take for each product in a typical day?
- Does their productivity change when interacting with different subject matter?
These type of data collected over time and analyzed will reveal opportunities to make staff photographers more efficient with their skills and time.
The need for freelance photographers can fluctuate seasonally, e.g. right before and during the launch of a new clothing line. Logging this “flex” demand data can help predict future requirements and allocate funds accordingly while also freeing up funds during off-peak times.
Models and product stylists
Model scheduling can have a big impact on photo shoot efficiency and costs.
- Is the studio/client getting the right model for the product at the right time?
- How often does this agency deliver the right model (or provide alternatives)?
- Which product types require a specific type of model that impact availability?
- Does the product stylist take more time in preparing the model to present a specific type of product?
Product samples and sample shipping companies
Punctuality in sample delivery affects different stakeholders within studio operations and externally. Logging in data on sample arrival times; shipping locations/distances; performance of specific shipping companies or specific products can reveal trends that can be used to make operations more productive and cost-effective.
Executive/C-level management (budgeting)
Do C-level executives always make important decisions with enough information at their disposal? A good set of data from different stakeholders can greatly help inform good budget decisions by revealing often unnoticed areas of improvement, necessary budget cuts and opportunities to optimize employee remunerations.
- Is all of the studio equipment owned or rented?
- Can one piece equipment perform the functions of two others by altering scheduling?
Collecting data on type and frequency of use; storage characteristics (e.g. cloud vs. on-premise); and performance on automated and manual operations can inform productivity decisions on technology use and saving money.
An effective relationship between a photo studio and an outsourcing partner (e.g. an image retouching service provider) strongly affects studio operations and output. There are a number of data you can collect on the performance of your outsourcing partner, from how to choose one to how to get the best out of the partnership.
QC team and marketing communications
Stringent quality control adhering to industry best practices boosts productivity. QC related data from different stages of operations, e.g. post-shoot and post-processing, can help identify actions to improve processes and reduce turnaround times.
Measuring and sharing the right type of data benefits all employees. Data helps senior management make effective overall business decisions, and shared data also helps all employees better understand data-driven management decisions and how they can contribute to a more efficient and effective studio operation.