Monday, December 13, 2004

Do you know more about your customers than your staff?

Most businesses know a lot more about their customers than their staff. For retailers loyalty cards have provided masses of data about basket composition, shopping habits, even likeliness to take up offers. For companies selling directly to a smaller number of customers there are feedback programmes, customer research, the list goes on. Ultimately it’s all about one thing – know what makes your customers tick and you are far more likely to be able to add real value.

This value is not just a nice-to-have but an essential. In real terms it can mean more brand loyalty, great spends, better planning of product lines. Lots in fact that can drive higher margins and profit.

So, what does your firm know about its staff. Well, it might know average age, the take up for the pension scheme, the retention rate. Oh, and they probably told you lots of stuff about how they felt in the last employer opinion survey. But my guess is that this does not really tell you much.

What you should be focusing on is WHY they act and think this way. How does work fit into their lives? What gets them up in the morning to come to you, rather than your competitor? What would cause them to leave, or just as bad to mentally bailout?

Generalisations can be worse than no information but this doesn’t mean that you have to understand everyone individually – this would take far too much time and energy and they probably would resent it. What you need is to be able to group these people into groups who share similar behaviors. Marketers call these groups segments

Knowing the behaviors of these segments, and the size of the segments gives you great insight into how your staff are going to behave. You can segment in numerous different ways, and none is ‘right’. Segmenting by attitude to work is one of the more popular ones.

How could you use this information? Let me give you an example. Retailer X offers a competitive salary and a range of benefits that equate to about an additional 30% of salary. It is justifiably proud of its pension scheme.

Retailer X attracts young, fashion-orientated people to work in its stores. The turnover is high, but not uncommon for the industry. Let’s call one fictional employee ‘Sarah’ (the majority are female).

Why does Sarah work? Well she needs the cash, or potentially wants the cash. She still lives with her parents, though she is saving for a deposit for that first flat. She really would like a small car, maybe a Ford Fiesta and once a year Sarah goes to Ibiza with her closest friends. You’ll find Sarah spending quite a high proportion of her salary on nights out with the girls.

Does Sarah really care about that pension – no (although she probably should)? What Sarah would really value is ways to help her realize her ambitions.

Knowing this information the Compensation and Benefits teams speak to Ford and extend that great car-purchase scheme designed for middle managers to enable Sarah to get the great rate on her Fiesta that the company can get. This costs the firm almost nothing, but gives the Sarah lots of reason to stay with the firm. Maybe they do a deal with a travel firm.

Sarah is excited about these new benefits and tells her friends. She encourages two to apply and one joins in a nearby branch.

Once you know about your Sarah’s you can design a whole range of policies that help them. And if you know that 48% of your staff are like Sarah you can predict uptake on policies, likely effects of reorganizations.

Building this thinking into your high performer data will enable you to understand what policies to give to everyone which will specifically appeal to high performers. Or you could use it to help you attract more older workers to your firm.

Just remember, these segments aren’t fixed – people do move between them, usually after significant moments in their lives. However understanding your workforce will give you considerable power to predict and design interventions.