As midsized companies scale, they must increasingly invest in making the work easier and more efficient. While leaders of small firms can see how efficiently the work is progressing, leaders of midsized firms must rely on data and analytics.

First published in Forbes. Read below, or read it on Forbes.

As midsized companies scale, they must increasingly invest in making the work easier and more efficient, since there is so much more activity. While leaders of small firms can see how efficiently the work is progressing, leaders of midsized firms must rely on data and analytics. That means data, and plenty of it. But wanting to make data-driven decisions is not the same as employees actually working more efficiently. Without an established best-practice approach to using the information, data and activity measurement can be chaotic, ineffective, even destabilizing. What’s the best way to drive efficiency with data while supporting and empowering employees?

As companies grow to midsized, leadership becomes distanced from the day to day. Efficiency is harder to assess, and data becomes ever more important. Once the concept of data-driven decision making  is unleashed, however, the executive team may get overexcited by the possibilities, announcing ambitious targets, reaching for off-the-shelf data solutions, and either drowning existing staff in unmanageable data sets or bringing in outside data experts without building internal capacity. Above all, staff may see a data-driven efficiency agenda as threatening, when the whole point is to mobilize them around improving results.

A better way is to build an appreciation of data-driven decision-making gradually. This means introducing it as part of a commitment to continuous improvement – an ongoing, staged process rather than an abrupt, one-off step change. Setting achievable targets establishes a collaborative culture that highlights quality as much or more than merely shaving off production or turn-around time. This enables everyone to share the success, motivates teams around continuing wins, and forges in-house expertise and best-practice habits so the data culture becomes sustainable and self-perpetuating.

“You can only improve things that you measure,” says, Shawn Miele, CEO of MyAdvice, the Park City, Utah-based provider of software marketing solutions for the medical and legal industries. “Once we used data seriously to look at our own workflows, we not only increased profit but also found better ways of working, with better results. The improvement has been at all levels.”

Learning to Count Activity

Increasing efficiency through detailed measurement takes time, investment and care, so the effort will bring real results. Steps to establishing a data-driven culture include:

• Build commitment to a data-driven approach across the senior group, and assess the resources, effort and potential disruption the effort may take as new ways of working take hold.
• Identify or hire a data or operations analyst to set up systems (including time tracking and work management tools), create reports, cleanse the data for accuracy and relevance, and analyze it.
• Detect differences, identifying best-practice techniques, sharing and training them, and then measure again to note change.
• Find and promote early wins to gain buy-in, either in the way a product is produced or how less profitable clients are handled – inefficient practices are often not very enjoyable either.
• For a year or more after introducing activity measurements, never accuse anyone of slacking, as this shifts the focus to exactly where people will resist.
• Do reallocate work away from those hard-working employees overloaded with impossible levels of work, distributing work more evenly or hiring more people to spread the load – another win.
• Celebrate improvement. Set up a routine review of the process (say, quarterly), and ensure consultation and staff input to address problems and talk over any concerns or resistance.

Some staff may find performance measurement unsettling. They may resist and will need time and discussion to adjust. Some staff will never buy into data-based measurement at this level, and so may not remain a longer-term fit. Take time and care to introduce the concept – to avoid any hint of catching out underperforming staff or imposing an unsustainable pace of work. Yes, it’s to enable faster growth, but also for competitive advantage, better work practices, improved outputs.

MyAdvice Software Example

Software companies live and breathe data. But using that information firepower to analyze their own work processes can still be a challenge – even if worthwhile in the end.

MyAdvice is a Software-as-a-Service (SaaS) company of more than 150 staff across three offices in the west and east coasts and three offshore locations, in India, the Philippines and Australia. They market a suite of software products focusing on websites, search-engine optimization (SEO) and social media to improve digital marketing for doctors and dentists, vets, law firms and others.

“Every one of our people, you could compare them to a person working at a workstation on a manufacturing assembly line,” says CEO Miele. “And you can measure their output and the quality of their output. Over the past few years, we have been developing all these metrics.”

