Jan 2019

Large (legacy) corporates have woken up to the value that data analytics can create for them. While large organisations in the US and to some extent in Europe saw this opportunity a while back, Asian corporates have been behind in the use of data to solve customer pain points, develop new products, build new customer experiences, and drive value from existing customers. 

However they have started to realise the role that data plays in their next evolution of growth. But they have several challenges to overcome.

It is about time for these legacy companies to really step on the data accelerator or they will get marginalized as new digital first companies take hold in their sectors. The digital first companies are data first natives and hence their business models evolve from data. They quickly roll out new offerings, expand beyond their core products, and understand customer needs much faster. That is because all their decisions are driven by the value of the data they have. 

The key difference is that digital first companies belief that they are running a data and technology company first and the product innovation follows from what the customer data is telling them.  To them, products are just solutions to solve the customer pain points. As they are focused on solving customer pain points (once they decide what pain point to solve), the product is just a way to solve that pain point. Customer is first, product is second. They interact with their customers through the data and tech. Data tells them what the customers are doing vs. what they want to hear about their products. This is a big difference. Legacy companies do product research and product surveys, digital companies analyse customer journeys and pain points using data. Digital companies use data to drive product acceptance (you all are very familiar with custom play lists of Spotify or basket recommendation of online grocery stores), rather than product sales.

This is why it is so hard to define the products of digital companies. Digital companies solve broad customer problems across the customer journey. For example, why is an online book retailer into groceries and into cloud technologies? Why is an online retailer company into payments? Why is a digital gaming company into online retail?  Why is a transportation company into home solutions, payments, pick-up and delivery sectors? To digital native companies, all are customer pain points in their seamless journey with the firm. The products are just solutions to make that total journey easier and more seamless. On the other hand legacy companies still continue to be very “sector” specific product companies and their total organization is aligned to similar product P&L’s.

In this new world, we have to redefine what is a firm’s asset. For digital companies their core asset is “DATA”. And this is the angle that digital first companies play on.  Data is the single most valuable, intangible, and priceless asset they own.   Every company measures a metric called “Return on Asset”. A digital company sees data as their core asset and measures the data’s RoA. Let’s call it “Return on Data Asset (RoDA)”. To them as long as RoDA is a solution to a customer pain point, they will launch products to solve them. It’s no different than a legacy company builds a factory and wants to run at 100% capacity or builds a call center and uses it for service and sales. Digital first companies are also optimising their resources – it just happens to be data. I believe that the firms have to develop a RoDA concept for the future. That will make data move from intangible to tangible value and hence suppliers of that asset (customers in this case) would be able to see the value of that asset to the firm. As a sidebar – maybe the customers can then ask for premium for this asset that they contribute to the growth.

If legacy companies can quickly see how much data they have and build their own RoDA, they can start to play at the same level as digital disruptors and win at this game. Growth will follow.

There are two key observations that are important before I give some perspective on how legacy corporates can win in the data game.

1.    Organizational Dynamics– Every employee at digital first company is a data and tech person. There is little to no separation between business (product P&L managers) and data people. All leaders in digital first companies have grown with data and digital, hence make unemotional decisions based on data, and have no legacy holdings to products. They simply want customer usage and engagement. That is why these new age companies have leaders with little or no experience in the very sectors they disrupt, don’t have layers of management with decades of similar experience, and don’t hold on to believes that they can’t break. Legacy companies on the other hand have different “departments” for data and digital with C-level titles within those. They have further creative ways to distinguish these groups. They call them functional organizations or horizontal departments. They also use scenario’s like “use-case”; “proof of concept” where the product departments spent time justifying the cost of data rather than focusing on benefit of the data and it’s use. If in today’s world we have to “justify” and “proof” value of data then the game is already lost.

2.    Customer costs– Legacy corporates that have been in existence for a while traditionally have a low cost of acquiring a new customer but high cost of servicing them (given the infrastructure they have built).  On the other side are digital natives that have high cost of acquisitions (promo codes, freemium models) but low cost of servicing (digital and tech driven). This makes for a big difference in lifetime value of an acquired customer (leaving accounting treatment aside) between the two firms. The difference is in maximizing value of each customer through engagement (digital natives) vs. optimizing the revenue and cost model (legacy companies). Each product must produce it’s own P&L in legacy organizations. How many times have we heard that.  They ask for paybacks, return on investments, profitability of each product marketed to the customer, expense per customer etc. Because the organization is product centric, they use the data to justify the product existence, the product teams, and reward employees for maximizing product profitability. They hardly use the data to drive customer value.

So that brings my view on how legacy companies can really change the game.

  1. Start from the top– Review your organizational set-up and management experience. How many of your leaders and mid level management are data or tech experienced? How many of your managers have come out of tech or data science departments? I believe and digital native companies have shown this that data and tech knowledge is more important than years of product knowledge.
  2. Rethink of how you manage P&L’s – You don’t have to remove product managers or take away P&L’s but you can certainly reweight on revenue vs. expenses. Give each product head to grow revenue and relieve them of things like direct expenses, allocated expenses, group office expenses etc. The amount of time these managers spent doing reviews of their expenses can be well spent on solving customer pain points using data.
  3. Give the leaders clear goals on data and tech usage– Be very careful here. I am not talking about items like digital customer service, digital statements, paper reduction but truly change the way that the product managers make decisions using data and digital that is unemotional and unbiased from human viewpoints. Maybe bring people that have no experience in those products at all to evaluate business models.
  4. Build your data architecture– This is very critical. I don’t think legacy company leadership fully appreciates the different types of skills and capabilities needed to build a data driven organization. You need expertise and knowledge to build and staff a data driven platform.
  5. Expand your data talent pool – Don’t just hire data people in the data science departments. Don’t count your data capabilities by saying you have a large data science team.  Hire them across all groups – product, sales, finance, service, design and give them key role in decision making. 

I do agree that such change is big and radical. The larger the legacy corporates the harder it will be. So I do recommend that you will need dedicated data leaders for near term as you change the internal perspective. But you must change the perspective and have clear targets on the above. You may use external help as you go through this transformation. But my humble view is do it both, hire analytical talent that drives value from data and organisational changes that not only accepts that value, but asks for more and leads the change to the data driven organization. 

This blog is a guest contribution by Sandeep Bhalla, which was first published on his personal LinkedIn account.

Sandeep Bhalla