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TECHNOLOGY IN RETAIL : ESCAPING THE COMPLEXITY TRAP
Simplifying and modernizing tech is getting even harder , but industry leaders show a path forward
By Yukiko Tsukamoto , Donna Enverga and Marc-André Kamel
They understand and commit to the required investment , aided by their transparent approach to spending and a clear-eyed knowledge of both their tech debt and their capacity to spend more . They build the capability to realize value at speed by adopting Agile methodologies early , focusing on products rather than projects , deploying internal engineering squads at scale , and actively managing the failure risks involved in complex change .
Yukiko Tsukamoto is Partner at Bain & Company based in Manila . Donna Enverga is a Partner based in Melbourne . Marc-André Kamel leads Bain ’ s global retail practice and is a partner based in Paris .
Technology modernization is one of the hardest items on the executive to-do list in retail . When we surveyed retail CEOs on the issue , 9 out of 10 said their company lacked at least some of the capabilities needed to build on its tech strategy . Furthermore , a quarter said returns on technology investment didn ’ t meet their expectations , while 80 % felt the unpredictability of the market ’ s response to tech initiatives was an obstacle to achieving tech goals .
As if this weren ’ t challenging enough , tech modernization is only likely to become more daunting over the short to medium term . Margin erosion is already limiting funds available to invest in transformation projects . That may exacerbate the tendency to spread the technology investment budget too thinly across competing initiatives . Further complications also loom large , such as the accelerating deployment of generative AI .
For retailers that are good but not yet great at technology , this all adds up to a pivotal moment . Can they grasp a shrinking opportunity to update and future-proof their technology systems ? Drawing on our work with top retail and technology businesses around the world , we see a path for many retailers to make the progression to excellence by emulating the industry ’ s current tech leaders .
Above all , what differentiates these leading companies is their understanding of the strategic importance of technology . We found plenty of evidence of that when we analyzed 45 of the world ’ s biggest retailers . The people steering high-performing companies within this group had a much stronger tech background than those at the cohort ’ s weaker competitors , for instance . On average , 16 % of board members and executives at the high-performing retailers we analyzed had tech experience , vs . 7 % at low performers .
As well as fully appreciating the strategic importance of technology and tightly focusing their tech spending on areas of competitive differentiation , leaders also tend to do three things :
They embrace modular and flexible architecture , allowing them to innovate in domains that are critical to competitive differentiation , while standardizing solutions and services across channels and business units to capture scale benefits .
What ’ s more , winners continually focus on managing their run costs so that keeping the lights on doesn ’ t crowd out investments in growth and innovation . In our experience , the right balance can often be achieved by limiting the cost of maintaining core retail capabilities to about 70 % of spending , allowing 25 % to flow through to modernizing and optimizing current processes and systems , and 5 % to transformational innovations with long-term returns .
We ’ ve highlighted how leaders differentiate themselves through their architecture , their investment posture , and their delivery capabilities . Below , we focus on specific actions that can help retailers raise their game in these three crucial areas .
Embrace modular and flexible architecture . Develop a modular and loosely coupled architecture , which guides ongoing choices on solution selection and upgrades . Establish clear build vs . buy guidelines based on strategic differentiation , investment posture , and speed to market . Consider maximizing scale efficiencies through the development and reuse of common services across channels and platforms . Build a data architecture that enables easy access to critical data assets , to enable both analytical and AI-powered use cases . Continually measure developer productivity and streamline engineering processes .
Understand and commit to the required investment . Align company leaders and engage the board on the required investment , informed by the scale of technical debt and capacity to increase technology investment . Figure out whether investment will follow “ a pig through a python ” template — meaning a threeto five-year bulge in investment to fund modernization . Get granular visibility of technology spending and ruthlessly manage down run costs to reinvest in change and innovation .
Build the capability to realize value at speed . Strengthen the technology delivery model via adoption of agile , product-oriented teams . Be mindful of which product teams should operate horizontally to deliver cross-functional experiences . Free delivery teams from unnecessary oversight and bureaucracy . Adopt DevOps principles of end-to-end , “ development-to-run ” ownership , along with automation to improve the reliability and quality of releases . Insource engineering and UX leadership talent . Foster greater accountability for outcomes by defining and implementing metrics based on objectives and key results ( OKR ).
While all of these areas are vital , the sequencing will vary a lot between companies , depending on their needs and priorities . Similarly , executive teams will need to gauge the right balance between building completely new systems and upgrading existing ones . 16 17