The principal driver the data-analysts approach was when the company started using objectives and key results (OKRs) and realized they needed better measurements internally.

“All of the key results in an OKR should be both time-bound and measured numerically. And having adopted OKRs really forced us to be very intellectually honest about our results,” recalls Miele.

An important part of the initial effort was to focus on breaking down the specific phases of work, say in developing a website, then defining and clarifying roles and functions so the job could be measured meaningfully and the efficiency assessed.

“Then we started measuring how many days in each phase of development over seven or eight different phases,” explains Miele. “Once we had measurements, we started trying to improve each of those phases a little bit.”

At one Mastering Midsized client, an early win was to focus on customers who were overly demanding and created headaches for the team. Such clients can delay production times and cause havoc with scheduling. The analytical work made these customers stand out, and the company worked to raise their prices and minimize this work. Employees applauded.

This client had a person in marketing who loved data and was instrumental in managing the process and setting up the analytics group. For data collection, they used Harvest for time-tracking in conjunction with Asana for work-management. All this still brought a cost, but well worth it.

“You just have to make the investment,” says Miele. “We use an EBITDA profitability measurement, and at the get-go, it’s going to cut into your EBITDA. But if you take a longer-term perspective on it, you realize that the data you’re developing will allow you to become better, with a higher quality and a higher throughput, and therefore more profitable.”

Last year, they instituted central processes for their SEO practice so that everybody was doing the same things in the same way. They use technology to show what tasks should be done, and video training for the how-to. This simple process automation increased the efficiency of that department by 15%. They also noted a significant improvement in customer retention in this product area, bringing it into line with the company average.

“Measurement has helped the teams focus, and that’s where a lot of the change has come,” explains Miele. “I’ve had department heads come up to me and say, ‘Gosh, this quarter was amazing, because we said we’re going to do these three things. And it really kept us focused on those three things, instead of chasing other things that might not be as important.’”

Where they can, they identify targets and allocate them across the departments, so the departments can drive them. This year, every department has been tasked with trying to get 10% better on both quantity and quality. Miele held a series of meetings with the customer success department, for example, starting with the team leads and then with their direct reports. The aim was to solicit ideas for what they could do to press on with the 10% initiative. Not everyone has bought into it, and some resist these kinds of measurements, so personal engagement and consultation helps.

There is a lot of art behind SEO, which means that many people on this team do whatever they think they should on a given day without any real science or process behind it. The company started demanding that a science be installed – and be followed. There was a lot of unease at first in that group that they were losing some of their freedom, but when they saw the results, most people came around. Not everybody, though, and those who are not on board have been slowly self-selecting themselves out of the organization.

“Not everybody buys into it, so you have to be kind and gentle about it,” acknowledges Miele. “I would say there is a bit of cultural resistance to data-based measurement in our domestic workforce. Time-study measurements are more common in our offshore centers. Staff at home are more resistant to having their work measured this way.”

High performers also need a push. “High performers embrace the idea readily, but they don’t always contribute as much as we might like, partly because they’re so busy,” says Miele. “So, we have to urge them to put a real focus on making quality improvement part of their everyday job.”

Data Based Improvement

Introducing a data-based improvement approach takes care, but it can bring huge benefits. Metrics reveal areas for improvement. By measuring activities, data analysts and industrial engineers help companies go granular to put in place changes that produce more efficient results. They also help identify incremental improvements that make work easier for everyone. Improving productivity over time makes companies more profitable, more competitive and more sustainable. It should be a win for all.

MyAdvice has seen a significant increase in their gross margin over the past year, an improvement they put down to data-driven improvement. Now they are thinking of hiring another data analyst, this time possibly in one of their offshore offices.

“We frame everything here through the lens of the customer, with both an efficiency and a quality measurement, you’ve got to have both,” says Miele. “But if you do, you are really creating time to value for the customer – improving the customer’s experience, our own work flows and the company’s bottom line.”